MétaCan
Menu
Back to cohort
Record W2910361792 · doi:10.1128/jvi.02168-18

The Nonstructural NS1 Protein of Influenza Viruses Modulates <i>TP53</i> Splicing through Host Factor CPSF4

2019· article· en· W2910361792 on OpenAlexaff
Julia Dubois, Aurélien Traversier, Thomas Julien, Blandine Padey, Bruno Lina, Jean‐Christophe Bourdon, Virginie Marcel, Guy Boivin, Manuel Rosa‐Calatrava, Olivier Terrier

Bibliographic record

VenueJournal of Virology · 2019
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersRégion Auvergne-Rhône-AlpesUniversité Claude Bernard Lyon 1
KeywordsBiologyViral replicationInfluenza A virusCell biologyRNA splicingVirologyRegulatorVirusGeneticsGeneRNA

Abstract

fetched live from OpenAlex

Influenza A viruses (IAV) constitute a major public health issue, causing illness and death in high-risk populations during seasonal epidemics or pandemics. IAV are known to modulate cellular pathways to promote their replication and avoid immune restriction via the targeting of several cellular proteins. One of these proteins, p53, is a master regulator involved in a large panel of biological processes, including cell cycle arrest, apoptosis, or senescence. This “cellular gatekeeper” is also involved in the control of viral infections, and viruses have developed a wide diversity of mechanisms to modulate/hijack p53 functions to achieve an optimal replication in their hosts. Our group and others have previously shown that p53 activity is finely modulated by different multilevel mechanisms during IAV infection. Here, we characterized IAV nonstructural protein NS1 and the cellular factor CPSF4 as major partners involved in the IAV-induced modulation of the TP53 alternative splicing that was associated with a strong modulation of p53 activity and notably the p53-mediated antiviral response.

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 score0.003

Distilled classifier scores by category (both heads)

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

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 head0.062
GPT teacher head0.377
Teacher spread0.315 · 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

Citations40
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of VirologySame topicInfluenza Virus Research StudiesFrench-language works237,207