From 8a7150f763d92815045c45d8ea741caf9db12bcd Mon Sep 17 00:00:00 2001 From: sherwoodf <161822064+sherwoodf@users.noreply.github.com> Date: Thu, 12 Dec 2024 13:39:23 +0000 Subject: [PATCH] added option to override biostudies submission in order to make point fixes (#265) * added option to override biostudies submission in order to make point fixes * expanded overrides * updated to overrides --- bia-ingest/bia_ingest/biostudies/api.py | 33 + .../S-BIAD1076/S-BIAD1076_original.json | 356 ++ .../S-BIAD1076/S-BIAD1076_override.json | 350 ++ .../S-BIAD1136/S-BIAD1136_original.json | 221 + .../S-BIAD1136/S-BIAD1136_override.json | 221 + .../S-BIAD1223/S-BIAD1223_original.json | 336 ++ .../S-BIAD1223/S-BIAD1223_override.json | 336 ++ .../S-BIAD1261/S-BIAD1261_original.json | 123 + .../S-BIAD1261/S-BIAD1261_override.json | 126 + .../S-BIAD1344/S-BIAD1344_original.json | 280 ++ .../S-BIAD1344/S-BIAD1344_override.json | 280 ++ .../S-BIAD15/S-BIAD15_original.json | 219 + .../S-BIAD15/S-BIAD15_override.json | 160 + .../S-BIAD954/S-BIAD954_original.json | 300 ++ .../S-BIAD954/S-BIAD954_override.json | 300 ++ .../S-BIAD978/S-BIAD978_original.json | 154 + .../S-BIAD978/S-BIAD978_override.json | 154 + .../biostudies/S-BSMS4/S-BSMS4_original.json | 3762 ++++++++++++++++ .../biostudies/S-BSMS4/S-BSMS4_override.json | 3768 +++++++++++++++++ .../S-BSST651/S-BSST651_original.json | 107 + .../S-BSST651/S-BSST651_override.json | 107 + .../S-BSST744/S-BSST744_original.json | 284 ++ .../S-BSST744/S-BSST744_override.json | 284 ++ 23 files changed, 12261 insertions(+) create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1136/S-BIAD1136_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1136/S-BIAD1136_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSMS4/S-BSMS4_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSMS4/S-BSMS4_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_override.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_original.json create mode 100644 bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_override.json diff --git a/bia-ingest/bia_ingest/biostudies/api.py b/bia-ingest/bia_ingest/biostudies/api.py index caeb2148..e3f2237a 100644 --- a/bia-ingest/bia_ingest/biostudies/api.py +++ b/bia-ingest/bia_ingest/biostudies/api.py @@ -188,6 +188,39 @@ def load_submission_table_info(accession_id: str) -> SubmissionTable: def load_submission(accession_id: str) -> Submission: + # Note this is a dictionary to include reasons why the override was made + overrides = { + "S-BSMS4": "Author links to affiliations were missing 'reference: true'", + "S-BIAD15": "Invalid licence, and affilicaiton was missing accno", + "S-BIAD1076": "Biosample had the Experimental variables text split up into 3 sections, possibly due to commas?", + "S-BIAD1261": "Author had no name, and the email was for a whole lab. Name added as Cytology Department RUB", + "S-BIAD978": "Unreferenced Image analysis-5, and a broken association to image analysis 1 (that doesn't exist)", + "S-BIAD954": "invalid email: Julia Nöth changed to: julia.noeth@ufz.de", + "S-BIAD1136": "invalid email: oona.paavolainen@ut changed to: oona.k.paavolainen@utu.fi (same ending as other authors - seemed to be missing the .k. based off google search)", + "S-BIAD1223": "invalid email: ylva.ivarsson@kemi..u.se changed to: ylva.ivarsson@kemi.uu.se", + "S-BIAD1344": "invalid email: raffaeledefilippis92@gmail.comraffaeledefilippis92@gmail.com changed to: raffaeledefilippis92@gmail.com", + "S-BSST651": "invalid email: huw.williams@williams@nottingham.ac.uk changed to: huw.williams@nottingham.ac.uk", + "S-BSST744": "invalid email: ‫britta.engelhardt@tki.unibe.ch (right-to-left embedding) changed to: britta.engelhardt@tki.unibe.ch", + } + if accession_id in overrides: + return read_override(accession_id) + else: + return submission_from_biostudies_api(accession_id) + + +def read_override(accession_id: str) -> Submission: + submission_path = pathlib.Path( + "submission_overrides/biostudies", accession_id, f"{accession_id}_override.json" + ) + abs_path = submission_path.absolute() + logger.info(f"Reading submission from {abs_path}") + file = abs_path.read_text() + submission = Submission.model_validate_json(file) + assert submission.accno == accession_id + return submission + + +def submission_from_biostudies_api(accession_id) -> Submission: url = STUDY_URL_TEMPLATE.format(accession=accession_id) logger.info(f"Fetching submission from {url}") headers = { diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_original.json new file mode 100644 index 00000000..7383ed10 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_original.json @@ -0,0 +1,356 @@ +{ + "accno" : "S-BIAD1076", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.MIFA.v1" + }, { + "name" : "REMBI_PageTab Conversion Script Version", + "value" : "1.0.0" + }, { + "name" : "Title", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "ReleaseDate", + "value" : "2024-04-01" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Description", + "value" : "Mini-immunofluorescence assay that builds on a custom neural network-based image analysis pipeline for automated and multiplexed detection of immunoglobulins (IgG, IgA, and IgM) in patient samples." + }, { + "name" : "Keyword", + "value" : "COVID-19" + }, { + "name" : "Keyword", + "value" : "SARS-CoV-2" + }, { + "name" : "Keyword", + "value" : "high-content imaging" + }, { + "name" : "Keyword", + "value" : "antibody response" + }, { + "name" : "Keyword", + "value" : "machine-learning" + }, { + "name" : "Keyword", + "value" : "immunofluorescence" + }, { + "name" : "Keyword", + "value" : "serology" + }, { + "name" : "Keyword", + "value" : "virus" + }, { + "name" : "Acknowledgements", + "value" : "The authors thank the Minerva Institute (Helsinki, Finland) for providing utilities for the project, Prof. Perttu Hämäläinen (Aalto University, Finland) for providing the expertise of his group for the project, the FIMM High Throughput Biomedicine Unit for providing access to high-throughput robotics, the FIMM High Content Imaging and Analysis Unit for HC imaging and analysis (HiLIFE, University of Helsinki and Biocenter Finland; EuroBioImaging, ISIDORe partner), and the CSC – IT Center for Science, Finland, for computational resources." + }, { + "name" : "Funding statement", + "value" : "We acknowledge support from the LENDULET-BIOMAG grant (2018-342), from the European Regional Development Funds (GINOP-2.3.2-15-2016-00006, GINOP-2.3.2-15-2016-00026, and GINOP-2.3.2-15-2016-00037), from the H2020-discovAIR (874656), from the H2020 ATTRACT-SpheroidPicker, and from the Chan Zuckerberg Initiative, Seed Networks for the HCA-DVP. The Finnish TEKES/BusinessFinland FiDiPro Fellow Grant 40294/13 (to V.P., O.K., L.P., and P.H.), grants awarded by the Academy of Finland (iCOIN-336496 to O.K., V.P., and O.V.; 308613 to J.H.; 321809 to T.S.; 310552 to L.P.; 337530 to I.J.; and FIRI2020-337036 to FIMM-HCA, A.H., L.P., V.P., and P.H.), the EU H2020 VEO project (O.V.), and a Minerva Foundation for COVID-19 Research project grant (to V.P.) are also acknowledged. C.G. is funded by the Academy of Finland Flagship program, Finnish Center for Artificial Intelligence. OrthoSera Ltd. was funded by NKFIH grants (2020-1.1.6-JÖVŐ-2021-00010 and TKP2020-NKA-17).Networks for the HCA-DVP, the Finnish TEKES FiDiPro Fellow Grant 40294/13 (VP, OK, LP, PH), grants awarded by the Academy of Finland (iCOIN-336496: OK, VP, OV; 308613: JH; 321809: TS; 310552: LP; 337530: IJ, FIRI2020-337036: FIMM-HCA, AH, LP, VP, PH), the EU H2020 VEO project (OV), Minerva Foundation COVID-19 research project grant (VP), the Academy of Finland Flagship programme (CG, Finnish Center for Artificial Intelligence), and NKFIH grants (2020-1.1.6-JOVO-2021-00010, and TKP2020-NKA-17) to OrthoSera Ltd. I.K. receives funding from EU Horizon 2020 under grant agreement no. 101046203 (BY-COVID)." + } ], + "links" : [ { + "url" : "https://github.com/fimm-covid-19-hca/mini-IFA_paper", + "attributes" : [ { + "name" : "Description", + "value" : "Supplementary code of machine-learning model training, prediction and evaluation pipeline" + } ] + }, { + "url" : "https://dx.doi.org/10.5281/zenodo.6352550", + "attributes" : [ { + "name" : "Description", + "value" : "Extracted single-cell features from microscopic images to train and test models" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Lassi Paavolainen" + }, { + "name" : "E-mail", + "value" : "lassi.paavolainen@helsinki.fi" + }, { + "name" : "Role", + "value" : "submitter, data acquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0000-0003-1508-2718" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Antti Hassinen" + }, { + "name" : "E-mail", + "value" : "antti.hassinen@helsinki.fi" + }, { + "name" : "Role", + "value" : "data aquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0000-0001-9491-2868" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Minttu Polso" + }, { + "name" : "E-mail", + "value" : "minttu.polso@helsinki.fi" + }, { + "name" : "Role", + "value" : "data aquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0009-0007-2029-9707" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Vilja Pietiäinen" + }, { + "name" : "E-mail", + "value" : "vilja.pietiainen@helsinki.fi" + }, { + "name" : "Role", + "value" : "first author, corresponding author" + }, { + "name" : "ORCID", + "value" : "0000-0003-3125-2406" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Isabel Kemmer" + }, { + "name" : "E-mail", + "value" : "isabel.kemmer@eurobioimaging.eu" + }, { + "name" : "Role", + "value" : "data steward" + }, { + "name" : "ORCID", + "value" : "0000-0002-8799-4671" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organization", + "attributes" : [ { + "name" : "Name", + "value" : "Euro-BioImaging ERIC" + }, { + "name" : "Address", + "value" : "Euro-BioImaging Bio-Hub, EMBL, Meyerhofstrasse 1, 69117 Heidelberg." + } ] + }, { + "accno" : "o2", + "type" : "organization", + "attributes" : [ { + "name" : "Name", + "value" : "Institute for Molecular Medicine Finland" + }, { + "name" : "Address", + "value" : "P.O.Box 20, FI-00014 University of Helsinki, Finland" + } ] + }, { + "type" : "Publication", + "attributes" : [ { + "name" : "Title", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "Year", + "value" : "2023" + }, { + "name" : "Authors", + "value" : "Vilja Pietiäinen, Minttu Polso, Ede Migh, Christian Guckelsberger, Maria Harmati, Akos Diosdi, Laura Turunen, Antti Hassinen, Swapnil Potdar, Annika Koponen, Edina Gyukity Sebestyen, Ferenc Kovacs, Andras Kriston, Reka Hollandi, Katalin Burian, Gabriella Terhes, Adam Visnyovszki, Eszter Fodor, Zsombor Lacza, Anu Kantele, Pekka Kolehmainen, Laura Kakkola, Tomas Strandin, Lev Levanov, Olli Kallioniemi, Lajos Kemeny, Ilkka Julkunen, Olli Vapalahti, Krisztina Buzas, Lassi Paavolainen, Peter Horvath, Jussi Hepojoki" + }, { + "name" : "DOI", + "value" : "https://doi.org/10.1016/j.crmeth.2023.100565" + }, { + "name" : "PMC ID", + "value" : "37671026" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Biosample" + }, { + "name" : "Biological entity", + "value" : "Vero E6 cells" + }, { + "name" : "Description", + "value" : "African green monkey kidney cell line, ATCC; mycoplasma tested" + }, { + "name" : "Intrinsic variable", + "value" : "cells transfected to express SARS-CoV-2 antigens: N [nucleo proteins], M [Membrane], R [Receptor-binding domain], and S [Spike]" + }, { + "name" : "Extrinsic variable", + "value" : "addition of serum samples obtained from positive (COVID-19+) and negative (COVID-19–) patients" + }, { + "name" : "Experimental variable", + "value" : "imaging of four different fluorescent channels to detect three immunoglobulins (IgG" + }, { + "name" : "Experimental variable", + "value" : "IgA" + }, { + "name" : "Experimental variable", + "value" : "IgM; binding to transiently transfected virus antigens) with fluorescently labelled secondary antibodies and cell nuclei" + } ], + "subsections" : [ { + "accno" : "Organism-1", + "type" : "Organism", + "attributes" : [ { + "name" : "Scientific name", + "value" : "Chlorocebus aethiops" + }, { + "name" : "Common name", + "value" : "African green monkey" + }, { + "name" : "NCBI taxon ID", + "value" : "NCBI:txid9534" + } ] + } ] + }, { + "accno" : "Specimen-1", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Specimen" + }, { + "name" : "Sample Preparation Protocol", + "value" : "The transiently transfected Vero E6 cells on 384-well plates were fixed with 4 % PFA and washed before storing at +4° C. For control purposes, Hoechst 33342 (Invitrogen H1399) was added to serum samples before aquiring them to plate (final concentration of Hoechst on plates was 1:5000). Protocol: The transfected and fixed Vero E6 cells were permeabilized and blocked with 3 % BSA-TBSTx (0.25 %) and incubated at RT for 15 min before washing. Serum samples (including Hoechst) were dispensed to wells in 1/100 and 1/50 dilutions and incubated at RT for 1.5 h followed by washing with TBS. A secondary antibody mixture with Alexa Fluor 647 Anti-Human Serum IgA (1/1000 dilution, ), anti-Human IgM Alexa Fluor 488 (1/1000 dilution, Invitrogen A-21215) and anti-Human IgG DyLight 550 Secondary Antibody (1/500 dilution, Invitrogen SA5-10135) was used to detect the SARS-CoV-2 antibodies from plates." + }, { + "name" : "Growth Protocol", + "value" : "Vero E6 Cells were transfected with plasmid DNA (S-pCAGG, RBD-pCAGG, N-pCAGG or M-pEBB) and incubated at RT for 15-30 min. The cells were then seeded to a 384 plate and incubated for 48 hours at 37° C with 5 % CO2. The plasmids: S-pCAGGS, SARS-CoV-2 spike protein/plasmid (Amanat et al. 2020. A serological assay to detect SARS-CoV-2 seroconversion in humans); RBD-pCAGGS, SARS-CoV-2 receptor-binding domain/plasmid (Amanat et al. 2020); NP-pCAGGS, SARS-CoV-2 nucleoprotein/plasmid (Rusanen et al. 2021. A 10-Minute “Mix and Read” Antibody Assay for SARS-CoV-2), M-pEBB, SARS-CoV-2 membrane, protein/plasmid, hCoV-19/Finland/1/2020, (Genbank accession MT020781) with pEBB-N-HA mammalian expression plasmid." + } ] + }, { + "accno" : "Image Acquisition-1", + "type" : "Image Acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Acquisition" + }, { + "name" : "Imaging Instrument", + "value" : "PerkinElmer Opera Phenix high-throughput spinning disc confocal microscope using Harmony 4.9 software, 20x water-immersion objective (NA 1.0, working distance 1.7 mm, depth of focus 1.8 μm, effective xy resolution 0.66 μm) and two Andor Zyla sCMOS cameras" + }, { + "name" : "Image Acquisition Parameters", + "value" : "Two-peak autofocus in confocal mode with binning 1, Four excitation lasers (ex) with 100% laser power and emission band-pass filters (em) were used: Channel 1 (Hoechst): ex 405 nm, em 435-480 nm, 100 ms exposure time Channel 2 (IgM): ex 488 nm, em 500-550 nm, 100 ms exposure time Channel 3 (IgG): ex 561 nm, em 570-630 nm, 200 ms exposure time Channel 4 (IgA): ex 640 nm, em 650-760 nm, 200 ms exposure time A grid of nine adjacent fields selected from the center of the well, 5 % overlap between the images. Area of the selection is 3,83 mm^2 or 36 % of the total well area. Z-stack of 2 fields selected, first plane at -4.0 µm, 3 µm distance between planes" + }, { + "name" : "Image data: file format: TIFF, Bit depth: 16 bit, Image dimensions: 2160x2160 px, pixel size: 0.298988040478381 µm" + } ], + "subsections" : [ { + "accno" : "Imaging Method-1", + "type" : "Imaging Method", + "attributes" : [ { + "name" : "Ontology Value", + "value" : "spinning disk confocal microscopy" + }, { + "name" : "Ontology Name", + "value" : "Biological Imaging Methods Ontology (FBbi)" + }, { + "name" : "Ontology Term ID", + "value" : "http://purl.obolibrary.org/obo/FBbi_00000253" + } ] + } ] + }, { + "accno" : "Image-Analysis-1", + "type" : "Image Analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Analysis" + }, { + "name" : "Image Analysis Overview", + "value" : "Images were processed using BIAS software (Mund et al., 2021; Piccinini et al., 2017). Pipeline created for the analysis consisted of pre-processing of the images, and nuclear/cell segmentation. In the pre-processing, a maximum intensity projection was created from each stack of images in different focus depths. Non-uniform illumination was corrected separately for each channel using the CIDRE method (Smith et al., 2015)." + } ] + }, { + "accno" : "Annotations-1", + "type" : "Annotations", + "attributes" : [ { + "name" : "Title", + "value" : "Segmentation masks" + }, { + "name" : "Annotation Overview", + "value" : "Segmentations underlying the machine learning-guided image analysis. Machine learning is employed for (i) nuclei and cell segmentation, and (ii) phenotypic cell classification." + }, { + "name" : "Annotation Type", + "value" : "segmentation_mask" + }, { + "name" : "Annotation Method", + "value" : "Pre-trained deep learning segmentation method (Hollandi et al., 2020) was applied to segment nuclei in images. From these nuclei regions, two additional segmented regions were defined: 1) the cells were defined by dilating nuclei regions with maximum 7 μm radius so that adjacent cells did not overlap, and 2) cytoplasm regions were defined by subtracting nuclei segmentation from the cell segmentation." + }, { + "name" : "File List", + "value" : "file_list_annotations.json" + } ], + "subsections" : [ { + "type" : "Version", + "attributes" : [ { + "name" : "Annotation version", + "value" : "1.0" + }, { + "name" : "Version timestamp", + "value" : "2024-03-06 16:30:00" + } ] + } ] + }, { + "accno" : "Study Component-1", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "Description", + "value" : "Images underlying the machine learning-guided image analysis. Vero E6 cells, transfected to express SARS-CoV-2 antigens (N, M, R, and S), are fixed in 384-well plates for incubation with serum samples. The immunoglobulins (IgG, IgA, and IgM) are detected simultaneously with fluorophore-labelled secondary antibodies using automated high-content fluorescence microscopy. Machine learning is employed for (i) nuclei and cell segmentation, and (ii) phenotypic cell classification." + }, { + "name" : "File List", + "value" : "file_list_images.