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Record W3194288891 · doi:10.1016/j.rvsc.2021.08.014

Proteomic analysis of the secretome of equine herpesvirus-1 infected rabbit kidney cells

2021· article· en· W3194288891 on OpenAlexfundno aff
Wojciech Rożek, Małgorzata Kwaśnik, Agata Malinowska, Karol Stasiak, Magdalena Larska, J. Rola

Bibliographic record

VenueResearch in Veterinary Science · 2021
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsnot available
FundersMinisterstwo Edukacji i NaukiUniversity of Alberta
KeywordsEndoplasmic reticulumSecretionBiologyCalreticulinPathogenesisDownregulation and upregulationSecretory proteinWestern blotVirologyCell biologyImmunologyGeneGenetics

Abstract

fetched live from OpenAlex

Herpesviruses are the main cause of abortions and respiratory or neurological disorders in horses. Various disease patterns are suspected to be associated with the A2254G point mutation in the DNA polymerase sequence (ORF30) of the herpesvirus genome, although the importance of this link is still under debate. Based on a label-free quantitative proteomic analysis, the differences in the secretion of some host proteins between rabbit kidney cells infected with A2254 and cells of the same line infected with G2254 equine herpesvirus 1 (EHV-1) strains were identified. In both groups, downregulation of proteins involved in insulin growth factor and extracellular matrix pathway regulation was observed. Among 12 proteins with increased secretion, 8 were regulated only in G2254 EHV-1 infection. Those were endoplasmic reticulum chaperones with calcium binding properties, related to unfolded protein response and mitochondria. It was presumed that the secretion of proteins such as calreticulin, Hspa5 or endoplasmin may contribute to the pathogenesis of EHV-1 infection.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.421
Teacher spread0.319 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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