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Record W3213524116 · doi:10.21203/rs.3.rs-311000/v1

Single-cell immunophenotyping of the fetal immune response to maternal SARS-CoV-2 infection in late gestation

2021· preprint· en· W3213524116 on OpenAlexaff
Juan D. Matute, Benjamin Finander, David Pépin, Xinbin Ai, Neal P. Smith, Jonathan Z. Li, Andrea G. Edlow, Alexandra Chloé Villani, Paul H. Lerou, Brian T. Kalish

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Neurological Disorders and Stroke
KeywordsImmunophenotypingGestationFetusImmune systemImmunologyPregnancyMedicineObstetricsBiologyAntigenGenetics

Abstract

fetched live from OpenAlex

During the COVID-19 pandemic, thousands of pregnant women have been infected with SARS-CoV-2. The implications of maternal SARS-CoV-2 infection on fetal and childhood well-being are unknown. We aimed to characterize the fetal immune response to maternal SARS-CoV-2 infection. We performed single-cell RNA sequencing and T-cell receptor (TCR) sequencing on cord blood mononuclear cells (CBMC) from newborns of mothers infected with SARS-CoV-2 in the third-trimester (cases) or without SARS-CoV-2 infection. We identified widespread gene expression changes in CBMC from cases, including upregulation of interferon-stimulated genes and Major Histocompatibility Complex genes in CD14 + monocytes; transcriptional changes suggestive of activation of plasmacytoid dendritic cells, and activation and exhaustion of NK cells and CD8 + T-cells. Lastly, we observed fetal TCR repertoire expansion in cases. As none of the infants were infected with SARS-CoV-2, our results suggest that SARS-CoV-2 maternal infection might modulate the fetal immune system in the absence of vertical transmission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.413
Teacher spread0.325 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2021
Admission routes1
Has abstractyes

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