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Specimen" + }, { + "name" : "Image acquisition", + "value" : "Acquisition" + }, { + "name" : "Image Analysis", + "value" : "Analysis" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_override.json new file mode 100644 index 00000000..bae688e1 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1076/S-BIAD1076_override.json @@ -0,0 +1,350 @@ +{ + "accno" : "S-BIAD1076", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.MIFA.v1" + }, { + "name" : "REMBI_PageTab Conversion Script Version", + "value" : "1.0.0" + }, { + "name" : "Title", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "ReleaseDate", + "value" : "2024-04-01" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Description", + "value" : "Mini-immunofluorescence assay that builds on a custom neural network-based image analysis pipeline for automated and multiplexed detection of immunoglobulins (IgG, IgA, and IgM) in patient samples." + }, { + "name" : "Keyword", + "value" : "COVID-19" + }, { + "name" : "Keyword", + "value" : "SARS-CoV-2" + }, { + "name" : "Keyword", + "value" : "high-content imaging" + }, { + "name" : "Keyword", + "value" : "antibody response" + }, { + "name" : "Keyword", + "value" : "machine-learning" + }, { + "name" : "Keyword", + "value" : "immunofluorescence" + }, { + "name" : "Keyword", + "value" : "serology" + }, { + "name" : "Keyword", + "value" : "virus" + }, { + "name" : "Acknowledgements", + "value" : "The authors thank the Minerva Institute (Helsinki, Finland) for providing utilities for the project, Prof. Perttu Hämäläinen (Aalto University, Finland) for providing the expertise of his group for the project, the FIMM High Throughput Biomedicine Unit for providing access to high-throughput robotics, the FIMM High Content Imaging and Analysis Unit for HC imaging and analysis (HiLIFE, University of Helsinki and Biocenter Finland; EuroBioImaging, ISIDORe partner), and the CSC – IT Center for Science, Finland, for computational resources." + }, { + "name" : "Funding statement", + "value" : "We acknowledge support from the LENDULET-BIOMAG grant (2018-342), from the European Regional Development Funds (GINOP-2.3.2-15-2016-00006, GINOP-2.3.2-15-2016-00026, and GINOP-2.3.2-15-2016-00037), from the H2020-discovAIR (874656), from the H2020 ATTRACT-SpheroidPicker, and from the Chan Zuckerberg Initiative, Seed Networks for the HCA-DVP. The Finnish TEKES/BusinessFinland FiDiPro Fellow Grant 40294/13 (to V.P., O.K., L.P., and P.H.), grants awarded by the Academy of Finland (iCOIN-336496 to O.K., V.P., and O.V.; 308613 to J.H.; 321809 to T.S.; 310552 to L.P.; 337530 to I.J.; and FIRI2020-337036 to FIMM-HCA, A.H., L.P., V.P., and P.H.), the EU H2020 VEO project (O.V.), and a Minerva Foundation for COVID-19 Research project grant (to V.P.) are also acknowledged. C.G. is funded by the Academy of Finland Flagship program, Finnish Center for Artificial Intelligence. OrthoSera Ltd. was funded by NKFIH grants (2020-1.1.6-JÖVŐ-2021-00010 and TKP2020-NKA-17).Networks for the HCA-DVP, the Finnish TEKES FiDiPro Fellow Grant 40294/13 (VP, OK, LP, PH), grants awarded by the Academy of Finland (iCOIN-336496: OK, VP, OV; 308613: JH; 321809: TS; 310552: LP; 337530: IJ, FIRI2020-337036: FIMM-HCA, AH, LP, VP, PH), the EU H2020 VEO project (OV), Minerva Foundation COVID-19 research project grant (VP), the Academy of Finland Flagship programme (CG, Finnish Center for Artificial Intelligence), and NKFIH grants (2020-1.1.6-JOVO-2021-00010, and TKP2020-NKA-17) to OrthoSera Ltd. I.K. receives funding from EU Horizon 2020 under grant agreement no. 101046203 (BY-COVID)." + } ], + "links" : [ { + "url" : "https://github.com/fimm-covid-19-hca/mini-IFA_paper", + "attributes" : [ { + "name" : "Description", + "value" : "Supplementary code of machine-learning model training, prediction and evaluation pipeline" + } ] + }, { + "url" : "https://dx.doi.org/10.5281/zenodo.6352550", + "attributes" : [ { + "name" : "Description", + "value" : "Extracted single-cell features from microscopic images to train and test models" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Lassi Paavolainen" + }, { + "name" : "E-mail", + "value" : "lassi.paavolainen@helsinki.fi" + }, { + "name" : "Role", + "value" : "submitter, data acquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0000-0003-1508-2718" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Antti Hassinen" + }, { + "name" : "E-mail", + "value" : "antti.hassinen@helsinki.fi" + }, { + "name" : "Role", + "value" : "data aquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0000-0001-9491-2868" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Minttu Polso" + }, { + "name" : "E-mail", + "value" : "minttu.polso@helsinki.fi" + }, { + "name" : "Role", + "value" : "data aquisition, data analysis" + }, { + "name" : "ORCID", + "value" : "0009-0007-2029-9707" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Vilja Pietiäinen" + }, { + "name" : "E-mail", + "value" : "vilja.pietiainen@helsinki.fi" + }, { + "name" : "Role", + "value" : "first author, corresponding author" + }, { + "name" : "ORCID", + "value" : "0000-0003-3125-2406" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Isabel Kemmer" + }, { + "name" : "E-mail", + "value" : "isabel.kemmer@eurobioimaging.eu" + }, { + "name" : "Role", + "value" : "data steward" + }, { + "name" : "ORCID", + "value" : "0000-0002-8799-4671" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organization", + "attributes" : [ { + "name" : "Name", + "value" : "Euro-BioImaging ERIC" + }, { + "name" : "Address", + "value" : "Euro-BioImaging Bio-Hub, EMBL, Meyerhofstrasse 1, 69117 Heidelberg." + } ] + }, { + "accno" : "o2", + "type" : "organization", + "attributes" : [ { + "name" : "Name", + "value" : "Institute for Molecular Medicine Finland" + }, { + "name" : "Address", + "value" : "P.O.Box 20, FI-00014 University of Helsinki, Finland" + } ] + }, { + "type" : "Publication", + "attributes" : [ { + "name" : "Title", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "Year", + "value" : "2023" + }, { + "name" : "Authors", + "value" : "Vilja Pietiäinen, Minttu Polso, Ede Migh, Christian Guckelsberger, Maria Harmati, Akos Diosdi, Laura Turunen, Antti Hassinen, Swapnil Potdar, Annika Koponen, Edina Gyukity Sebestyen, Ferenc Kovacs, Andras Kriston, Reka Hollandi, Katalin Burian, Gabriella Terhes, Adam Visnyovszki, Eszter Fodor, Zsombor Lacza, Anu Kantele, Pekka Kolehmainen, Laura Kakkola, Tomas Strandin, Lev Levanov, Olli Kallioniemi, Lajos Kemeny, Ilkka Julkunen, Olli Vapalahti, Krisztina Buzas, Lassi Paavolainen, Peter Horvath, Jussi Hepojoki" + }, { + "name" : "DOI", + "value" : "https://doi.org/10.1016/j.crmeth.2023.100565" + }, { + "name" : "PMC ID", + "value" : "37671026" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Biosample" + }, { + "name" : "Biological entity", + "value" : "Vero E6 cells" + }, { + "name" : "Description", + "value" : "African green monkey kidney cell line, ATCC; mycoplasma tested" + }, { + "name" : "Intrinsic variable", + "value" : "cells transfected to express SARS-CoV-2 antigens: N [nucleo proteins], M [Membrane], R [Receptor-binding domain], and S [Spike]" + }, { + "name" : "Extrinsic variable", + "value" : "addition of serum samples obtained from positive (COVID-19+) and negative (COVID-19–) patients" + }, { + "name" : "Experimental variable", + "value" : "imaging of four different fluorescent channels to detect three immunoglobulins (IgG IgA IgM; binding to transiently transfected virus antigens) with fluorescently labelled secondary antibodies and cell nuclei" + }], + "subsections" : [ { + "accno" : "Organism-1", + "type" : "Organism", + "attributes" : [ { + "name" : "Scientific name", + "value" : "Chlorocebus aethiops" + }, { + "name" : "Common name", + "value" : "African green monkey" + }, { + "name" : "NCBI taxon ID", + "value" : "NCBI:txid9534" + } ] + } ] + }, { + "accno" : "Specimen-1", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Specimen" + }, { + "name" : "Sample Preparation Protocol", + "value" : "The transiently transfected Vero E6 cells on 384-well plates were fixed with 4 % PFA and washed before storing at +4° C. For control purposes, Hoechst 33342 (Invitrogen H1399) was added to serum samples before aquiring them to plate (final concentration of Hoechst on plates was 1:5000). Protocol: The transfected and fixed Vero E6 cells were permeabilized and blocked with 3 % BSA-TBSTx (0.25 %) and incubated at RT for 15 min before washing. Serum samples (including Hoechst) were dispensed to wells in 1/100 and 1/50 dilutions and incubated at RT for 1.5 h followed by washing with TBS. A secondary antibody mixture with Alexa Fluor 647 Anti-Human Serum IgA (1/1000 dilution, ), anti-Human IgM Alexa Fluor 488 (1/1000 dilution, Invitrogen A-21215) and anti-Human IgG DyLight 550 Secondary Antibody (1/500 dilution, Invitrogen SA5-10135) was used to detect the SARS-CoV-2 antibodies from plates." + }, { + "name" : "Growth Protocol", + "value" : "Vero E6 Cells were transfected with plasmid DNA (S-pCAGG, RBD-pCAGG, N-pCAGG or M-pEBB) and incubated at RT for 15-30 min. The cells were then seeded to a 384 plate and incubated for 48 hours at 37° C with 5 % CO2. The plasmids: S-pCAGGS, SARS-CoV-2 spike protein/plasmid (Amanat et al. 2020. A serological assay to detect SARS-CoV-2 seroconversion in humans); RBD-pCAGGS, SARS-CoV-2 receptor-binding domain/plasmid (Amanat et al. 2020); NP-pCAGGS, SARS-CoV-2 nucleoprotein/plasmid (Rusanen et al. 2021. A 10-Minute “Mix and Read” Antibody Assay for SARS-CoV-2), M-pEBB, SARS-CoV-2 membrane, protein/plasmid, hCoV-19/Finland/1/2020, (Genbank accession MT020781) with pEBB-N-HA mammalian expression plasmid." + } ] + }, { + "accno" : "Image Acquisition-1", + "type" : "Image Acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Acquisition" + }, { + "name" : "Imaging Instrument", + "value" : "PerkinElmer Opera Phenix high-throughput spinning disc confocal microscope using Harmony 4.9 software, 20x water-immersion objective (NA 1.0, working distance 1.7 mm, depth of focus 1.8 μm, effective xy resolution 0.66 μm) and two Andor Zyla sCMOS cameras" + }, { + "name" : "Image Acquisition Parameters", + "value" : "Two-peak autofocus in confocal mode with binning 1, Four excitation lasers (ex) with 100% laser power and emission band-pass filters (em) were used: Channel 1 (Hoechst): ex 405 nm, em 435-480 nm, 100 ms exposure time Channel 2 (IgM): ex 488 nm, em 500-550 nm, 100 ms exposure time Channel 3 (IgG): ex 561 nm, em 570-630 nm, 200 ms exposure time Channel 4 (IgA): ex 640 nm, em 650-760 nm, 200 ms exposure time A grid of nine adjacent fields selected from the center of the well, 5 % overlap between the images. Area of the selection is 3,83 mm^2 or 36 % of the total well area. Z-stack of 2 fields selected, first plane at -4.0 µm, 3 µm distance between planes" + }, { + "name" : "Image data: file format: TIFF, Bit depth: 16 bit, Image dimensions: 2160x2160 px, pixel size: 0.298988040478381 µm" + } ], + "subsections" : [ { + "accno" : "Imaging Method-1", + "type" : "Imaging Method", + "attributes" : [ { + "name" : "Ontology Value", + "value" : "spinning disk confocal microscopy" + }, { + "name" : "Ontology Name", + "value" : "Biological Imaging Methods Ontology (FBbi)" + }, { + "name" : "Ontology Term ID", + "value" : "http://purl.obolibrary.org/obo/FBbi_00000253" + } ] + } ] + }, { + "accno" : "Image-Analysis-1", + "type" : "Image Analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Analysis" + }, { + "name" : "Image Analysis Overview", + "value" : "Images were processed using BIAS software (Mund et al., 2021; Piccinini et al., 2017). Pipeline created for the analysis consisted of pre-processing of the images, and nuclear/cell segmentation. In the pre-processing, a maximum intensity projection was created from each stack of images in different focus depths. Non-uniform illumination was corrected separately for each channel using the CIDRE method (Smith et al., 2015)." + } ] + }, { + "accno" : "Annotations-1", + "type" : "Annotations", + "attributes" : [ { + "name" : "Title", + "value" : "Segmentation masks" + }, { + "name" : "Annotation Overview", + "value" : "Segmentations underlying the machine learning-guided image analysis. Machine learning is employed for (i) nuclei and cell segmentation, and (ii) phenotypic cell classification." + }, { + "name" : "Annotation Type", + "value" : "segmentation_mask" + }, { + "name" : "Annotation Method", + "value" : "Pre-trained deep learning segmentation method (Hollandi et al., 2020) was applied to segment nuclei in images. From these nuclei regions, two additional segmented regions were defined: 1) the cells were defined by dilating nuclei regions with maximum 7 μm radius so that adjacent cells did not overlap, and 2) cytoplasm regions were defined by subtracting nuclei segmentation from the cell segmentation." + }, { + "name" : "File List", + "value" : "file_list_annotations.json" + } ], + "subsections" : [ { + "type" : "Version", + "attributes" : [ { + "name" : "Annotation version", + "value" : "1.0" + }, { + "name" : "Version timestamp", + "value" : "2024-03-06 16:30:00" + } ] + } ] + }, { + "accno" : "Study Component-1", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2" + }, { + "name" : "Description", + "value" : "Images underlying the machine learning-guided image analysis. Vero E6 cells, transfected to express SARS-CoV-2 antigens (N, M, R, and S), are fixed in 384-well plates for incubation with serum samples. The immunoglobulins (IgG, IgA, and IgM) are detected simultaneously with fluorophore-labelled secondary antibodies using automated high-content fluorescence microscopy. Machine learning is employed for (i) nuclei and cell segmentation, and (ii) phenotypic cell classification." + }, { + "name" : "File List", + "value" : "file_list_images.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Specimen" + }, { + "name" : "Image acquisition", + "value" : "Acquisition" + }, { + "name" : "Image Analysis", + "value" : "Analysis" + } ] + } ] + } ] + }, + "type" : "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1136/S-BIAD1136_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1136/S-BIAD1136_original.json new file mode 100644 index 00000000..5f574bab --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1136/S-BIAD1136_original.json @@ -0,0 +1,221 @@ +{ + "accno" : "S-BIAD1136", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1136" + }, { + "name" : "ReleaseDate", + "value" : "2024-09-22" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "3D light sheet microscopy imaging of cleared human mammary gland terminal ductal lobular unit" + }, { + "name" : "Description", + "value" : "3D image dataset of cleared human mammary gland terminal ductal lobular unit imaged using light sheet microscopy. Cytokeratin 8 was stained to visualize luminal mammary epithelial cells." + }, { + "name" : "Keywords", + "value" : "light sheet microscopy" + }, { + "name" : "Keywords", + "value" : "human mammary gland" + }, { + "name" : "Keywords", + "value" : "terminal ductal lobular unit" + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Oona Paavolainen" + }, { + "name" : "E-mail", + "value" : "oona.paavolainen@ut" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Markus Peurla" + }, { + "name" : "E-mail", + "value" : "markus.peurla@utu.fi" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Emilia Peuhu" + }, { + "name" : "E-mail", + "value" : "emilia.peuhu@utu.fi" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Larissa Mourao" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Colinda LGJ Scheele" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Pia Boström" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Pauliina Hartiala" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "University of Turku" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "KU Leuven" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Turku University Hospital" + } ] + }, { + "type" : "Publication", + "attributes" : [ { + "name" : "DOI", + "value" : "10.1101/2023.03.12.532249" + }, { + "name" : "Year", + "value" : "2023" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Human mammary gland" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "Human mammary gland tissue" + }, { + "name" : "Biological entity", + "value" : "Human mammary gland terminal ductal lobular unit" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Cleared human mammary gland tissue" + }, { + "name" : "Sample preparation protocol", + "value" : "All incubation steps were performed on a roller mixer. Tissue pieces were fixed with 4% PFA in SDS permeabilization buffer (10% SDS in H2O, pH 7.4) o/n in +4°C. The next day, pieces were washed 3x5 min with PBS and moved to SDS permeabilization buffer for 1-2 days in +37°C. Fixed tissue pieces were then transferred to 25-50ml of CUBIC 1 (1.6 M urea, 5% Quadrol [Sigma, 122262], 15% Triton X-100, 25 mM NaCL [Fisher Scientific, S/3160/60] in ddH2O) and incubated in +37°C for a minimum of 3 weeks, changing the buffer every 2-3 days. Next, the pieces were labelled with DAPI (1:1000-1:3000, [Life Technologies, D1306]) in PBS o/n at room temperature. The areas with TDLU structures were visualized with fluorescence microscopy, and chosen areas cut into pieces of approximately 2-5mm in diameter. Tissues were then permeabilized again using SDS permeabilization buffer for 2 days in +37°C, changing the buffer between the days. The tissues were then washed 3x1h in PBT at room temperature (PBS + 0.2% Triton X-100, pH 7.4) and blocked with iFLASH blocking buffer (10% FBS [Sigma, 122262], 5% DMSO [Chem Cruz, 358801], 0.1% NaN3, 1% BSA in PBT) for 1h at room temperature, and incubated in primary antibodies diluted in iFLASH blocking buffer for 3 days (anti-keratin 8 primary antibody 1:100 [Hybridoma Bank, TROMA-1). Tissues were washed 3x1h with PBT at room temperature, and pieces incubated in secondary antibodies (anti-rat secondary antibody (H+L) 1:400 [Thermo Scientific, Alexa Fluor 488]) in +37°C. Finally, the pieces were washed 3x1h with PBT at room temperature, and transferred to 25-50ml of CUBIC2 (1.2 M sucrose [Millipore, 107651], 3.6M urea, 9% triethanolamine [Sigma, 90279], 0.1% Triton X-100 in ddH2O) for a minimum of 2 days in +37°C, or until mounting and imaging. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Light sheet imaging" + }, { + "name" : "Imaging instrument", + "value" : "MSquared Aurora Airy Beam Light Sheet microscope using Aurora acquisition software version 0.5. The objective used was a Special Optics dipping objective which has dipping medium refractive index (RI) dependent magnification 15.3×-17.9× (NA 0.37-0.43) in immersion medium refractive index range 1.33-1.56." + }, { + "name" : "Image acquisition parameters", + "value" : "Alexa488 secondary antibody was imaged with a 488 nm laser and emission filter at 500-540 nm. 3D images were acquired by taking z-stacks with 400 nm spacing with a pixel size of 387 nm. Images were deconvoluted using Aurora Deconvolution software version 0.5 using point spread functions of fluorescent beads obtained from agarose embedded samples. Images were downsampled by ImageJ Bin function using x, y, z shrink factors 2 and bin method Average. 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Cytokeratin 8 was stained to visualize luminal mammary epithelial cells." + }, { + "name" : "Keywords", + "value" : "light sheet microscopy" + }, { + "name" : "Keywords", + "value" : "human mammary gland" + }, { + "name" : "Keywords", + "value" : "terminal ductal lobular unit" + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Oona Paavolainen" + }, { + "name" : "E-mail", + "value" : "oona.k.paavolainen@utu.fi" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Markus Peurla" + }, { + "name" : "E-mail", + "value" : "markus.peurla@utu.fi" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Emilia Peuhu" + }, { + "name" : "E-mail", + "value" : "emilia.peuhu@utu.fi" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Larissa Mourao" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Colinda LGJ Scheele" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Pia Boström" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Pauliina Hartiala" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "University of Turku" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "KU Leuven" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Turku University Hospital" + } ] + }, { + "type" : "Publication", + "attributes" : [ { + "name" : "DOI", + "value" : "10.1101/2023.03.12.532249" + }, { + "name" : "Year", + "value" : "2023" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Human mammary gland" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "Human mammary gland tissue" + }, { + "name" : "Biological entity", + "value" : "Human mammary gland terminal ductal lobular unit" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Cleared human mammary gland tissue" + }, { + "name" : "Sample preparation protocol", + "value" : "All incubation steps were performed on a roller mixer. Tissue pieces were fixed with 4% PFA in SDS permeabilization buffer (10% SDS in H2O, pH 7.4) o/n in +4°C. The next day, pieces were washed 3x5 min with PBS and moved to SDS permeabilization buffer for 1-2 days in +37°C. Fixed tissue pieces were then transferred to 25-50ml of CUBIC 1 (1.6 M urea, 5% Quadrol [Sigma, 122262], 15% Triton X-100, 25 mM NaCL [Fisher Scientific, S/3160/60] in ddH2O) and incubated in +37°C for a minimum of 3 weeks, changing the buffer every 2-3 days. Next, the pieces were labelled with DAPI (1:1000-1:3000, [Life Technologies, D1306]) in PBS o/n at room temperature. The areas with TDLU structures were visualized with fluorescence microscopy, and chosen areas cut into pieces of approximately 2-5mm in diameter. Tissues were then permeabilized again using SDS permeabilization buffer for 2 days in +37°C, changing the buffer between the days. The tissues were then washed 3x1h in PBT at room temperature (PBS + 0.2% Triton X-100, pH 7.4) and blocked with iFLASH blocking buffer (10% FBS [Sigma, 122262], 5% DMSO [Chem Cruz, 358801], 0.1% NaN3, 1% BSA in PBT) for 1h at room temperature, and incubated in primary antibodies diluted in iFLASH blocking buffer for 3 days (anti-keratin 8 primary antibody 1:100 [Hybridoma Bank, TROMA-1). Tissues were washed 3x1h with PBT at room temperature, and pieces incubated in secondary antibodies (anti-rat secondary antibody (H+L) 1:400 [Thermo Scientific, Alexa Fluor 488]) in +37°C. Finally, the pieces were washed 3x1h with PBT at room temperature, and transferred to 25-50ml of CUBIC2 (1.2 M sucrose [Millipore, 107651], 3.6M urea, 9% triethanolamine [Sigma, 90279], 0.1% Triton X-100 in ddH2O) for a minimum of 2 days in +37°C, or until mounting and imaging. