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Record W4308450590 · doi:10.1016/j.xpro.2022.101872

Protocol for SARS-CoV-2 infection of kidney organoids derived from human pluripotent stem cells

2022· article· en· W4308450590 on OpenAlexafffund
Elena Garreta, Daniel Moya‐Rull, Megan L. Stanifer, Vanessa Monteil, Patricia Prado, Andrés Marco, Carolina Tarantino, Maria Gallo, Gustav Jonsson, Astrid Hagelkrüys, Alì Mirazimi, Steeve Boulant, Josef Penninger, Núria Montserrat

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsUniversity of British Columbia
FundersH2020 European Research CouncilFP7 Coordination of Research ActivitiesHorizon 2020 Framework ProgrammeInstitute for Bioengineering of CataloniaEIT HealthCanadian Institutes of Health ResearchFundación BBVAFundació la Marató de TV3Innovative Medicines InitiativeEuropean CommissionT. Von Zastrow FoundationInnovative Health InitiativeVetenskapsrådetGeneralitat de CatalunyaInstituto de Salud Carlos IIIAustrian Science FundEuropean Research CouncilMinisterio de Ciencia, Innovación y UniversidadesÖsterreichischen Akademie der WissenschaftenCollege of Medicine, University of FloridaEuropean Federation of Pharmaceutical Industries and Associations
KeywordsOrganoidInduced pluripotent stem cellSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakHuman Induced Pluripotent Stem CellsVirologyBiologyMedicineCell biologyPathologyGeneticsEmbryonic stem cellInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

This protocol presents the use of SARS-CoV-2 isolates to infect human kidney organoids, enabling exploration of the impact of SARS-CoV-2 infection in a human multicellular in vitro system. We detail steps to generate kidney organoids from human pluripotent stem cells (hPSCs) and emulate a diabetic milieu via organoids exposure to diabetogenic-like cell culture conditions. We further describe preparation and titration steps of SARS-CoV-2 virus stocks, their subsequent use to infect the kidney organoids, and assessment of the infection via immunofluorescence. For complete details on the use and execution of this protocol, please refer to Garreta et al. (2022). 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0580.028

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.120
GPT teacher head0.435
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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