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Record W4281766760 · doi:10.3390/v14061218

Non-Productive Infection of Glial Cells with SARS-CoV-2 in Hamster Organotypic Cerebellar Slice Cultures

2022· article· en· W4281766760 on OpenAlexafffund
Lise Lamoureux, Babu V. Sajesh, Jessy A. Slota, Sarah J. Medina, Matthew Mayor, Kathy L. Frost, Bryce M. Warner, Kathy Manguiat, Heidi Wood, Darwyn Kobasa, Stephanie A. Booth

Bibliographic record

VenueViruses · 2022
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersPublic Health Agency of Canada
KeywordsVirologyBiologyHamsterPathogenesisViral replicationPhenotypeVirusImmunologyGeneticsGeneMolecular biology

Abstract

fetched live from OpenAlex

The numerous neurological syndromes associated with COVID-19 implicate an effect of viral pathogenesis on neuronal function, yet reports of direct SARS-CoV-2 infection in the brain are conflicting. We used a well-established organotypic brain slice culture to determine the permissivity of hamster brain tissues to SARS-CoV-2 infection. We found levels of live virus waned after inoculation and observed no evidence of cell-to-cell spread, indicating that SARS-CoV-2 infection was non-productive. Nonetheless, we identified a small number of infected cells with glial phenotypes; however, no evidence of viral infection or replication was observed in neurons. Our data corroborate several clinical studies that have assessed patients with COVID-19 and their association with neurological involvement.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

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