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Light sheet imaging" + }, { + "name" : "Imaging instrument", + "value" : "MSquared Aurora Airy Beam Light Sheet microscope using Aurora acquisition software version 0.5. The objective used was a Special Optics dipping objective which has dipping medium refractive index (RI) dependent magnification 15.3×-17.9× (NA 0.37-0.43) in immersion medium refractive index range 1.33-1.56." + }, { + "name" : "Image acquisition parameters", + "value" : "Alexa488 secondary antibody was imaged with a 488 nm laser and emission filter at 500-540 nm. 3D images were acquired by taking z-stacks with 400 nm spacing with a pixel size of 387 nm. Images were deconvoluted using Aurora Deconvolution software version 0.5 using point spread functions of fluorescent beads obtained from agarose embedded samples. Images were downsampled by ImageJ Bin function using x, y, z shrink factors 2 and bin method Average. " + }, { + "name" : "Imaging method", + "value" : "light sheet microscopy" + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Light sheet microscopy imaging of cleared human mammary gland" + }, { + "name" : "Description", + "value" : "3D light sheet microscopy imaging of cleared human mammary gland terminal ductal lobular unit" + }, { + "name" : "File List", + "value" : "filelist.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Human mammary gland" + }, { + "name" : "Specimen", + "value" : "Cleared human mammary gland tissue" + }, { + "name" : "Image acquisition", + "value" : "Light sheet imaging" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_original.json new file mode 100644 index 00000000..aeaacbc3 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_original.json @@ -0,0 +1,336 @@ +{ + "accno" : "S-BIAD1223", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1223" + }, { + "name" : "ReleaseDate", + "value" : "2024-06-13" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Fiji 3Dprojections of Z-stacks of confocal fluorescence microscopy to assess the cellular localisation of EGFP-ABRAXAS1 wild-type/mutant and EGFP-CDC45 wild-type/mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of Z-stacks recorded on a LSM700 confocal microscopy (Zeiss) represented in Figure 5H and I and Appendix Figure 8-11, Kliche et al., (2024). DAPI was visualised with the 405 nm laser and GFP with the 488 nm laser." + }, { + "name" : "Keywords", + "value" : "Nuclear localisation" + }, { + "name" : "Keywords", + "value" : "CDC45" + }, { + "name" : "Keywords", + "value" : "ABRAXAS1" + }, { + "name" : "Keywords", + "value" : "Disease mutations" + }, { + "name" : "Acknowledgements", + "value" : "We thank Prof. Robert Winqvist for the FLAG-ABRAXAS1 wild-type and mutant constructs." + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "This work was supported by the grants from the Swedish Research Council (YI: 2020-03380 a Marie Sklodowska-Curie European Training Network Grant #860517 (Ubimotif). Work at the Novo Nordisk Foundation Center for Protein Research is supported by grant NNF14CC0001 and NNF23OC0082227. " + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Johanna Kliche" + }, { + "name" : "E-mail", + "value" : "johanna.kliche@cpr.ku.dk" + }, { + "name" : "ORCID", + "value" : "0000-0003-3179-4635" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ylva Ivarsson" + }, { + "name" : "E-mail", + "value" : "ylva.ivarsson@kemi..u.se" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "University of Copenhagen" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Uppsala University" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Swedish research council" + }, { + "name" : "grant_id", + "value" : "2020-03380" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Marie Sklodowska-Curie European Training Network Grant \"UbiMotif\"" + }, { + "name" : "grant_id", + "value" : "860517 " + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Novo Nordisk Foundation" + }, { + "name" : "grant_id", + "value" : "NNF14CC0001" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Novo Nordisk Foundation" + }, { + "name" : "grant_id", + "value" : "NNF23OC0082227" + } ] + }, { + "accno" : "Biosample-7", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "ABRAXAS1 wild-type" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-ABRAXAS1 wild-type, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-6", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-ABRAXAS1 mutant, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-7", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "CDC45 wild-type" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-CDC45 wild-type, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-8", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "CDC45 mutant" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-CDC45 mutant, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Sample preparation protocol", + "value" : "From bioRxiv 2023.09.18.558189: HEK293 cells were transfected with 0.25 µg of respective plasmid (EGFP-ABRAXAS1 and R361Q mutant; EGFP-CDC45 wild-type and R157C mutant) while seeding (ca. 25% confluency) in a 8 chamber slide system (Nunc Lab-Tek II CC2). Medium was changed after 24 h and protein expression allowed for 48 h in total after transfection. After that, cells were fixed and mounted with cell nuclei stained with NucBlue Live ReadyProbes (Invitrogen). Z-stacks of the cells were recorded on a LSM700 confocal microscope (Zeiss) and images analysed with Fiji. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Z-stacks obtained by confocal microscopy" + }, { + "name" : "Imaging instrument", + "value" : "LSM700 confocal microscope (Zeiss) " + }, { + "name" : "Image acquisition parameters", + "value" : "Z-stacks were recorded using the 63x/1.4 oil objective, 405 nm and 488 nm laser" + }, { + "name" : "Imaging method", + "value" : "confocal microscopy" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Fiji 3Dprojections of confocal microscopy images" + }, { + "name" : "Image analysis overview", + "value" : "Z-stacks were analysed in Fiji as 3D projections. No quantification of the images was performed." + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "EGFP-ABRAXAS1 wild-type" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-ABRAXAS1 wild-type, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "ABRAXAS1_wt.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "ABRAXAS1 wild-type" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-9", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-ABRAXAS1 mutant, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "ABRAXAS1_mut.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-10", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "CDC45 wild-type" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-CDC45 wild-type, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "CDC45_wt.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "CDC45 wild-type" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-11", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "CDC45 mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-CDC45 mutant, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "CDC45_mut.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "CDC45 mutant" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_override.json new file mode 100644 index 00000000..bc9e9ec1 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1223/S-BIAD1223_override.json @@ -0,0 +1,336 @@ +{ + "accno" : "S-BIAD1223", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1223" + }, { + "name" : "ReleaseDate", + "value" : "2024-06-13" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Fiji 3Dprojections of Z-stacks of confocal fluorescence microscopy to assess the cellular localisation of EGFP-ABRAXAS1 wild-type/mutant and EGFP-CDC45 wild-type/mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of Z-stacks recorded on a LSM700 confocal microscopy (Zeiss) represented in Figure 5H and I and Appendix Figure 8-11, Kliche et al., (2024). DAPI was visualised with the 405 nm laser and GFP with the 488 nm laser." + }, { + "name" : "Keywords", + "value" : "Nuclear localisation" + }, { + "name" : "Keywords", + "value" : "CDC45" + }, { + "name" : "Keywords", + "value" : "ABRAXAS1" + }, { + "name" : "Keywords", + "value" : "Disease mutations" + }, { + "name" : "Acknowledgements", + "value" : "We thank Prof. Robert Winqvist for the FLAG-ABRAXAS1 wild-type and mutant constructs." + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "This work was supported by the grants from the Swedish Research Council (YI: 2020-03380 a Marie Sklodowska-Curie European Training Network Grant #860517 (Ubimotif). Work at the Novo Nordisk Foundation Center for Protein Research is supported by grant NNF14CC0001 and NNF23OC0082227. " + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Johanna Kliche" + }, { + "name" : "E-mail", + "value" : "johanna.kliche@cpr.ku.dk" + }, { + "name" : "ORCID", + "value" : "0000-0003-3179-4635" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ylva Ivarsson" + }, { + "name" : "E-mail", + "value" : "ylva.ivarsson@kemi.uu.se" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "University of Copenhagen" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Uppsala University" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Swedish research council" + }, { + "name" : "grant_id", + "value" : "2020-03380" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Marie Sklodowska-Curie European Training Network Grant \"UbiMotif\"" + }, { + "name" : "grant_id", + "value" : "860517 " + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Novo Nordisk Foundation" + }, { + "name" : "grant_id", + "value" : "NNF14CC0001" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "Novo Nordisk Foundation" + }, { + "name" : "grant_id", + "value" : "NNF23OC0082227" + } ] + }, { + "accno" : "Biosample-7", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "ABRAXAS1 wild-type" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-ABRAXAS1 wild-type, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-6", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-ABRAXAS1 mutant, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-7", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "CDC45 wild-type" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-CDC45 wild-type, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Biosample-8", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "CDC45 mutant" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "HEK293 cells transfected with EGFP-CDC45 mutant, fixed and stained for DAPI" + }, { + "name" : "Biological entity", + "value" : "Human Embryonic Kidney 293 Cells" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Sample preparation protocol", + "value" : "From bioRxiv 2023.09.18.558189: HEK293 cells were transfected with 0.25 µg of respective plasmid (EGFP-ABRAXAS1 and R361Q mutant; EGFP-CDC45 wild-type and R157C mutant) while seeding (ca. 25% confluency) in a 8 chamber slide system (Nunc Lab-Tek II CC2). Medium was changed after 24 h and protein expression allowed for 48 h in total after transfection. After that, cells were fixed and mounted with cell nuclei stained with NucBlue Live ReadyProbes (Invitrogen). Z-stacks of the cells were recorded on a LSM700 confocal microscope (Zeiss) and images analysed with Fiji. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Z-stacks obtained by confocal microscopy" + }, { + "name" : "Imaging instrument", + "value" : "LSM700 confocal microscope (Zeiss) " + }, { + "name" : "Image acquisition parameters", + "value" : "Z-stacks were recorded using the 63x/1.4 oil objective, 405 nm and 488 nm laser" + }, { + "name" : "Imaging method", + "value" : "confocal microscopy" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Fiji 3Dprojections of confocal microscopy images" + }, { + "name" : "Image analysis overview", + "value" : "Z-stacks were analysed in Fiji as 3D projections. No quantification of the images was performed." + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "EGFP-ABRAXAS1 wild-type" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-ABRAXAS1 wild-type, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "ABRAXAS1_wt.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "ABRAXAS1 wild-type" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-9", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-ABRAXAS1 mutant, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "ABRAXAS1_mut.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "ABRAXAS1 mutant" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-10", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "CDC45 wild-type" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-CDC45 wild-type, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "CDC45_wt.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "CDC45 wild-type" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + }, { + "accno" : "Study Component-11", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "CDC45 mutant" + }, { + "name" : "Description", + "value" : "Fiji 3Dprojections of confocal images of HEK293 cells transfected with EGFP-CDC45 mutant, fixed and stained for DAPI" + }, { + "name" : "File List", + "value" : "CDC45_mut.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "CDC45 mutant" + }, { + "name" : "Specimen", + "value" : "Fixed HEK293 cells transfected with EGFP-constructs (ABRAXAS1 and R361Q mutant; CDC45 wild-type and R157C mutant)" + }, { + "name" : "Image acquisition", + "value" : "Z-stacks obtained by confocal microscopy" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_original.json new file mode 100644 index 00000000..ec9afe64 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_original.json @@ -0,0 +1,123 @@ +{ + "accno" : "S-BIAD1261", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1261" + }, { + "name" : "ReleaseDate", + "value" : "2024-07-05" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Region-Specific Protective Effects of Monomethyl Fumarate in Cerebellar and Hippocampal Organotypic Slice Cultures Following Oxygen-Glucose Deprivation" + }, { + "name" : "Description", + "value" : "To date, apart from moderate hypothermia, there are almost no adequate interventions available for neuroprotection in cases of brain damage due to cardiac arrest. Affected persons often have severe limitations in their quality of life. The aim of this study was to investigate protective properties of the active compound of dimethyl fumarate, monomethyl fumarate (MMF), on distinct regions of the central nervous system after ischemic events. Dimethyl fumarate is an already established drug in neurology with known anti-inflammatory and antioxidant properties. In this study, we chose organotypic slice cultures of rat cerebellum and hippocampus as an ex vivo model. To simulate cardiac arrest and return of spontaneous circulation we performed oxygen-glucose-deprivation (OGD) followed by treatments with different concentrations of MMF (1-30 µM in cerebellum and 5-30 µM in hippocampus). Immunofluorescence staining with propidium iodide (PI) and 4′,6-diamidine-2-phenylindole (DAPI) was performed to analyze PI/DAPI ratio after imaging with a spinning disc confocal microscope. In the statistical analysis, the relative cell death of the different groups was compared. In both, the cerebellum and hippocampus, the MMF-treated group showed a significantly lower PI/DAPI ratio compared to the non-treated group after OGD. Thus, we showed for the first time that both cerebellar and hippocampal slice cultures treated with MMF after OGD are significantly less affected by cell death." + }, { + "name" : "Keywords", + "value" : "brain damage; cardiac arrest; cell death; hypoxic chamber; ischemia; organotypic slice cultures; post-treatment; resuscitation" + }, { + "name" : "Acknowledgements", + "value" : "The authors gratefully acknowledge A. Lodwig, C. Grzelak, A. Harbecke, and F. Opdenhoevel, for technical assistance, as well as A. Lenz for secretarial work." + }, { + "name" : "License", + "value" : "CC0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/publicdomain/zero/1.0/legalcode" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "E-mail", + "value" : "cytologie@rub.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Ruhr University Bochum" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Biosample" + }, { + "name" : "Organism", + "value" : "Wistar rat" + }, { + "name" : "Biological entity", + "value" : "p9 Wistar rat hippocampal and cerebellar slice cultures" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Speciem" + }, { + "name" : "Sample preparation protocol", + "value" : "Six neonatal Wistar rats were decapitated by guillotine on postnatal day 9 (p9) without prior anesthesia. The Cerebellum and hippocampus were carefully dissected under strictly sterile conditions and stored in sterile ice-cooled Hank’s solution (#H8264-500ML; Sigma-Aldrich, Darmstadt, Germany). Using a McIlwain tissue chopper, the cerebellum was sliced along its sagittal axis into 275 µm slices, and the hippocampus was sliced along its long axis into 350 µm slices. The slices were subsequently transferred to cell culture inserts with semi-permeable membranes made of PTFE film (Millicell Cell Culture Inserts, 0.4 µm pore-size, #PICM0RG50, Merck, Darmstadt, Germany). The inserts are placed in six-well plates containing one ml of culture medium and are pre-incubated at 37 °C and 5 % CO2 for at least two h. The culture medium consists of Dulbeccos Modified Eagle Medium (DMEM; #A14430-01, Thermo Fisher Scientific, Waltham, MA, USA) containing 25 % heat-inactivated horse serum (#16050-122; Thermo Fisher Scientific), 25 % Hank's balanced salts solution (NaCl 8 g/L, KCl 0.4 g/L, Na2HPO4 0.048 g/L, KH2PO4 0.06 g/L, CaCl2 0.185 g/L, MgSO4 0.098 g/L, NaHCO3 0.35 g/L, glucose 1 g/L), 6.5 % glucose, 2.5 mg/l NGF (N-0513; Sigma-Aldrich), 1 % GlutaMax (#35050-061; Thermo Fisher Scientific), 1 % PenStrep (10,000 U penicillin, 10 mg streptomycin, #P4333, Sigma-Aldrich), and 10 mg/l phenol red (#P0290; Sigma-Aldrich). The organotypic slice cultures were maintained at 37 °C and 5 % CO2 for seven days. Every other day, half of the cell culture medium was replaced with fresh cell culture medium" + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Image acquisition" + }, { + "name" : "Imaging instrument", + "value" : "VisiScope Confocal-Cell Explorer, Visitron Systems GmbH, Puchheim, Germany\nNikon PlanFluor 20×, NA 0.5; Nikon Instruments Europe BV, Amsterdam, Netherlands" + }, { + "name" : "Image acquisition parameters", + "value" : "Imaging was performed on a spinning disk confocal microscope using a 20x objective. The exposure time was set to 900 ms. Multiple z-stacks were first acquired as a matrix, then stitched and stacked into a single image. A 405 nm laser was used for DAPI excitation and a 561 nm laser for PI excitation." + }, { + "name" : "Imaging method", + "value" : "spinning disk confocal microscopy" + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Stitched and stacked fluorescence confocal images" + }, { + "name" : "Description", + "value" : "Stitched and stacked fluorescence confocal images" + }, { + "name" : "File List", + "value" : "mmf_ogd.