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Record W4200247047 · doi:10.3390/biomed1020013

Mast Cell Tryptase and Implications for SARS-CoV-2 Pathogenesis

2021· article· en· W4200247047 on OpenAlexafffund
Negar Karimi, Solmaz Morovati, Lily Chan, Christina Napoleoni, Yeganeh Mehrani, Byram W. Bridle, Khalil Karimi

Bibliographic record

VenueBioMed · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTryptaseProteasesPathogenesisImmunologyDegranulationCoronavirusMast cellAngiotensin-converting enzyme 2BiologyChymaseSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Innate immune systemVirologyReceptorDiseaseMedicineCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)Immune systemEnzymePathology

Abstract

fetched live from OpenAlex

Mast cells (MCs) are heterogenous innate leukocytes producing many inflammatory mediators during viral infections that can be protective or damaging to the host, as is seen in the infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for the coronavirus disease that was first identified in 2019 (COVID-19). MCs can sense viruses by diverse mechanisms. They express angiotensin-converting enzyme 2 (ACE2), known as the principal entry receptor for SARS-CoV-2, and tryptase that can promote SARS-CoV-2 infection. Tryptase is one of the most abundant serine proteases released by MCs during degranulation and is reported to have both beneficial and detrimental roles in respiratory diseases. Reviewed here are the potential roles of MC-derived tryptase during COVID-19, the implications it has in the pathogenesis of SARS-CoV-2, and the possibility of treating COVID-19 by targeting tryptase.

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 score0.471
Threshold uncertainty score0.286

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 head0.024
GPT teacher head0.256
Teacher spread0.232 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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