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Record W4376630331 · doi:10.3390/cells12091332

Novel Therapeutic Target Critical for SARS-CoV-2 Infectivity and Induction of the Cytokine Release Syndrome

2023· article· en· W4376630331 on OpenAlexafffund
William Harless, B. M. Lewis, Bessi Qorri, Samar Abdulkhalek, Myron R. Szewczuk

Bibliographic record

VenueCells · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReceptorCell biologyInternalizationCytokineInfectivityNeuraminidaseChemistryBiologyEnzymeVirusImmunologyBiochemistry

Abstract

fetched live from OpenAlex

We discovered a novel therapeutic target critical for SARS-CoV-2, cellular infectivity and the induction of the cytokine release syndrome. Here, we show that the mammalian enzyme neuraminidase-1 (Neu-1) is part of a highly conserved signaling platform that regulates the dimerization and activation of the ACE2 receptors and the Toll-like receptors (TLRs) implicated in the cytokine release syndrome (CRS). Activated Neu-1 cleaves glycosylated residues that provide a steric hindrance to both ACE2 and TLR dimerization, a process critical to both viral attachment to the receptor and entry into the cell and TLR activation. Blocking Neu-1 inhibited ACE2 receptor dimerization and internalization, TLR dimerization and activation, and the expression of several key inflammatory molecules implicated in the CRS and death from ARDS. Treatments that target Neu-1 are predicted to be highly effective against infection with SARS-CoV-2, given the central role played by this enzyme in viral cellular entry and the induction of the CRS.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.301

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 head0.071
GPT teacher head0.365
Teacher spread0.295 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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