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Speciem" + }, { + "name" : "Image acquisition", + "value" : "Image acquisition" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_override.json new file mode 100644 index 00000000..1bb8cac1 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1261/S-BIAD1261_override.json @@ -0,0 +1,126 @@ +{ + "accno" : "S-BIAD1261", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1261" + }, { + "name" : "ReleaseDate", + "value" : "2024-07-05" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Region-Specific Protective Effects of Monomethyl Fumarate in Cerebellar and Hippocampal Organotypic Slice Cultures Following Oxygen-Glucose Deprivation" + }, { + "name" : "Description", + "value" : "To date, apart from moderate hypothermia, there are almost no adequate interventions available for neuroprotection in cases of brain damage due to cardiac arrest. Affected persons often have severe limitations in their quality of life. The aim of this study was to investigate protective properties of the active compound of dimethyl fumarate, monomethyl fumarate (MMF), on distinct regions of the central nervous system after ischemic events. Dimethyl fumarate is an already established drug in neurology with known anti-inflammatory and antioxidant properties. In this study, we chose organotypic slice cultures of rat cerebellum and hippocampus as an ex vivo model. To simulate cardiac arrest and return of spontaneous circulation we performed oxygen-glucose-deprivation (OGD) followed by treatments with different concentrations of MMF (1-30 µM in cerebellum and 5-30 µM in hippocampus). Immunofluorescence staining with propidium iodide (PI) and 4′,6-diamidine-2-phenylindole (DAPI) was performed to analyze PI/DAPI ratio after imaging with a spinning disc confocal microscope. 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The Cerebellum and hippocampus were carefully dissected under strictly sterile conditions and stored in sterile ice-cooled Hank’s solution (#H8264-500ML; Sigma-Aldrich, Darmstadt, Germany). Using a McIlwain tissue chopper, the cerebellum was sliced along its sagittal axis into 275 µm slices, and the hippocampus was sliced along its long axis into 350 µm slices. The slices were subsequently transferred to cell culture inserts with semi-permeable membranes made of PTFE film (Millicell Cell Culture Inserts, 0.4 µm pore-size, #PICM0RG50, Merck, Darmstadt, Germany). The inserts are placed in six-well plates containing one ml of culture medium and are pre-incubated at 37 °C and 5 % CO2 for at least two h. The culture medium consists of Dulbeccos Modified Eagle Medium (DMEM; #A14430-01, Thermo Fisher Scientific, Waltham, MA, USA) containing 25 % heat-inactivated horse serum (#16050-122; Thermo Fisher Scientific), 25 % Hank's balanced salts solution (NaCl 8 g/L, KCl 0.4 g/L, Na2HPO4 0.048 g/L, KH2PO4 0.06 g/L, CaCl2 0.185 g/L, MgSO4 0.098 g/L, NaHCO3 0.35 g/L, glucose 1 g/L), 6.5 % glucose, 2.5 mg/l NGF (N-0513; Sigma-Aldrich), 1 % GlutaMax (#35050-061; Thermo Fisher Scientific), 1 % PenStrep (10,000 U penicillin, 10 mg streptomycin, #P4333, Sigma-Aldrich), and 10 mg/l phenol red (#P0290; Sigma-Aldrich). The organotypic slice cultures were maintained at 37 °C and 5 % CO2 for seven days. Every other day, half of the cell culture medium was replaced with fresh cell culture medium" + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Image acquisition" + }, { + "name" : "Imaging instrument", + "value" : "VisiScope Confocal-Cell Explorer, Visitron Systems GmbH, Puchheim, Germany\nNikon PlanFluor 20×, NA 0.5; Nikon Instruments Europe BV, Amsterdam, Netherlands" + }, { + "name" : "Image acquisition parameters", + "value" : "Imaging was performed on a spinning disk confocal microscope using a 20x objective. The exposure time was set to 900 ms. Multiple z-stacks were first acquired as a matrix, then stitched and stacked into a single image. A 405 nm laser was used for DAPI excitation and a 561 nm laser for PI excitation." + }, { + "name" : "Imaging method", + "value" : "spinning disk confocal microscopy" + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Stitched and stacked fluorescence confocal images" + }, { + "name" : "Description", + "value" : "Stitched and stacked fluorescence confocal images" + }, { + "name" : "File List", + "value" : "mmf_ogd.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Speciem" + }, { + "name" : "Image acquisition", + "value" : "Image acquisition" + } ] + } ] + } ] + }, + "type" : "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_original.json new file mode 100644 index 00000000..2e0285f6 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_original.json @@ -0,0 +1,280 @@ +{ + "accno" : "S-BIAD1344", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1344" + }, { + "name" : "ReleaseDate", + "value" : "2024-08-29" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Multiplex Immunofluorescent Whole Slide Images of Renal Cancer" + }, { + "name" : "Description", + "value" : "The dataset is composed of 98 whole slide images (WSIs) of renal cell carcinoma, a type of kidney cancer. 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By analyzing these images, researchers can gain deeper insights into how renal cancer evolves and spreads, potentially leading to improved prognostic tools and personalised treatment strategies for patients." + }, { + "name" : "Keywords", + "value" : "Multiplex immunofluorescence; WSI; Renal cancer; Image analysis; " + }, { + "name" : "Acknowledgements", + "value" : "We would like to acknowledge Frances Rae and NHS Lothian tissue bank for collecting tissue samples used in this study, John O’Connor for preparing the whole slide samples, and East of Scotland Research Ethics Service for granting the ethical approval." + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "This work was supported by Medical Research Scotland (MRS), NHS Lothian, NanoString Technologies, and the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690]. It was also partially supported by the KATY project which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101017453." + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "In Hwa Um" + }, { + "name" : "E-mail", + "value" : "ihu@st-andrews.ac.uk" + }, { + "name" : "Role", + "value" : "corresponding author" + }, { + "name" : "ORCID", + "value" : "0000-0001-9999-4292" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Raffaele De Philippis" + }, { + "name" : "E-mail", + "value" : "raffaeledefilippis92@gmail.comraffaeledefilippis92@gmail.com" + }, { + "name" : "Role", + "value" : "experiment performer" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Georg Wölflein" + }, { + "name" : "E-mail", + "value" : "gw66@st-andrews.ac.uk" + }, { + "name" : "Role", + "value" : "data analyst" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Grant D. 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By analyzing these images, researchers can gain deeper insights into how renal cancer evolves and spreads, potentially leading to improved prognostic tools and personalised treatment strategies for patients." + }, { + "name" : "File List", + "value" : "Multiplex immunofluorescence WSI-renal cancer.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Specimen" + }, { + "name" : "Image acquisition", + "value" : "Image acquisition" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_override.json new file mode 100644 index 00000000..47eb2476 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD1344/S-BIAD1344_override.json @@ -0,0 +1,280 @@ +{ + "accno" : "S-BIAD1344", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "DOI", + "value" : "10.6019/S-BIAD1344" + }, { + "name" : "ReleaseDate", + "value" : "2024-08-29" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Multiplex Immunofluorescent Whole Slide Images of Renal Cancer" + }, { + "name" : "Description", + "value" : "The dataset is composed of 98 whole slide images (WSIs) of renal cell carcinoma, a type of kidney cancer. 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By analyzing these images, researchers can gain deeper insights into how renal cancer evolves and spreads, potentially leading to improved prognostic tools and personalised treatment strategies for patients." + }, { + "name" : "Keywords", + "value" : "Multiplex immunofluorescence; WSI; Renal cancer; Image analysis; " + }, { + "name" : "Acknowledgements", + "value" : "We would like to acknowledge Frances Rae and NHS Lothian tissue bank for collecting tissue samples used in this study, John O’Connor for preparing the whole slide samples, and East of Scotland Research Ethics Service for granting the ethical approval." + }, { + "name" : "License", + "value" : "CC BY 4.0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/licenses/by/4.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "This work was supported by Medical Research Scotland (MRS), NHS Lothian, NanoString Technologies, and the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690]. It was also partially supported by the KATY project which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101017453." + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "In Hwa Um" + }, { + "name" : "E-mail", + "value" : "ihu@st-andrews.ac.uk" + }, { + "name" : "Role", + "value" : "corresponding author" + }, { + "name" : "ORCID", + "value" : "0000-0001-9999-4292" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Raffaele De Philippis" + }, { + "name" : "E-mail", + "value" : "raffaeledefilippis92@gmail.com" + }, { + "name" : "Role", + "value" : "experiment performer" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Georg Wölflein" + }, { + "name" : "E-mail", + "value" : "gw66@st-andrews.ac.uk" + }, { + "name" : "Role", + "value" : "data analyst" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Grant D. 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Panel 1 - TIM-3 (FITC channel, Exposure time-60ms), PD1 (Cy5 channel, Exposure time-50ms), PD-L1 (Cy3 channel, Exposure time-100ms), CD8 (Alexa Fluore 750 channel, Exposure time-800ms), Hoechst (Hoechst channel, Exposure time-7ms)\n2. Panel 2 - ZEB1 (FITC channel, Exposure time-50ms), SNAIL (Cy5 channel, Exposure time-50ms), OCT4a (Cy3 channel, Exposure time-50ms), CD44 (Alexa Fluore 750 channel, Exposure time-300ms), Hoechst (Hoechst channel, Exposure time-6ms)" + }, { + "name" : "Imaging method", + "value" : "fluorescence microscopy" + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Multiplex Immunofluorescent Whole Slide Images of Renal Cancer" + }, { + "name" : "Description", + "value" : "The dataset is composed of 98 whole slide images (WSIs) of renal cell carcinoma, a type of kidney cancer. These WSIs are multiplex immunofluorescent (mIF) images. They have been labeled using tow distinct panels of protein markers to allow simultaneous visualisation of multiple targets withing the same tissue sample. Panel 1 includes markers TIM-3, PD1, PD-L1, and CD8 with a DNA counterstain (Hoechst). These markers are often associated with immune response and are crucial in understanding how the immune system interacts with cancer cells. Panel 2 includes OCT4a, ZEB1, Snail, and CD44, also combined with Hoechst for DNA visualisation. These markers are particularly important because they are linked to cancer stem cells (CSC) and the epithelial-to-mesenchymal transition (EMT), processes that play significant roles in cancer progression and metastasis. This dataset will be expected to be highly valuable in the development of tools and methods aimed at characterising the differences between primary renal cancer and its metastatic forms. By analyzing these images, researchers can gain deeper insights into how renal cancer evolves and spreads, potentially leading to improved prognostic tools and personalised treatment strategies for patients." + }, { + "name" : "File List", + "value" : "Multiplex immunofluorescence WSI-renal cancer.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Biosample" + }, { + "name" : "Specimen", + "value" : "Specimen" + }, { + "name" : "Image acquisition", + "value" : "Image acquisition" + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_original.json new file mode 100644 index 00000000..9d333e83 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_original.json @@ -0,0 +1,219 @@ +{ + "accno": "S-BIAD15", + "attributes": [ + { + "name": "Title", + "value": "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, + { + "name": "ReleaseDate", + "value": "2020-02-14" + }, + { + "name": "RootPath", + "value": "S-IMDR0067" + }, + { + "name": "AttachTo", + "value": "BioImages" + } + ], + "section": { + "type": "Study", + "attributes": [ + { + "name": "Title", + "value": "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, + { + "name": "Release date", + "value": "2019-12-10" + }, + { + "name": "Description", + "value": "Production of healthy gametes in meiosis relies on the quality control and proper distribution of both nuclear and cytoplasmic contents. Meiotic differentiation naturally eliminates age-induced cellular damage by an unknown mechanism. Using time-lapse fluorescence microscopy in budding yeast, we found that nuclear senescence factors - including protein aggregates, extrachromosomal ribosomal DNA circles, and abnormal nucleolar material - are sequestered away from chromosomes during meiosis II and subsequently eliminated. A similar sequestration and elimination process occurs for the core subunits of the nuclear pore complex in both young and aged cells. Nuclear envelope remodeling drives the formation of a membranous compartment containing the sequestered material. Importantly, de novo generation of plasma membrane is required for the sequestration event, preventing the inheritance of long-lived nucleoporins and senescence factors into the newly formed gametes. Our study uncovers a new mechanism of nuclear quality control and provides insight into its function in meiotic cellular rejuvenation." + }, + { + "name": "Study type", + "value": "time-lapse imaging", + "valqual": [ + { + "name": "Ontology", + "value": "OMIT" + }, + { + "name": "TermId", + "value": "OMIT_0027490" + } + ] + }, + { + "name": "Organism", + "value": "Saccharomyces cerevisiae", + "valqual": [ + { + "name": "Ontology", + "value": "NCBITaxon" + }, + { + "name": "TermId", + "value": "4932" + } + ] + }, + { + "name": "Keyword", + "value": "meiosis" + }, + { + "name": "Keyword", + "value": "nuclear pore complex" + }, + { + "name": "Keyword", + "value": "nucleoporin" + }, + { + "name": "Keyword", + "value": "nuclear senescence factor" + }, + { + "name": "Keyword", + "value": "time-lapse fluorescence microscopy" + }, + { + "name": "License", + "value": "CC-BY 4.0" + }, + { + "name": "Number of experiments", + "value": "1" + } + ], + "subsections": [ + { + "type": "Publication", + "attributes": [ + { + "name": "Title", + "value": "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, + { + "name": "Authors", + "value": "King GA, Goodman JS, Schick JG, Chetlapalli K, Jorgens DM, McDonald KL, Ünal E" + }, + { + "name": "DOI", + "value": "https://doi.org/10.7554/eLife.47156" + }, + { + "name": "PMC ID", + "value": "PMC6711709" + } + ] + }, + { + "type": "Author", + "attributes": [ + { + "name": "Name", + "value": "Elçin Ünal" + }, + { + "name": "Email", + "value": "elcin@berkeley.edu" + }, + { + "name": "Role", + "value": "submitter" + }, + { + "name": "ORCID", + "value": "0000-0002-6768-609X" + }, + { + "name": "affiliation", + "value": "o1", + "reference": true + } + ] + }, + { + "type": "Organization", + "attributes": [ + { + "name": "Name", + "value": "622 Barker Hall, UC-Berkeley, Berkeley, CA, 94720" + } + ] + }, + { + "type": "Experiment", + "attributes": [ + { + "name": "Sample type", + "value": "cell" + }, + { + "name": "Description", + "value": "Time-lapse and fixed cell fluorescence microscopy or transmission electron microscopy images depicting budding yeast cells progressing through meiosis. The goal of this study was to characterize nuclear remodeling during budding yeast meiosis, with a focus on determining how various nuclear senescence factors are eliminated." + }, + { + "name": "Experiment size", + "value": "Average Image Dimension (XYZCT):XYZCT" + }, + { + "name": "Imaging Method", + "value": "fluorescence microscopy", + "valqual": [ + { + "name": "Ontology", + "value": "Fbbi" + }, + { + "name": "TermId", + "value": "FBbi_00000246" + } + ] + }, + { + "name": "Imaging Method", + "value": "transmission electron microscopy", + "valqual": [ + { + "name": "Ontology", + "value": "Fbbi" + }, + { + "name": "TermId", + "value": "FBbi_00000258" + } + ] + }, + { + "name": "Imaging Method", + "value": "bright-field microscopy" + }, + { + "name": "File List", + "value": "file_list.json" + } + ] + }, + { + "type": "Supplementary Data", + "attributes": [ + { + "name": "Description", + "value": "Supplementary files for archival" + }, + { + "name": "File List", + "value": "file_list_other.json" + } + ] + } + ] + }, + "type": "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_override.json new file mode 100644 index 00000000..ccfcd9b6 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD15/S-BIAD15_override.json @@ -0,0 +1,160 @@ +{ + "accno" : "S-BIAD15", + "attributes" : [ { + "name" : "Title", + "value" : "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, { + "name" : "ReleaseDate", + "value" : "2020-02-14" + }, { + "name" : "RootPath", + "value" : "S-IMDR0067" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, { + "name" : "Release date", + "value" : "2019-12-10" + }, { + "name" : "Description", + "value" : "Production of healthy gametes in meiosis relies on the quality control and proper distribution of both nuclear and cytoplasmic contents. Meiotic differentiation naturally eliminates age-induced cellular damage by an unknown mechanism. Using time-lapse fluorescence microscopy in budding yeast, we found that nuclear senescence factors - including protein aggregates, extrachromosomal ribosomal DNA circles, and abnormal nucleolar material - are sequestered away from chromosomes during meiosis II and subsequently eliminated. A similar sequestration and elimination process occurs for the core subunits of the nuclear pore complex in both young and aged cells. Nuclear envelope remodeling drives the formation of a membranous compartment containing the sequestered material. Importantly, de novo generation of plasma membrane is required for the sequestration event, preventing the inheritance of long-lived nucleoporins and senescence factors into the newly formed gametes. Our study uncovers a new mechanism of nuclear quality control and provides insight into its function in meiotic cellular rejuvenation." + }, { + "name" : "Study type", + "value" : "time-lapse imaging", + "valqual" : [ { + "name" : "Ontology", + "value" : "OMIT" + }, { + "name" : "TermId", + "value" : "OMIT_0027490" + } ] + }, { + "name" : "Organism", + "value" : "Saccharomyces cerevisiae", + "valqual" : [ { + "name" : "Ontology", + "value" : "NCBITaxon" + }, { + "name" : "TermId", + "value" : "4932" + } ] + }, { + "name" : "Keyword", + "value" : "meiosis" + }, { + "name" : "Keyword", + "value" : "nuclear pore complex" + }, { + "name" : "Keyword", + "value" : "nucleoporin" + }, { + "name" : "Keyword", + "value" : "nuclear senescence factor" + }, { + "name" : "Keyword", + "value" : "time-lapse fluorescence microscopy" + }, { + "name" : "License", + "value" : "CC BY 4.0" + }, { + "name" : "Number of experiments", + "value" : "1" + } ], + "subsections" : [ { + "type" : "Publication", + "attributes" : [ { + "name" : "Title", + "value" : "Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast" + }, { + "name" : "Authors", + "value" : "King GA, Goodman JS, Schick JG, Chetlapalli K, Jorgens DM, McDonald KL, Ünal E" + }, { + "name" : "DOI", + "value" : "https://doi.org/10.7554/eLife.47156" + }, { + "name" : "PMC ID", + "value" : "PMC6711709" + } ] + }, { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Elçin Ünal" + }, { + "name" : "Email", + "value" : "elcin@berkeley.edu" + }, { + "name" : "Role", + "value" : "submitter" + }, { + "name" : "ORCID", + "value" : "0000-0002-6768-609X" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "Organization", + "attributes" : [ { + "name" : "Name", + "value" : "622 Barker Hall, UC-Berkeley, Berkeley, CA, 94720" + } ] + }, { + "type" : "Experiment", + "attributes" : [ { + "name" : "Sample type", + "value" : "cell" + }, { + "name" : "Description", + "value" : "Time-lapse and fixed cell fluorescence microscopy or transmission electron microscopy images depicting budding yeast cells progressing through meiosis. The goal of this study was to characterize nuclear remodeling during budding yeast meiosis, with a focus on determining how various