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Record W2808077517 · doi:10.1128/jvi.00404-18

Axonal Transport Enables Neuron-to-Neuron Propagation of Human Coronavirus OC43

2018· article· en· W2808077517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Virology · 2018
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of TorontoInstitut National de la Recherche Scientifique
FundersInstitute of Infection and ImmunityCanadian Institutes of Health Research
KeywordsBiologyNeuroscienceOlfactory bulbCoronavirusNeuronVirologyCentral nervous systemCoronavirus disease 2019 (COVID-19)DiseasePathologyMedicine

Abstract

fetched live from OpenAlex

Coronaviruses may invade the CNS, disseminate, and participate in the induction of neurological diseases. Their neuropathogenicity is being increasingly recognized in humans, and the presence and persistence of human coronaviruses (HCoV) in human brains have been proposed to cause long-term sequelae. Using our mouse model relying on natural susceptibility to HCoV OC43 and neuronal cell cultures, we have defined the most relevant path taken by HCoV OC43 to access and spread to and within the CNS toward the brain stem and spinal cord and studied in cell culture the underlying modes of intercellular propagation to better understand its neuropathogenesis. Our data suggest that axonal transport governs HCoV OC43 egress in the CNS, leading to the exacerbation of neuropathogenesis. Exploiting knowledge on neuroinvasion and dissemination will enhance our ability to control viral infection within the CNS, as it will shed light on underlying mechanisms of neuropathogenesis and uncover potential druggable molecular virus-host interfaces.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.507
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.379
Teacher spread0.313 · 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