nuclear senescence factors are eliminated." + }, { + "name" : "Experiment size", + "value" : "Average Image Dimension (XYZCT):XYZCT" + }, { + "name" : "Imaging Method", + "value" : "fluorescence microscopy", + "valqual" : [ { + "name" : "Ontology", + "value" : "Fbbi" + }, { + "name" : "TermId", + "value" : "FBbi_00000246" + } ] + }, { + "name" : "Imaging Method", + "value" : "transmission electron microscopy", + "valqual" : [ { + "name" : "Ontology", + "value" : "Fbbi" + }, { + "name" : "TermId", + "value" : "FBbi_00000258" + } ] + }, { + "name" : "Imaging Method", + "value" : "bright-field microscopy" + }, { + "name" : "File List", + "value" : "file_list.json" + } ] + }, { + "type" : "Supplementary Data", + "attributes" : [ { + "name" : "Description", + "value" : "Supplementary files for archival" + }, { + "name" : "File List", + "value" : "file_list_other.json" + } ] + } ] + }, + "type" : "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_original.json new file mode 100644 index 00000000..c4f6bce2 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_original.json @@ -0,0 +1,300 @@ +{ + "accno" : "S-BIAD954", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "ReleaseDate", + "value" : "2023-11-30" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Analysis of vascular disruption in zebrafish embryos as an endpoint to predict developmental toxicity - High Content Screening Raw Data (OBI/WIK strain)" + }, { + "name" : "Description", + "value" : "A novel automated imaging-based method to detect inhibition of angiogenesis in early life stage zebrafish. Video subtraction was used to identify the location and number of functional intersegmental vessels according to the detection of moving blood cells. By exposing embryos to multiple tyrosine kinase inhibitors including SU4312, SU5416, Sorafenib, or PTK787, we confirmed that this method can detect concentration-dependent inhibition of angiogenesis. The new test method showed higher sensitivity, i.e. lower effect concentrations, relative to a fluorescent reporter gene strain (Tg(KDR:EGFP)) exposed to the same tyrosine kinase inhibitors. Indicating that functional effects due to altered tubulogenesis or blood transport can be detected before structural changes of the endothelium are visible by fluorescence imaging. Comparison of exposure windows indicated higher specificity for angiogenesis when exposure started at later embryonic stages (24 hours post fertilization). Our findings establish video imaging in wild-type strains as viable, non-invasive, high-throughput method for the detection of chemical-induced angiogenic disruption in zebrafish embryos. We established a lable-free and non-invasive method to visualize the blood vessel network in the developing wild type zebrafish embryo. We quantified ISV inhibition by comparing WT control, treated with tyrosine kinase inhibitors (SU4312, SU5416, Sorafenib and PTK787) and a fluorescent strain (TG(KDR:EGFP)). Dose-response curves and EC50 values were determined by KNIME-Workflows" + }, { + "name" : "Keywords", + "value" : "zebrafish" + }, { + "name" : "Keywords", + "value" : "angiogenesis" + }, { + "name" : "Keywords", + "value" : "tyrosine kinase inhibitors" + }, { + "name" : "Keywords", + "value" : "developmental toxicity" + }, { + "name" : "Acknowledgements", + "value" : "We acknowledge Philipe Rocce-Sera (Oxford University) and Nils Klüver (UFZ) for help with translation of FishInspector annotation metrics to ontology terms. The transgenic strain Tg(kdr:EGFP) was kindly provided by Leibniz Institute on Aging - Fritz Lipmann Institute research group of Christoph Englert" + }, { + "name" : "License", + "value" : "CC0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/publicdomain/zero/1.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "The project was funded by the German Minister of Education and Research in the funding scheme “Alternatives to Animal Tests” (Grant number 031L0232A)\nRiccardo Massei was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – 501864659" + } ], + "links" : [ { + "url" : "https://www.ufz.de/index.php?de=44460", + "attributes" : [ { + "name" : "Description", + "value" : "FishInspector - Information on the analysis software" + } ] + }, { + "url" : "https://codebase.helmholtz.cloud/ufz/tb3-cite/biotox/FishInspector", + "attributes" : [ { + "name" : "Description", + "value" : "FishInspector - GitLab Repository" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Julia Nöth" + }, { + "name" : "E-mail", + "value" : "Julia Nöth " + }, { + "name" : "Role", + "value" : "first author" + }, { + "name" : "ORCID", + "value" : "0000-0002-5695-2209" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Stefan Scholz" + }, { + "name" : "E-mail", + "value" : "stefan.scholz@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Wibke Busch" + }, { + "name" : "E-mail", + "value" : "wibke.busch@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Tamara Tal" + }, { + "name" : "E-mail", + "value" : "tamara.tal@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Chih Lai" + }, { + "name" : "E-mail", + "value" : "CLAI@stthomas.edu" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Akhil Ambekar" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Riccardo Massei" + }, { + "name" : "E-mail", + "value" : "riccardo.massei@ufz.de" + }, { + "name" : "Role", + "value" : "submitter" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Helmholtz Centre for Environmental Research" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "St. Thomas University" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Duke University" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "German Minister of Education and Research" + }, { + "name" : "grant_id", + "value" : "031L0232A" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "OBI/WIK" + }, { + "name" : "Organism", + "value" : "Danio rerio (zebrafish)" + }, { + "name" : "Description", + "value" : "Danio rerio embryos" + }, { + "name" : "Biological entity", + "value" : "Four days old zebrafish eleuthero-embryos" + }, { + "name" : "Experimental variable", + "value" : "Chemical exposure " + }, { + "name" : "Extrinsic variable", + "value" : "SU4312, SU5416, Sorafenib, PTK787, Valproic acid" + }, { + "name" : "Intrinsic variable", + "value" : "OBI-WIK strain" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Protocols" + }, { + "name" : "Sample preparation protocol", + "value" : "Prior to imaging, all embryos were anesthetized by adding 20 µl tricaine solution (6 mg/l tricaine, TRIS 26 mM, pH 7.5 ±0.1) to each well of the microplate. " + }, { + "name" : "Growth protocol", + "value" : "A wild type adult zebrafish strain (D. rerio, strain OBI/WIK, generation F3), originating from an in-house cross of zebrafish strains UFZ-OBI and WIK, was used for all experiments. TFish were fed twice daily with dry food (SDS-400, Special Diets Services, Essex England) and once daily with Artemia sp. Fish were cultured under 14h light/10h dark photoperiod in 20 L aquaria with 1-2 fish per liter density (26.5±1 °C). Water quality parameters were pH 7–8; water hardness 2–3 mmol/L, conductivity 540–560 S/cm, nitrate < 2.5 mg/L, nitrite < 0.025 mg/L, ammonia < 0.6 mg/L, oxygen saturation 87–91 %. Spawning trays were inserted 4-6 hours before the end of the light cycle. The following day, spawning was initiated by the onset of light and eggs were collected within 1 h. Exposure in all experiment was ceased at 96 hpf. Facilities for breeding and the production of embryos were licensed by Landesdirektion Leipzig (Aktenzeichen 75-9185.64).\nFertilized and normally developed embryos were selected according to Kimmel et al. (Kimmel et al. 1995) with a dissection microscope (Olympus SZx7-ILLT) at 1 hpf. Depending on experiment, exposure was started within 2-3 h post fertilization (16 to 128 cell stages) or at 24 hpf. Exposure was conducted in rectangular 96-well microplates (Clear Polystyrene, flat bottom, Uniplate, Whatman, GE Healthcare) covered by a lid with a test volume of 400 µL of exposure media. For each replicate one embryo per well and 16 wells per concentration were assessed. Experiments were performed with at least two replicates on independent days and breeding.\n" + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "VAST BioImage" + }, { + "name" : "Imaging instrument", + "value" : "VAST BioImager (Union Biometrica, Gees, Belgium) equipped with a large particle sampler (LP sampler, Union Biometrica). " + }, { + "name" : "Image acquisition parameters", + "value" : "Lateral and dorsoventral images were obtained at 10 µm resolution at 96 hpf" + }, { + "name" : "Imaging method", + "value" : "bright-field microscopy" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Automated high-throughput image analysis " + }, { + "name" : "Image analysis overview", + "value" : "Images were processed with an amended version (1.70, available via https://github.com/sscholz-UFZ/FishInspector) of the FishInspector imaging software (Teixidó et al. 2019). The FishInspector software allows to automatically annotate morphological features including body contour, eye, lower mouth tip, pericard, otoliths, notochord, swimbladder, and yolk and to calculate diverse metrics such as feature length, size, curvature indices, or angle between feature-connecting lines. In contrast to the previously published version, FishInspector 1.70 detects morphological features based on a deep learning approach using the Matlab Neural Network Toolbox and Matlab Image Processing Toolbox (Mathworks, Natick, MS). In addition, metric calculation were included into the software, and meta information such as test compound, exposure window or test concentration was associated to each image using a microplate layout file. To facilitate training of the models, two additional programs were generated in Matlab including FishTrainer 0.9 (for training of semantic segmentation models of structural features) and FishClassificator 0.9 (for training of position classes to be used in automated flipping of images). For image training, image size was adjusted to 450 x 300 pixel to reduce computing time. This resolution was sufficient to detect the selected features (data not shown). For training of the deep learning models, approximately 3000 previously annotated images (Teixidó et al. 2022) were used. The automated annotations were corrected by the user in the event that they were not adequately detecting visible structures. User-bias was avoided by a blinded assessment of images. Following model training, experimental images used for annotation had a resolution of 1024 x 190 pixels\n\nFishInspector provided a JSON file corresponding to each image file containing the coordinates of all features and the applied smoothing factor. For each image, a csv file was generated containing calculated metrics. The software automatically provides a summary table containing metrics r of individual embryos. All experimental images and corresponding csv files can be found in Supplementary Material. All subsequent analyses were conducted using the summary excel file and a KNIME workflows with embedded R-scripts, as previously described (Teixidó et al. 2022). The KNIME workflow (all workflows are available via https://git.ufz.de/automated-fish-embryotest/zebrafish-embryo-crc/zebrafish-isv) will be provided after publication) converted pixel metrics into µm or µm², combined results from different replicates, and conducted concentration response analysis to calculate effect concentrations (EC10 and EC50). " + } ], + "subsections" : [ [ { + "type" : "Software Informations", + "attributes" : [ { + "name" : "Column 1", + "value" : "https://www.ufz.de/index.php?de=44460" + } ] + }, { + "type" : "Software Informations", + "attributes" : [ { + "name" : "Column 1", + "value" : "https://codebase.helmholtz.cloud/ufz/tb3-cite/biotox/FishInspector" + } ] + } ] ] + }, { + "accno" : "Study Component-7", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "High Content Screening - WIK/OBI" + }, { + "name" : "Description", + "value" : "VAST Biomage Data analyzed with FishInspector" + }, { + "name" : "File List", + "value" : "COMP1_sample_list.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "OBI/WIK" + }, { + "name" : "Specimen", + "value" : "Protocols" + }, { + "name" : "Image acquisition", + "value" : "VAST BioImage" + }, { + "name" : "Image analysis", + "value" : "Automated high-throughput image analysis " + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_override.json new file mode 100644 index 00000000..29417193 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD954/S-BIAD954_override.json @@ -0,0 +1,300 @@ +{ + "accno" : "S-BIAD954", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "ReleaseDate", + "value" : "2023-11-30" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "Analysis of vascular disruption in zebrafish embryos as an endpoint to predict developmental toxicity - High Content Screening Raw Data (OBI/WIK strain)" + }, { + "name" : "Description", + "value" : "A novel automated imaging-based method to detect inhibition of angiogenesis in early life stage zebrafish. Video subtraction was used to identify the location and number of functional intersegmental vessels according to the detection of moving blood cells. By exposing embryos to multiple tyrosine kinase inhibitors including SU4312, SU5416, Sorafenib, or PTK787, we confirmed that this method can detect concentration-dependent inhibition of angiogenesis. The new test method showed higher sensitivity, i.e. lower effect concentrations, relative to a fluorescent reporter gene strain (Tg(KDR:EGFP)) exposed to the same tyrosine kinase inhibitors. Indicating that functional effects due to altered tubulogenesis or blood transport can be detected before structural changes of the endothelium are visible by fluorescence imaging. Comparison of exposure windows indicated higher specificity for angiogenesis when exposure started at later embryonic stages (24 hours post fertilization). Our findings establish video imaging in wild-type strains as viable, non-invasive, high-throughput method for the detection of chemical-induced angiogenic disruption in zebrafish embryos. We established a lable-free and non-invasive method to visualize the blood vessel network in the developing wild type zebrafish embryo. We quantified ISV inhibition by comparing WT control, treated with tyrosine kinase inhibitors (SU4312, SU5416, Sorafenib and PTK787) and a fluorescent strain (TG(KDR:EGFP)). Dose-response curves and EC50 values were determined by KNIME-Workflows" + }, { + "name" : "Keywords", + "value" : "zebrafish" + }, { + "name" : "Keywords", + "value" : "angiogenesis" + }, { + "name" : "Keywords", + "value" : "tyrosine kinase inhibitors" + }, { + "name" : "Keywords", + "value" : "developmental toxicity" + }, { + "name" : "Acknowledgements", + "value" : "We acknowledge Philipe Rocce-Sera (Oxford University) and Nils Klüver (UFZ) for help with translation of FishInspector annotation metrics to ontology terms. The transgenic strain Tg(kdr:EGFP) was kindly provided by Leibniz Institute on Aging - Fritz Lipmann Institute research group of Christoph Englert" + }, { + "name" : "License", + "value" : "CC0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/publicdomain/zero/1.0/legalcode" + } ] + }, { + "name" : "Funding statement", + "value" : "The project was funded by the German Minister of Education and Research in the funding scheme “Alternatives to Animal Tests” (Grant number 031L0232A)\nRiccardo Massei was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – 501864659" + } ], + "links" : [ { + "url" : "https://www.ufz.de/index.php?de=44460", + "attributes" : [ { + "name" : "Description", + "value" : "FishInspector - Information on the analysis software" + } ] + }, { + "url" : "https://codebase.helmholtz.cloud/ufz/tb3-cite/biotox/FishInspector", + "attributes" : [ { + "name" : "Description", + "value" : "FishInspector - GitLab Repository" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Julia Nöth" + }, { + "name" : "E-mail", + "value" : "julia.noeth@ufz.de" + }, { + "name" : "Role", + "value" : "first author" + }, { + "name" : "ORCID", + "value" : "0000-0002-5695-2209" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Stefan Scholz" + }, { + "name" : "E-mail", + "value" : "stefan.scholz@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Wibke Busch" + }, { + "name" : "E-mail", + "value" : "wibke.busch@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Tamara Tal" + }, { + "name" : "E-mail", + "value" : "tamara.tal@ufz.de" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Chih Lai" + }, { + "name" : "E-mail", + "value" : "CLAI@stthomas.edu" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Akhil Ambekar" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Riccardo Massei" + }, { + "name" : "E-mail", + "value" : "riccardo.massei@ufz.de" + }, { + "name" : "Role", + "value" : "submitter" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Helmholtz Centre for Environmental Research" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "St. Thomas University" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Duke University" + } ] + }, { + "type" : "Funding", + "attributes" : [ { + "name" : "Agency", + "value" : "German Minister of Education and Research" + }, { + "name" : "grant_id", + "value" : "031L0232A" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "OBI/WIK" + }, { + "name" : "Organism", + "value" : "Danio rerio (zebrafish)" + }, { + "name" : "Description", + "value" : "Danio rerio embryos" + }, { + "name" : "Biological entity", + "value" : "Four days old zebrafish eleuthero-embryos" + }, { + "name" : "Experimental variable", + "value" : "Chemical exposure " + }, { + "name" : "Extrinsic variable", + "value" : "SU4312, SU5416, Sorafenib, PTK787, Valproic acid" + }, { + "name" : "Intrinsic variable", + "value" : "OBI-WIK strain" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Protocols" + }, { + "name" : "Sample preparation protocol", + "value" : "Prior to imaging, all embryos were anesthetized by adding 20 µl tricaine solution (6 mg/l tricaine, TRIS 26 mM, pH 7.5 ±0.1) to each well of the microplate. " + }, { + "name" : "Growth protocol", + "value" : "A wild type adult zebrafish strain (D. rerio, strain OBI/WIK, generation F3), originating from an in-house cross of zebrafish strains UFZ-OBI and WIK, was used for all experiments. TFish were fed twice daily with dry food (SDS-400, Special Diets Services, Essex England) and once daily with Artemia sp. Fish were cultured under 14h light/10h dark photoperiod in 20 L aquaria with 1-2 fish per liter density (26.5±1 °C). Water quality parameters were pH 7–8; water hardness 2–3 mmol/L, conductivity 540–560 S/cm, nitrate < 2.5 mg/L, nitrite < 0.025 mg/L, ammonia < 0.6 mg/L, oxygen saturation 87–91 %. Spawning trays were inserted 4-6 hours before the end of the light cycle. The following day, spawning was initiated by the onset of light and eggs were collected within 1 h. Exposure in all experiment was ceased at 96 hpf. Facilities for breeding and the production of embryos were licensed by Landesdirektion Leipzig (Aktenzeichen 75-9185.64).\nFertilized and normally developed embryos were selected according to Kimmel et al. (Kimmel et al. 1995) with a dissection microscope (Olympus SZx7-ILLT) at 1 hpf. Depending on experiment, exposure was started within 2-3 h post fertilization (16 to 128 cell stages) or at 24 hpf. Exposure was conducted in rectangular 96-well microplates (Clear Polystyrene, flat bottom, Uniplate, Whatman, GE Healthcare) covered by a lid with a test volume of 400 µL of exposure media. For each replicate one embryo per well and 16 wells per concentration were assessed. Experiments were performed with at least two replicates on independent days and breeding.\n" + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "VAST BioImage" + }, { + "name" : "Imaging instrument", + "value" : "VAST BioImager (Union Biometrica, Gees, Belgium) equipped with a large particle sampler (LP sampler, Union Biometrica). " + }, { + "name" : "Image acquisition parameters", + "value" : "Lateral and dorsoventral images were obtained at 10 µm resolution at 96 hpf" + }, { + "name" : "Imaging method", + "value" : "bright-field microscopy" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Automated high-throughput image analysis " + }, { + "name" : "Image analysis overview", + "value" : "Images were processed with an amended version (1.70, available via https://github.com/sscholz-UFZ/FishInspector) of the FishInspector imaging software (Teixidó et al. 2019). The FishInspector software allows to automatically annotate morphological features including body contour, eye, lower mouth tip, pericard, otoliths, notochord, swimbladder, and yolk and to calculate diverse metrics such as feature length, size, curvature indices, or angle between feature-connecting lines. In contrast to the previously published version, FishInspector 1.70 detects morphological features based on a deep learning approach using the Matlab Neural Network Toolbox and Matlab Image Processing Toolbox (Mathworks, Natick, MS). In addition, metric calculation were included into the software, and meta information such as test compound, exposure window or test concentration was associated to each image using a microplate layout file. To facilitate training of the models, two additional programs were generated in Matlab including FishTrainer 0.9 (for training of semantic segmentation models of structural features) and FishClassificator 0.9 (for training of position classes to be used in automated flipping of images). For image training, image size was adjusted to 450 x 300 pixel to reduce computing time. This resolution was sufficient to detect the selected features (data not shown). For training of the deep learning models, approximately 3000 previously annotated images (Teixidó et al. 2022) were used. The automated annotations were corrected by the user in the event that they were not adequately detecting visible structures. User-bias was avoided by a blinded assessment of images. Following model training, experimental images used for annotation had a resolution of 1024 x 190 pixels\n\nFishInspector provided a JSON file corresponding to each image file containing the coordinates of all features and the applied smoothing factor. For each image, a csv file was generated containing calculated metrics. The software automatically provides a summary table containing metrics r of individual embryos. All experimental images and corresponding csv files can be found in Supplementary Material. All subsequent analyses were conducted using the summary excel file and a KNIME workflows with embedded R-scripts, as previously described (Teixidó et al. 2022). The KNIME workflow (all workflows are available via https://git.ufz.de/automated-fish-embryotest/zebrafish-embryo-crc/zebrafish-isv) will be provided after publication) converted pixel metrics into µm or µm², combined results from different replicates, and conducted concentration response analysis to calculate effect concentrations (EC10 and EC50). " + } ], + "subsections" : [ [ { + "type" : "Software Informations", + "attributes" : [ { + "name" : "Column 1", + "value" : "https://www.ufz.de/index.php?de=44460" + } ] + }, { + "type" : "Software Informations", + "attributes" : [ { + "name" : "Column 1", + "value" : "https://codebase.helmholtz.cloud/ufz/tb3-cite/biotox/FishInspector" + } ] + } ] ] + }, { + "accno" : "Study Component-7", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "High Content Screening - WIK/OBI" + }, { + "name" : "Description", + "value" : "VAST Biomage Data analyzed with FishInspector" + }, { + "name" : "File List", + "value" : "COMP1_sample_list.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "OBI/WIK" + }, { + "name" : "Specimen", + "value" : "Protocols" + }, { + "name" : "Image acquisition", + "value" : "VAST BioImage" + }, { + "name" : "Image analysis", + "value" : "Automated high-throughput image analysis " + } ] + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_original.json b/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_original.json new file mode 100644 index 00000000..7a7c895f --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_original.json @@ -0,0 +1,154 @@ +{ + "accno" : "S-BIAD978", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "ReleaseDate", + "value" : "2023-12-21" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "SLE Serum Induces Altered Goblet Cell Differentiation and Leakiness in Human Intestinal Organoids" + }, { + "name" : "Description", + "value" : "Human intestinal epithelial cells are the interface between luminal content and basally residing immune cells. They form a tight monolayer that constantly secretes mucus creating a multi-layered protective barrier. Alterations in this barrier can lead to increased permeability which is common in Systemic Lupus Erythematosus (SLE) patients. However, it remains unexplored how the barrier is affected. Here, we present an in vitro model specifically designed to examine the effects of SLE on epithelial cells. We utilize human colon organoids that are stimulated with serum from SLE patients. Combining transcriptomic with functional analyses revealed that SLE serum induced an expression profile marked by a reduction of goblet cell markers and changed mucus composition. Additionally, organoids exhibited imbalanced cellular composition along with enhanced permeability, altered mitochondrial function, and an interferon gene signature. Similarly, transcriptomic analysis of SLE colon biopsies revealed a downregulation of secretory markers. Our work uncovers a crucial connection between SLE and intestinal homeostasis that might be promoted in vivo through the blood, offering insights into the causal connection of barrier dysfunction and autoimmune diseases." + }, { + "name" : "Keywords", + "value" : "Organoids, brightfield, serum stimulation" + }, { + "name" : "License", + "value" : "CC0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/publicdomain/zero/1.0/legalcode" + } ] + } ], + "links" : [ { + "url" : "https://www.biorxiv.org/content/10.1101/2023.07.04.547690v1" + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Inga Hensel" + }, { + "name" : "E-mail", + "value" : "hensel@bio.mx" + }, { + "name" : "Role", + "value" : "first author" + }, { + "name" : "ORCID", + "value" : "0000-0003-2716-5879" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "BioMedX Institute" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Brightfield images of serum stimulated organoids" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "This is the source data for figure 1B of https://www.biorxiv.org/content/10.1101/2023.07.04.547690v1." + }, { + "name" : "Biological entity", + "value" : "Human descending colon organoids" + }, { + "name" : "Experimental variable", + "value" : "The organoids were stimulated for 72h with either control or SLE serum. Images were acquired and analyzed using the OrgaQuant tool. " + }, { + "name" : "Extrinsic variable", + "value" : "Control or Systemic Lupus Erythematosus serum from patients" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Organoid serum stimulation" + }, { + "name" : "Sample preparation protocol", + "value" : "Organoids were passaged as described above with the modification of excluding bigger sized fragments by using a 70 µm strainer after the dissociation. In addition, fragments were counted and 400 fragments/µl were seeded. Organoids were grown in growth medium (Table EV2) for four days before dissociating them into single cells by incubation for 90s in Accutase followed by mechanical dissociation as described above. Bigger fragments were removed by using a 40 µm strainer. Then 800 cells/µl were seeded in 10 µl Matrigel mix in 96-well plate. After polymerization 100 µl expansion medium were added containing Y-27632. Organoids were stimulated with 5% SLE or 5% control serum in stimulation medium (Table EV2). In case of IFN-α stimulation 100 pg/ml IFN-α2B (Humankine, HZ-1072) were added in addition to control serum. Anifrolumab was added at a final concentration of 10 µg/ml. Stimulation started either 24h, 48h or 72h before harvesting organoids on day five." + }, { + "name" : "Growth protocol", + "value" : "Crypt isolation was performed as previously published.(Sato et al, 2011) The mucosa of approximately 1 cm2 was separated from the underlying tissue and cut into small pieces, washed with cold PBS before incubation in 10 mM EDTA/PBS for 1h at 4°C under constant rocking. The biopsies were then transferred to 5 ml cold PBS and crypts were liberated by pipetting. This was repeated twice, and the pooled fractions were centrifuged at 250g for 5 min at 4°C. The pellet was once washed in base medium (Table EV2) before the crypts were resuspended in 45 µl 80% Matrigel (#356231, Corning) in expansion medium (Table EV2) and plated in small drops in a 24-well plate. After polymerization 500 µl expansion medium containing Y-27632 was added until the first passage or later for the first days after passaging. Organoids were cultured at 37°C and 95% O2, 5% CO2 humid atmosphere. Initial passage was performed when organoids reached a size of approximately 200-300 µm in diameter. After establishing the organoid line organoids were passaged at a ratio of 1:6-1:10 every 4-5 days by a 45s incubation in Accutase at 37°C followed by mechanical dissociation in 6 ml base medium with a 10 ml pipet equipped with a 200 µl pipet tip. Organoid fragments were centrifuged at 150g for 5 min at 4°C and plated as stated above. Medium was changed every 2-3 days. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Brightfield images of stimulated organoids" + }, { + "name" : "Imaging instrument", + "value" : "Nikon Eclipse Ti2 inverted microscope" + }, { + "name" : "Image acquisition parameters", + "value" : "Several images were taken per well and stitched to show the whole Matrigel dome containing organoids. Different z planes were imaged." + }, { + "name" : "Imaging method", + "value" : "bright-field microscopy" + } ] + }, { + "accno" : "Study Component-4", + "type" : "Study Component", + "attributes" : [ { + "name" : "Name", + "value" : "Organoid size" + }, { + "name" : "Description", + "value" : "The organoid size after serum stimulation was analyzed" + }, { + "name" : "File List", + "value" : "1B - source images.json" + } ], + "subsections" : [ { + "type" : "Associations", + "attributes" : [ { + "name" : "Biosample", + "value" : "Brightfield images of serum stimulated organoids" + }, { + "name" : "Specimen", + "value" : "Organoid serum stimulation" + }, { + "name" : "Image acquisition", + "value" : "Brightfield images of stimulated organoids" + } ] + }, { + "accno" : "Image analysis-1", + "type" : "Image analysis" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Organoid size analysis using OrgaQuant" + }, { + "name" : "Image analysis overview", + "value" : "Images were analyzed using OrgaQuant tool (Kassis et al, 2019) with settings adjusted to 1600 (image size), 2 (contrast) and 0.7 (confidence threshold). Average diameter was calculated. " + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_override.json b/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_override.json new file mode 100644 index 00000000..a46a1b38 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BIAD978/S-BIAD978_override.json @@ -0,0 +1,154 @@ +{ + "accno" : "S-BIAD978", + "attributes" : [ { + "name" : "Template", + "value" : "BioImages.v4" + }, { + "name" : "ReleaseDate", + "value" : "2023-12-21" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "SLE Serum Induces Altered Goblet Cell Differentiation and Leakiness in Human Intestinal Organoids" + }, { + "name" : "Description", + "value" : "Human intestinal epithelial cells are the interface between luminal content and basally residing immune cells. They form a tight monolayer that constantly secretes mucus creating a multi-layered protective barrier. Alterations in this barrier can lead to increased permeability which is common in Systemic Lupus Erythematosus (SLE) patients. However, it remains unexplored how the barrier is affected. Here, we present an in vitro model specifically designed to examine the effects of SLE on epithelial cells. We utilize human colon organoids that are stimulated with serum from SLE patients. Combining transcriptomic with functional analyses revealed that SLE serum induced an expression profile marked by a reduction of goblet cell markers and changed mucus composition. Additionally, organoids exhibited imbalanced cellular composition along with enhanced permeability, altered mitochondrial function, and an interferon gene signature. Similarly, transcriptomic analysis of SLE colon biopsies revealed a downregulation of secretory markers. Our work uncovers a crucial connection between SLE and intestinal homeostasis that might be promoted in vivo through the blood, offering insights into the causal connection of barrier dysfunction and autoimmune diseases." + }, { + "name" : "Keywords", + "value" : "Organoids, brightfield, serum stimulation" + }, { + "name" : "License", + "value" : "CC0", + "valqual" : [ { + "name" : "URL", + "value" : "https://creativecommons.org/publicdomain/zero/1.0/legalcode" + } ] + } ], + "links" : [ { + "url" : "https://www.biorxiv.org/content/10.1101/2023.07.04.547690v1" + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Inga Hensel" + }, { + "name" : "E-mail", + "value" : "hensel@bio.mx" + }, { + "name" : "Role", + "value" : "first author" + }, { + "name" : "ORCID", + "value" : "0000-0003-2716-5879" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "BioMedX Institute" + } ] + }, { + "accno" : "Biosample-1", + "type" : "Biosample", + "attributes" : [ { + "name" : "Title", + "value" : "Brightfield images of serum stimulated organoids" + }, { + "name" : "Organism", + "value" : "Homo sapiens (human)" + }, { + "name" : "Description", + "value" : "This is the source data for figure 1B of https://www.biorxiv.org/content/10.1101/2023.07.04.547690v1." + }, { + "name" : "Biological entity", + "value" : "Human descending colon organoids" + }, { + "name" : "Experimental variable", + "value" : "The organoids were stimulated for 72h with either control or SLE serum. Images were acquired and analyzed using the OrgaQuant tool. " + }, { + "name" : "Extrinsic variable", + "value" : "Control or Systemic Lupus Erythematosus serum from patients" + } ] + }, { + "accno" : "Specimen-2", + "type" : "Specimen", + "attributes" : [ { + "name" : "Title", + "value" : "Organoid serum stimulation" + }, { + "name" : "Sample preparation protocol", + "value" : "Organoids were passaged as described above with the modification of excluding bigger sized fragments by using a 70 µm strainer after the dissociation. In addition, fragments were counted and 400 fragments/µl were seeded. Organoids were grown in growth medium (Table EV2) for four days before dissociating them into single cells by incubation for 90s in Accutase followed by mechanical dissociation as described above. Bigger fragments were removed by using a 40 µm strainer. Then 800 cells/µl were seeded in 10 µl Matrigel mix in 96-well plate. After polymerization 100 µl expansion medium were added containing Y-27632. Organoids were stimulated with 5% SLE or 5% control serum in stimulation medium (Table EV2). In case of IFN-α stimulation 100 pg/ml IFN-α2B (Humankine, HZ-1072) were added in addition to control serum. Anifrolumab was added at a final concentration of 10 µg/ml. Stimulation started either 24h, 48h or 72h before harvesting organoids on day five." + }, { + "name" : "Growth protocol", + "value" : "Crypt isolation was performed as previously published.(Sato et al, 2011) The mucosa of approximately 1 cm2 was separated from the underlying tissue and cut into small pieces, washed with cold PBS before incubation in 10 mM EDTA/PBS for 1h at 4°C under constant rocking. The biopsies were then transferred to 5 ml cold PBS and crypts were liberated by pipetting. This was repeated twice, and the pooled fractions were centrifuged at 250g for 5 min at 4°C. The pellet was once washed in base medium (Table EV2) before the crypts were resuspended in 45 µl 80% Matrigel (#356231, Corning) in expansion medium (Table EV2) and plated in small drops in a 24-well plate. After polymerization 500 µl expansion medium containing Y-27632 was added until the first passage or later for the first days after passaging. Organoids were cultured at 37°C and 95% O2, 5% CO2 humid atmosphere. Initial passage was performed when organoids reached a size of approximately 200-300 µm in diameter. After establishing the organoid line organoids were passaged at a ratio of 1:6-1:10 every 4-5 days by a 45s incubation in Accutase at 37°C followed by mechanical dissociation in 6 ml base medium with a 10 ml pipet equipped with a 200 µl pipet tip. Organoid fragments were centrifuged at 150g for 5 min at 4°C and plated as stated above. Medium was changed every 2-3 days. " + } ] + }, { + "accno" : "Image acquisition-3", + "type" : "Image acquisition", + "attributes" : [ { + "name" : "Title", + "value" : "Brightfield images of stimulated organoids" + }, { + "name" : "Imaging instrument", + "value" : "Nikon Eclipse Ti2 inverted microscope" + }, { + "name" : "Image acquisition parameters", + "value" : "Several images were taken per well and stitched to show the whole Matrigel dome containing organoids. Different z planes were imaged." + }, { + "name" : "Imaging method", + "value" : "bright-field microscopy" + } ] + }, { + "accno" : "Image analysis-5", + "type" : "Image analysis", + "attributes" : [ { + "name" : "Title", + "value" : "Organoid size analysis using OrgaQuant" + }, { + "name" : "Image analysis overview", + "value" : "Images were analyzed using OrgaQuant tool (Kassis et al, 2019) with settings adjusted to 1600 (image size), 2 (contrast) and 0.7 (confidence threshold). Average diameter was calculated. 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Mouse models of cancer are instrumental in the understanding of disease and the development of new treatments for patients. In this project we compare similarity of chemically induced mouse liver cancers to human liver cancers." + }, { + "name" : "Data availability", + "value" : "Complementary views on this dataset are available through different repositories. Image data files are available from BioStudies archive at the European Bioinformatics Institute (EMBL-EBI). Exome sequencing data is available from ENA at EMBL-EBI. Protocol: Liver tissue was harvested from mice, fixed for 24 hours in 10% neutral buffered formalin, processed and paraffin embedded. 3um tissue sections were stained with haematoxylin and eosin (H&E) using Leica ST5020 multistainer with following protocol: 1. Xylene (2 x 10 min); 2. 100% ethanol (2 x 5 min); 3. 70% ethanol (5 min); 4. Tap water (5 min); 5. Harris Haematoxylin (5 min); 6. Tap water (5 min); 7. 1% acid alcohol (10 sec); 8. Tap water (5 min); 9. Eosin (2 min); 10. Tap water (20 sec); 11. 70% ethanol (20 sec); 12. 100% ethanol (2 x 30 sec); 13. Xylene (2 x 5 min). Slides were scanned at with Aperio AT2 (Leica) x20 (0.5 microns per pixel). 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"name" : "TumourGrade", + "value" : "well" + }, { + "name" : "Date of birth", + "value" : "2013-10-15 00:00:00.000000" + }, { + "name" : "Date of death", + "value" : "2014-04-22 00:00:00.000000" + }, { + "name" : "Treatment date", + "value" : "2013-10-30_00:00:00.000000" + }, { + "name" : "Treatment agent", + "value" : "DEN" + }, { + "name" : "Treatment dose", + "value" : "20" + }, { + "name" : "Treatment dose unit", + "value" : "ug/g body weight" + }, { + "name" : "Batch", + "value" : "HR8402" + }, { + "name" : "Block", + "value" : "BL106408" + } ], + "type" : "file" + } ] ] + } ] + }, + "type" : "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_original.json b/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_original.json new file mode 100644 index 00000000..f0393630 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_original.json @@ -0,0 +1,107 @@ +{ + "accno" : "S-BSST651", + "attributes" : [ { + "name" : "Template", + "value" : "Default" + }, { + "name" : "Title", + "value" : "A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies " + }, { + "name" : "ReleaseDate", + "value" : "2022-05-22" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies " + }, { + "name" : "Description", + "value" : "Detailed molecular analysis is of increasing importance in research into the regulation of biochemical pathways, organismal growth and disease. Lipidomics in particular is increasingly sought after as it provides insight into molecular species involved in energy storage, signalling and fundamental cellular structures. This has led to the use of a range of tools and techniques to acquire lipidomics data. 31P NMR for lipidomics offers well-resolved head group/lipid class analysis, structural data that can be used to inform and strengthen interpretation of mass spectrometry data and part of structural determination a priori. In the present study, we codify the use of 31P NMR for lipidomics studies to make the technique more accessible to new users and more useful for a wider range of questions. The technique can be used in isolation (phospholipidomics) or as a part of determining lipid composition (lipidomics). We describe the process from sample extraction to data processing and analysis. This pipeline is important because it allows greater thoroughness in lipidomics studies and increases scope for answering scientific questions about lipid systems. \n\nChemRxiv DOI: 10.26434/chemrxiv.14053976.v1\nAnal. Bioanal. Chem DOI: " + }, { + "name" : "Organism", + "value" : "Mus musculus (mouse)" + }, { + "name" : "Organism", + "value" : "Glycine max (soybean)" + }, { + "name" : "Annotation 1", + "value" : "NMR" + }, { + "name" : "Annotation 2", + "value" : "Lipidomics" + } ], + "files" : [ { + "path" : "Data.zip", + "size" : 479720254, + "attributes" : [ { + "name" : "Description", + "value" : "1D and 2D NMR data " + }, { + "name" : "Type", + "value" : "Bruker format" + } ], + "type" : "file" + } ], + "subsections" : [ { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Samuel Furse" + }, { + "name" : "E-mail", + "value" : "samuel@samuelfurse.com" + }, { + "name" : "ORCID", + "value" : "0000-0003-4267-2051" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Huw Williams" + }, { + "name" : "E-mail", + "value" : "huw.williams@williams@nottingham.ac.uk" + }, { + "name" : "ORCID", + "value" : "0000-0002-2623-6287" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Albert Koulman" + }, { + "name" : "E-mail", + "value" : "ak675@medschl.cam.ac.uk" + }, { + "name" : "ORCID", + "value" : "0000-0001-9998-051X" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "Organization", + "attributes" : [ { + "name" : "Name", + "value" : "European Bioinformatics Institute (EMBL-EBI)" + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_override.json b/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_override.json new file mode 100644 index 00000000..d17d5b21 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BSST651/S-BSST651_override.json @@ -0,0 +1,107 @@ +{ + "accno" : "S-BSST651", + "attributes" : [ { + "name" : "Template", + "value" : "Default" + }, { + "name" : "Title", + "value" : "A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies " + }, { + "name" : "ReleaseDate", + "value" : "2022-05-22" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Title", + "value" : "A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies " + }, { + "name" : "Description", + "value" : "Detailed molecular analysis is of increasing importance in research into the regulation of biochemical pathways, organismal growth and disease. Lipidomics in particular is increasingly sought after as it provides insight into molecular species involved in energy storage, signalling and fundamental cellular structures. This has led to the use of a range of tools and techniques to acquire lipidomics data. 31P NMR for lipidomics offers well-resolved head group/lipid class analysis, structural data that can be used to inform and strengthen interpretation of mass spectrometry data and part of structural determination a priori. In the present study, we codify the use of 31P NMR for lipidomics studies to make the technique more accessible to new users and more useful for a wider range of questions. The technique can be used in isolation (phospholipidomics) or as a part of determining lipid composition (lipidomics). We describe the process from sample extraction to data processing and analysis. This pipeline is important because it allows greater thoroughness in lipidomics studies and increases scope for answering scientific questions about lipid systems. \n\nChemRxiv DOI: 10.26434/chemrxiv.14053976.v1\nAnal. Bioanal. Chem DOI: " + }, { + "name" : "Organism", + "value" : "Mus musculus (mouse)" + }, { + "name" : "Organism", + "value" : "Glycine max (soybean)" + }, { + "name" : "Annotation 1", + "value" : "NMR" + }, { + "name" : "Annotation 2", + "value" : "Lipidomics" + } ], + "files" : [ { + "path" : "Data.zip", + "size" : 479720254, + "attributes" : [ { + "name" : "Description", + "value" : "1D and 2D NMR data " + }, { + "name" : "Type", + "value" : "Bruker format" + } ], + "type" : "file" + } ], + "subsections" : [ { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Samuel Furse" + }, { + "name" : "E-mail", + "value" : "samuel@samuelfurse.com" + }, { + "name" : "ORCID", + "value" : "0000-0003-4267-2051" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Huw Williams" + }, { + "name" : "E-mail", + "value" : "huw.williams@nottingham.ac.uk" + }, { + "name" : "ORCID", + "value" : "0000-0002-2623-6287" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "Author", + "attributes" : [ { + "name" : "Name", + "value" : "Albert Koulman" + }, { + "name" : "E-mail", + "value" : "ak675@medschl.cam.ac.uk" + }, { + "name" : "ORCID", + "value" : "0000-0001-9998-051X" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "Organization", + "attributes" : [ { + "name" : "Name", + "value" : "European Bioinformatics Institute (EMBL-EBI)" + } ] + } ] + }, + "type" : "submission" + } \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_original.json b/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_original.json new file mode 100644 index 00000000..ee2f26d2 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_original.json @@ -0,0 +1,284 @@ +{ + "accno" : "S-BSST744", + "attributes" : [ { + "name" : "Template", + "value" : "Default" + }, { + "name" : "Title", + "value" : "Nano-scale Architecture of Blood-Brain Barrier Tight-Junctions" + }, { + "name" : "ReleaseDate", + "value" : "2021-12-12" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Description", + "value" : "Tight junctions (TJs) between blood-brain barrier (BBB) endothelial cells construct a robust physical barrier, whose damage underlies BBB dysfunctions related to several neurodegenerative diseases. What makes these highly specialized BBB-TJs extremely restrictive remains unknown. Here, we use super-resolution microscopy (dSTORM) to uncover new structural and functional properties of BBB TJs. Focusing on three major components, Nano-scale resolution revealed sparse (occludin) vs. clustered (ZO1/claudin-5) molecular architecture. Developmentally, permeable TJs become first restrictive to large molecules, and only later to small molecules, with claudin-5 proteins arrangement compacting during this maturation process. Mechanistically, we reveal that ZO1 clustering is independent of claudin-5 in-vivo. In contrast to accepted knowledge, we found that in the developmental context, total levels of claudin-5 inversely correlate with TJ functionality" + }, { + "name" : "Organism", + "value" : "Mus musculus (mouse)" + } ], + "files" : [ { + "path" : "fig 8", + "size" : 12674822, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 8: Investigating BBB TJ function using super-resolution microscopy. Tracer challenges testing cortical capillaries permeability with dSTORM imaging, provides evidence of leakage across immature TJs. a, E12 TJ function tested with an in utero embryonic liver tracer injection method (Ben-Zvi et al., 2014). 10 kDa dextran signals (upper-left) and ?443 Dalton sulfo-NHS-biotin signals (lower-left) were found in the luminal side, intermingling with claudin-5 clusters (arrows) and in the abluminal side and further away (presumably brain tissue, arrowheads). These were interpreted as evidence of tracer leakage across immature TJs. Following trans-cardiac tracer challenges, dSTORM imaging shows P9 capillaries can restrict movement of tracer molecules from the lumen to the brain side (10 kDa dextran upper-right, and ?443 Dalton sulfo-NHS-biotin lower-right). E16 cortical capillaries were previously found to prevent leakage of 10-kDa tracers (Ben-Zvi et al., 2014; Licht, Dor-Wollman, Ben-Zvi, Rothe, & Keshet, 2015), also validated here with dSTORM imaging (middle-upper). Surprisingly, at this stage sulfo-NHS-biotin was not restricted to the vessels’ lumen, evident also on the brain side (middle-lower arrowheads) and intermingling with claudin-5 clusters (arrows). Scale bars, 100 nm. L – capillary lumen. n=40 capillaries for each tracer of 3 pups/embryos. b-c, Developmental changes in permeability are reflected in quantification of tracer signal density at the abluminal side of the junctions (10 kDa dextran at b, and 443 Dalton sulfo-NHS-biotin at c). Relative leakage index was calculated as tracer signal density (signals/area) in a fixed area and distance from the abluminal side of the claudin-5 signal, and was normalized to the average signal density at P9 (set as leakage index=1). n=10 capillaries for each tracer of 3 pups/embryos, *P<0.0123, **P<0.0031,***P<0.0006, ****P<0.0001, Kruskal-Wallis test and Dunn’s test for multiple comparisons." + } ], + "type" : "directory" + }, { + "path" : "fig 7", + "size" : 367688755, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 7: Nano-scale organization of both ZO1 and occludin are independent of claudin-5 expression. a-b, Claudin-5 antibodies specificity was confirmed by both confocal microscopy (a, Scale bars, 50 µm) and dSTORM microscopy (b, Scale bars, 0.1 µm), with no detectable staining in E16 cortical null tissues (Isolectin staining used to localize vasculature, n=4 wild-type, 4 claudin-5 null embryos). c, E16 claudin-5 null and wild-type littermates cortical capillaries imaged with dSTORM display unaltered ZO1 clustering organization and occludin dispersed organization patterns. Scale bars, 100 nm. d, Total cellular signal quantifications revealed that occludin levels were ?1.29-fold higher in claudin-5 null capillaries compared to wild-type. Total cellular ZO1 signal levels were also higher in claudin-5 null capillaries (not statistically significant). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test). L – capillary lumen. n=109 capillaries of 4 wild-type embryos and 86 capillaries of 4 claudin-5 null embryos." + } ], + "type" : "directory" + }, { + "path" : "fig 6", + "size" : 14873534, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 6: Molecular organization of mouse cortical BBB TJs. Nano-scale molecular organization of TJ proteins in cortical capillaries of postnatal wild-type mice (P9). a, Claudin-5 and ZO1 display clustered organization (left) whereas occludin was much less organized in discrete clusters and had more dispersed organization patterns (right). 2D-STORM imaging data demonstrates that signals of all three TJ proteins are in close proximity (‘Gaussian visualization’ in which signal intensity correlates with localization precision). An inset with magnifications of each cluster (right images) demonstrates the very high molecular density of TJ proteins (‘Cross visualization’ shows all resolved signals where each single-molecule signal displays as a cross). Scale bars, 100 nm. Representative signal numbers are shown. n=40 capillaries of 4 wild-type pups. L – capillary lumen. b, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining of E12 and P9 cortical capillary cross-sections. Note that some claudin-5 clusters are coupled with ZO1 clusters (high magnification insets, arrows) while some are independent claudin-5 clusters (arrowhead). Scale bars, 1 µm and 100 nm in insets. c, Average density of P9 claudin-5 clusters that were coupled with ZO1 clusters was ?5-fold higher than independent claudin-5 clusters. The average density of E12 claudin-5 clusters was similar regardless of proximity to ZO1 clusters, and was low compared to P9 independent claudin-5 clusters. n=40 clusters from 11 capillaries and 43 clusters from 11 capillaries (of 3 embryos/pups, P9 and E12 respectively). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)" + } ], + "type" : "directory" + }, { + "path" : "fig 5", + "size" : 23503480, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 5: Total cellular claudin-5 abundance does not correlate with BBB restrictive properties. Quantifications of claudin-5 levels and clustering properties along developmental BBB maturation a, dSTORM (right) compared to epi-fluorescent images (left) of claudin-5 immunostaining in E12 and P9 cortical capillary cross-sections. Two distinct claudin-5 organizations could be observed; discrete clusters (arrowheads) and a more defused claudin-5 appearance composed of many small clusters with relatively small gaps between them, evident only in E12 capillaries (arrow, see Extended Data Fig. S1a for further analysis). Scale bars, 1 µm. b, Claudin-5 clustering-properties analysis showed that there were about 2.6 times more discrete clusters per capillary at E12 than at P9 (a set of 20 capillaries of each age). Distribution of claudin-5 clusters area in E12 capillaries was skewed towards smaller clusters and the average cluster area was slightly smaller in E12 with no dramatic difference between the distributions (average of 0.309 µm2 (E12) vs. 0.3413 µm2 (P9). There was no dramatic difference in the distribution of signals per cluster or signal densities between the two groups (see Fig. S1b). n=3 pups/embryos, 20 capillaries, 657 clusters (E12) and 246 clusters (P9). Data are mean±s.e.m. c, Quantifications of total cellular claudin-5 per capillary cross section shows a shift towards lower claudin-5 levels and smaller capillary diameter in P9 than in E12 vasculature. Capillary diameter was significantly smaller (5.9±0.39 µm (P9), 11.1±0.47µm (E12)), total number of claudin-5 signals per capillary was significantly lower (3,590±372 (P9), 14,341±1,257 (E12)). d, Normalizing the total number of signals per capillary to its diameter shows the average claudin-5 cellular abundance is significantly lower at P9. n=25 capillaries (E12) and 27 capillaries (P9) of 3 embryos/pups. Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + }, { + "path" : "fig 4", + "size" : 48910371, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 4: Claudin-5 exhibits clustered organization in cortical capillaries. Imaging in cortical fixed tissue sections of post-natal day 9 mice. a, Low magnification view of claudin-5 staining imaged by epi-fluorescent microscopy showing vascular fragments in cross-sections (arrows) or in sagittal-sections (arrowheads, scale bar, 50 µm). b, Claudin-5 exhibits clustered organization in vivo; dSTORM (right) compared to epi-fluorescent images (left) of claudin-5 immunostaining in P9 cortical capillary cross-section (upper panel) or sagittal-section (lower panel) (scale bars, 1 µm), n>30 capillaries." + } ], + "type" : "directory" + }, { + "path" : "fig 3", + "size" : 48541160, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 3: Claudin-5 signals in dSTORM imaging are exclusively localized to vascular structures. dSTORM imaging in cortical fixed tissue sections of post-natal day 9 mice. a, Illustration of a vascular structure with cross versus sagittal section directions, and the projected orientation of endothelial cells contact points. b, Claudin-5 staining (green) together with fluorescent circulating tracers (10 kDa dextran, and ?443 Dalton sulfo-NHS-biotin, magenta) are used to demarcate sagittal views of elongated vessels (dashed line, Scale bars, 1 µm). c, Staining for claudin-5 (green) together with the endothelial-specific transcription factor ERG (gray) showing capillary cross and sagittal sections (Scale bars, 1 µm). L – capillary lumen, N – endothelial nucleus. n>30 capillaries." + } ], + "type" : "directory" + }, { + "path" : "fig 2", + "size" : 190806164, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 2: Changes in nano-scale architecture correlates with tight junction function. Enhanced TJ function is accompanied by formation of smaller and denser clusters of claudin-5. a, Enhanced TJ function demonstrated by increase in TEER, along the first days of induced human brain microvascular endothelial-like cell (iBMEC) culture (n=4 experiments/12 inserts. TEER here shows data of a representative experiment. For average change in TEER across all experiments see Supplementary Figure S1b. n=4 inserts for permeability). b, Enhanced TJ function demonstrated by reduced permeability to sodium fluorescein (T0 represents low TEER and T1 represents high TEER states, n=4 inserts). Data are mean ± SD. *** P<0.0003 (two tailed pair t-test). c, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining in iBMEC confluent monolayers. Claudin-5 signals are concentrated in discrete and short foci at both time points. Scale bar, 1 µm. d, Examples of dSTORM imaging simulation of claudin-5 in iBMECs used for quantifications of clustering properties (produced by a custom clustering Matlab code, see methods for details). Cluster pattern visualization showing all points that belong to the same cluster with the same identifying color. e, Quantifications of claudin-5 clustering properties showed a shift towards smaller clusters with more claudin-5 signals per cluster along the improvement in TJ function. f, Average claudin-5 cluster density more than doubled (from 14,341 to 33,141 signals/µm2) with the improvement in TJ function (n=90 clusters (in lower TEER) and 278 clusters (in higher TEER) in triplicate cultures of two independent experiments). Data are mean ± s.e.m. *P < 0.01 (two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + }, { + "path" : "fig 1", + "size" : 104960161, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 1: Super-resolution microscopy of endothelial tight junctions. In vitro process of TJ maturation is accompanied by TJ architectural changes characterized by the formation of smaller, denser and more discrete clusters of TJ proteins. a, Epi-fluorescent imaging of claudin-5 (green) and ZO1 (red) immunostaining of bEND.3 cells in indicated time points after the cultures reached confluence state. Note translocation of claudin-5 from cytoplasmic localizations into continuous lines around the boundaries of the cells (known as ‘strands’), along the in vitro maturation process. Scale bars, 10 µm and 5 µm in insets. b, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining of bEND.3 cells confluent monolayers. TJ proteins form bead-like structures, especially in the super-confluence state. Claudin-5 signals are more concentrated in discrete and shorter foci (flanking ZO1 signals, arrowheads, right) than in the post-confluence state (arrows, left). During maturation TJ proteins translocate from different cellular locations (left) almost exclusively into the lateral cell membranes (right). Scale bar, 1 µm. c, Examples of dSTORM imaging simulation of claudin-5 in bEND.3 cells used for quantifications of clustering properties (produced by a custom clustering Matlab code, see methods for details). Signals were defined to be clustered if their 2D location was smaller than 70 nm threshold distance. Cluster pattern visualization showing all points that belong to the same cluster with the same identifying color. d, Quantifications of claudin-5 clustering properties showed a shift towards smaller clusters with more claudin-5 signals per cluster at the super-confluence state. Clusters with higher numbers of signals were more abundant at this late state, especially in clusters with area smaller than 0.3 µm2. e, Average claudin-5 cluster density was ?4-fold higher at the super-confluence state than in the post-confluence state (n=183 clusters (post-confluence) and 281 clusters (super-confluence) in 5 independent experiments). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + } ], + "links" : [ { + "url" : "https://www.biorxiv.org/content/10.1101/2021.08.12.456150v1.article-info", + "attributes" : [ { + "name" : "Description", + "value" : "pre print" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ayal Ben zvi" + }, { + "name" : "E-mail", + "value" : "ayalb@ekmd.huji.ac.il" + }, { + "name" : "ORCID", + "value" : "0000-0003-4012-7789" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ron Dzikowski" + }, { + "name" : "E-mail", + "value" : "rond@ekmd.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o5", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Gad D. Vatine" + }, { + "name" : "E-mail", + "value" : "vatineg@bgu.ac.il" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Eilon Sherman" + }, { + "name" : "E-mail", + "value" : "eilonsher@gmail.com" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Britta Engelhardt" + }, { + "name" : "E-mail", + "value" : "‫britta.engelhardt@tki.unibe.ch" + }, { + "name" : "affiliation", + "value" : "o4", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : " Urban Deutsch" + }, { + "name" : "E-mail", + "value" : " urban.deutsch@tki.unibe.ch" + }, { + "name" : "affiliation", + "value" : "o4", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Meshi Zorsky" + }, { + "name" : "E-mail", + "value" : "meshiz@post.bgu.ac.il" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Oren Yakovian" + }, { + "name" : "E-mail", + "value" : "oren.yakovian@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Batia Bell" + }, { + "name" : "E-mail", + "value" : "batia.bell@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Shira Anzi" + }, { + "name" : "E-mail", + "value" : "shira.anzi@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Esther Sasson" + }, { + "name" : "E-mail", + "value" : "esti.sasson@mail.huji.ac.il" + }, { + "name" : "ORCID", + "value" : "0000-0001-7156-1516" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Racah Institute of Physics, The Hebrew University, Jerusalem 9190401, Israel" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "The Department of Physiology and Cell Biology, Faculty of Health Sciences, The Regenerative Medicine and Stem Cell (RMSC) research Center and the Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel" + } ] + }, { + "accno" : "o4", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Theodor Kocher Institute, University of Bern, Bern, Switzerland" + } ] + }, { + "accno" : "o5", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Department of Microbiology and Molecular Genetics, The Kuvin Center for the Study of Infectious and Tropical Diseases, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel." + } ] + } ] + }, + "type" : "submission" +} \ No newline at end of file diff --git a/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_override.json b/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_override.json new file mode 100644 index 00000000..8163bc63 --- /dev/null +++ b/bia-ingest/submission_overrides/biostudies/S-BSST744/S-BSST744_override.json @@ -0,0 +1,284 @@ +{ + "accno" : "S-BSST744", + "attributes" : [ { + "name" : "Template", + "value" : "Default" + }, { + "name" : "Title", + "value" : "Nano-scale Architecture of Blood-Brain Barrier Tight-Junctions" + }, { + "name" : "ReleaseDate", + "value" : "2021-12-12" + }, { + "name" : "AttachTo", + "value" : "BioImages" + } ], + "section" : { + "type" : "Study", + "attributes" : [ { + "name" : "Description", + "value" : "Tight junctions (TJs) between blood-brain barrier (BBB) endothelial cells construct a robust physical barrier, whose damage underlies BBB dysfunctions related to several neurodegenerative diseases. What makes these highly specialized BBB-TJs extremely restrictive remains unknown. Here, we use super-resolution microscopy (dSTORM) to uncover new structural and functional properties of BBB TJs. Focusing on three major components, Nano-scale resolution revealed sparse (occludin) vs. clustered (ZO1/claudin-5) molecular architecture. Developmentally, permeable TJs become first restrictive to large molecules, and only later to small molecules, with claudin-5 proteins arrangement compacting during this maturation process. Mechanistically, we reveal that ZO1 clustering is independent of claudin-5 in-vivo. In contrast to accepted knowledge, we found that in the developmental context, total levels of claudin-5 inversely correlate with TJ functionality" + }, { + "name" : "Organism", + "value" : "Mus musculus (mouse)" + } ], + "files" : [ { + "path" : "fig 8", + "size" : 12674822, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 8: Investigating BBB TJ function using super-resolution microscopy. Tracer challenges testing cortical capillaries permeability with dSTORM imaging, provides evidence of leakage across immature TJs. a, E12 TJ function tested with an in utero embryonic liver tracer injection method (Ben-Zvi et al., 2014). 10 kDa dextran signals (upper-left) and ?443 Dalton sulfo-NHS-biotin signals (lower-left) were found in the luminal side, intermingling with claudin-5 clusters (arrows) and in the abluminal side and further away (presumably brain tissue, arrowheads). These were interpreted as evidence of tracer leakage across immature TJs. Following trans-cardiac tracer challenges, dSTORM imaging shows P9 capillaries can restrict movement of tracer molecules from the lumen to the brain side (10 kDa dextran upper-right, and ?443 Dalton sulfo-NHS-biotin lower-right). E16 cortical capillaries were previously found to prevent leakage of 10-kDa tracers (Ben-Zvi et al., 2014; Licht, Dor-Wollman, Ben-Zvi, Rothe, & Keshet, 2015), also validated here with dSTORM imaging (middle-upper). Surprisingly, at this stage sulfo-NHS-biotin was not restricted to the vessels’ lumen, evident also on the brain side (middle-lower arrowheads) and intermingling with claudin-5 clusters (arrows). Scale bars, 100 nm. L – capillary lumen. n=40 capillaries for each tracer of 3 pups/embryos. b-c, Developmental changes in permeability are reflected in quantification of tracer signal density at the abluminal side of the junctions (10 kDa dextran at b, and 443 Dalton sulfo-NHS-biotin at c). Relative leakage index was calculated as tracer signal density (signals/area) in a fixed area and distance from the abluminal side of the claudin-5 signal, and was normalized to the average signal density at P9 (set as leakage index=1). n=10 capillaries for each tracer of 3 pups/embryos, *P<0.0123, **P<0.0031,***P<0.0006, ****P<0.0001, Kruskal-Wallis test and Dunn’s test for multiple comparisons." + } ], + "type" : "directory" + }, { + "path" : "fig 7", + "size" : 367688755, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 7: Nano-scale organization of both ZO1 and occludin are independent of claudin-5 expression. a-b, Claudin-5 antibodies specificity was confirmed by both confocal microscopy (a, Scale bars, 50 µm) and dSTORM microscopy (b, Scale bars, 0.1 µm), with no detectable staining in E16 cortical null tissues (Isolectin staining used to localize vasculature, n=4 wild-type, 4 claudin-5 null embryos). c, E16 claudin-5 null and wild-type littermates cortical capillaries imaged with dSTORM display unaltered ZO1 clustering organization and occludin dispersed organization patterns. Scale bars, 100 nm. d, Total cellular signal quantifications revealed that occludin levels were ?1.29-fold higher in claudin-5 null capillaries compared to wild-type. Total cellular ZO1 signal levels were also higher in claudin-5 null capillaries (not statistically significant). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test). L – capillary lumen. n=109 capillaries of 4 wild-type embryos and 86 capillaries of 4 claudin-5 null embryos." + } ], + "type" : "directory" + }, { + "path" : "fig 6", + "size" : 14873534, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 6: Molecular organization of mouse cortical BBB TJs. Nano-scale molecular organization of TJ proteins in cortical capillaries of postnatal wild-type mice (P9). a, Claudin-5 and ZO1 display clustered organization (left) whereas occludin was much less organized in discrete clusters and had more dispersed organization patterns (right). 2D-STORM imaging data demonstrates that signals of all three TJ proteins are in close proximity (‘Gaussian visualization’ in which signal intensity correlates with localization precision). An inset with magnifications of each cluster (right images) demonstrates the very high molecular density of TJ proteins (‘Cross visualization’ shows all resolved signals where each single-molecule signal displays as a cross). Scale bars, 100 nm. Representative signal numbers are shown. n=40 capillaries of 4 wild-type pups. L – capillary lumen. b, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining of E12 and P9 cortical capillary cross-sections. Note that some claudin-5 clusters are coupled with ZO1 clusters (high magnification insets, arrows) while some are independent claudin-5 clusters (arrowhead). Scale bars, 1 µm and 100 nm in insets. c, Average density of P9 claudin-5 clusters that were coupled with ZO1 clusters was ?5-fold higher than independent claudin-5 clusters. The average density of E12 claudin-5 clusters was similar regardless of proximity to ZO1 clusters, and was low compared to P9 independent claudin-5 clusters. n=40 clusters from 11 capillaries and 43 clusters from 11 capillaries (of 3 embryos/pups, P9 and E12 respectively). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)" + } ], + "type" : "directory" + }, { + "path" : "fig 5", + "size" : 23503480, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 5: Total cellular claudin-5 abundance does not correlate with BBB restrictive properties. Quantifications of claudin-5 levels and clustering properties along developmental BBB maturation a, dSTORM (right) compared to epi-fluorescent images (left) of claudin-5 immunostaining in E12 and P9 cortical capillary cross-sections. Two distinct claudin-5 organizations could be observed; discrete clusters (arrowheads) and a more defused claudin-5 appearance composed of many small clusters with relatively small gaps between them, evident only in E12 capillaries (arrow, see Extended Data Fig. S1a for further analysis). Scale bars, 1 µm. b, Claudin-5 clustering-properties analysis showed that there were about 2.6 times more discrete clusters per capillary at E12 than at P9 (a set of 20 capillaries of each age). Distribution of claudin-5 clusters area in E12 capillaries was skewed towards smaller clusters and the average cluster area was slightly smaller in E12 with no dramatic difference between the distributions (average of 0.309 µm2 (E12) vs. 0.3413 µm2 (P9). There was no dramatic difference in the distribution of signals per cluster or signal densities between the two groups (see Fig. S1b). n=3 pups/embryos, 20 capillaries, 657 clusters (E12) and 246 clusters (P9). Data are mean±s.e.m. c, Quantifications of total cellular claudin-5 per capillary cross section shows a shift towards lower claudin-5 levels and smaller capillary diameter in P9 than in E12 vasculature. Capillary diameter was significantly smaller (5.9±0.39 µm (P9), 11.1±0.47µm (E12)), total number of claudin-5 signals per capillary was significantly lower (3,590±372 (P9), 14,341±1,257 (E12)). d, Normalizing the total number of signals per capillary to its diameter shows the average claudin-5 cellular abundance is significantly lower at P9. n=25 capillaries (E12) and 27 capillaries (P9) of 3 embryos/pups. Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + }, { + "path" : "fig 4", + "size" : 48910371, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 4: Claudin-5 exhibits clustered organization in cortical capillaries. Imaging in cortical fixed tissue sections of post-natal day 9 mice. a, Low magnification view of claudin-5 staining imaged by epi-fluorescent microscopy showing vascular fragments in cross-sections (arrows) or in sagittal-sections (arrowheads, scale bar, 50 µm). b, Claudin-5 exhibits clustered organization in vivo; dSTORM (right) compared to epi-fluorescent images (left) of claudin-5 immunostaining in P9 cortical capillary cross-section (upper panel) or sagittal-section (lower panel) (scale bars, 1 µm), n>30 capillaries." + } ], + "type" : "directory" + }, { + "path" : "fig 3", + "size" : 48541160, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 3: Claudin-5 signals in dSTORM imaging are exclusively localized to vascular structures. dSTORM imaging in cortical fixed tissue sections of post-natal day 9 mice. a, Illustration of a vascular structure with cross versus sagittal section directions, and the projected orientation of endothelial cells contact points. b, Claudin-5 staining (green) together with fluorescent circulating tracers (10 kDa dextran, and ?443 Dalton sulfo-NHS-biotin, magenta) are used to demarcate sagittal views of elongated vessels (dashed line, Scale bars, 1 µm). c, Staining for claudin-5 (green) together with the endothelial-specific transcription factor ERG (gray) showing capillary cross and sagittal sections (Scale bars, 1 µm). L – capillary lumen, N – endothelial nucleus. n>30 capillaries." + } ], + "type" : "directory" + }, { + "path" : "fig 2", + "size" : 190806164, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 2: Changes in nano-scale architecture correlates with tight junction function. Enhanced TJ function is accompanied by formation of smaller and denser clusters of claudin-5. a, Enhanced TJ function demonstrated by increase in TEER, along the first days of induced human brain microvascular endothelial-like cell (iBMEC) culture (n=4 experiments/12 inserts. TEER here shows data of a representative experiment. For average change in TEER across all experiments see Supplementary Figure S1b. n=4 inserts for permeability). b, Enhanced TJ function demonstrated by reduced permeability to sodium fluorescein (T0 represents low TEER and T1 represents high TEER states, n=4 inserts). Data are mean ± SD. *** P<0.0003 (two tailed pair t-test). c, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining in iBMEC confluent monolayers. Claudin-5 signals are concentrated in discrete and short foci at both time points. Scale bar, 1 µm. d, Examples of dSTORM imaging simulation of claudin-5 in iBMECs used for quantifications of clustering properties (produced by a custom clustering Matlab code, see methods for details). Cluster pattern visualization showing all points that belong to the same cluster with the same identifying color. e, Quantifications of claudin-5 clustering properties showed a shift towards smaller clusters with more claudin-5 signals per cluster along the improvement in TJ function. f, Average claudin-5 cluster density more than doubled (from 14,341 to 33,141 signals/µm2) with the improvement in TJ function (n=90 clusters (in lower TEER) and 278 clusters (in higher TEER) in triplicate cultures of two independent experiments). Data are mean ± s.e.m. *P < 0.01 (two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + }, { + "path" : "fig 1", + "size" : 104960161, + "attributes" : [ { + "name" : "Description", + "value" : "Fig. 1: Super-resolution microscopy of endothelial tight junctions. In vitro process of TJ maturation is accompanied by TJ architectural changes characterized by the formation of smaller, denser and more discrete clusters of TJ proteins. a, Epi-fluorescent imaging of claudin-5 (green) and ZO1 (red) immunostaining of bEND.3 cells in indicated time points after the cultures reached confluence state. Note translocation of claudin-5 from cytoplasmic localizations into continuous lines around the boundaries of the cells (known as ‘strands’), along the in vitro maturation process. Scale bars, 10 µm and 5 µm in insets. b, dSTORM imaging (Gaussian visualization) of claudin-5 (green) and ZO1 (red) immunostaining of bEND.3 cells confluent monolayers. TJ proteins form bead-like structures, especially in the super-confluence state. Claudin-5 signals are more concentrated in discrete and shorter foci (flanking ZO1 signals, arrowheads, right) than in the post-confluence state (arrows, left). During maturation TJ proteins translocate from different cellular locations (left) almost exclusively into the lateral cell membranes (right). Scale bar, 1 µm. c, Examples of dSTORM imaging simulation of claudin-5 in bEND.3 cells used for quantifications of clustering properties (produced by a custom clustering Matlab code, see methods for details). Signals were defined to be clustered if their 2D location was smaller than 70 nm threshold distance. Cluster pattern visualization showing all points that belong to the same cluster with the same identifying color. d, Quantifications of claudin-5 clustering properties showed a shift towards smaller clusters with more claudin-5 signals per cluster at the super-confluence state. Clusters with higher numbers of signals were more abundant at this late state, especially in clusters with area smaller than 0.3 µm2. e, Average claudin-5 cluster density was ?4-fold higher at the super-confluence state than in the post-confluence state (n=183 clusters (post-confluence) and 281 clusters (super-confluence) in 5 independent experiments). Data are mean±s.e.m. *P < 0.05 (Two tailed Mann–Whitney U-test)." + } ], + "type" : "directory" + } ], + "links" : [ { + "url" : "https://www.biorxiv.org/content/10.1101/2021.08.12.456150v1.article-info", + "attributes" : [ { + "name" : "Description", + "value" : "pre print" + } ] + } ], + "subsections" : [ { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ayal Ben zvi" + }, { + "name" : "E-mail", + "value" : "ayalb@ekmd.huji.ac.il" + }, { + "name" : "ORCID", + "value" : "0000-0003-4012-7789" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Ron Dzikowski" + }, { + "name" : "E-mail", + "value" : "rond@ekmd.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o5", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Gad D. Vatine" + }, { + "name" : "E-mail", + "value" : "vatineg@bgu.ac.il" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Eilon Sherman" + }, { + "name" : "E-mail", + "value" : "eilonsher@gmail.com" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Britta Engelhardt" + }, { + "name" : "E-mail", + "value" : "britta.engelhardt@tki.unibe.ch" + }, { + "name" : "affiliation", + "value" : "o4", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : " Urban Deutsch" + }, { + "name" : "E-mail", + "value" : " urban.deutsch@tki.unibe.ch" + }, { + "name" : "affiliation", + "value" : "o4", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Meshi Zorsky" + }, { + "name" : "E-mail", + "value" : "meshiz@post.bgu.ac.il" + }, { + "name" : "affiliation", + "value" : "o3", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Oren Yakovian" + }, { + "name" : "E-mail", + "value" : "oren.yakovian@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o2", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Batia Bell" + }, { + "name" : "E-mail", + "value" : "batia.bell@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Shira Anzi" + }, { + "name" : "E-mail", + "value" : "shira.anzi@mail.huji.ac.il" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "type" : "author", + "attributes" : [ { + "name" : "Name", + "value" : "Esther Sasson" + }, { + "name" : "E-mail", + "value" : "esti.sasson@mail.huji.ac.il" + }, { + "name" : "ORCID", + "value" : "0000-0001-7156-1516" + }, { + "name" : "affiliation", + "value" : "o1", + "reference" : true + } ] + }, { + "accno" : "o1", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel" + } ] + }, { + "accno" : "o2", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Racah Institute of Physics, The Hebrew University, Jerusalem 9190401, Israel" + } ] + }, { + "accno" : "o3", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "The Department of Physiology and Cell Biology, Faculty of Health Sciences, The Regenerative Medicine and Stem Cell (RMSC) research Center and the Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel" + } ] + }, { + "accno" : "o4", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Theodor Kocher Institute, University of Bern, Bern, Switzerland" + } ] + }, { + "accno" : "o5", + "type" : "organisation", + "attributes" : [ { + "name" : "Name", + "value" : "Department of Microbiology and Molecular Genetics, The Kuvin Center for the Study of Infectious and Tropical Diseases, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel." + } ] + } ] + }, + "type" : "submission" +} \ No newline at end of file