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Record W4407678948 · doi:10.1002/rmv.70023

Nuclear Factor of Activated T Cells Signalling and Viral Pathogens: A Dynamic Cross‐Talk

2025· review· en· W4407678948 on OpenAlexaff
Sayyad Khanizadeh, Kiana Shahzamani, Mohsen Nakhaie, Ali Pormohammad, Gholamreza Talei, Habibollah Mirzaei

Bibliographic record

VenueReviews in Medical Virology · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNFATTranscription factorCell biologyBiologyCalcineurinHedgehog signaling pathwaySignal transductionGeneticsTransplantationMedicine

Abstract

fetched live from OpenAlex

The signalling pathway of the nuclear factor of activated T cells (NFAT) plays a crucial role in regulating various cellular processes such as cardiac hypertrophy, adipose differentiation, chondrocyte development, angiogenesis, inflammation, immune system activation, organogenesis, cancer cell migration, differentiation and survival. In addition, the NFAT signalling pathway acts as a key regulator of viral infections. Accordingly, it is plausible to assume that viruses have developed different mechanisms to manipulate this pathway to promote their pathogenicity. Viral pathogens can either inhibit or upregulate NFAT signalling through various mechanisms, including modulation of calcineurin activity, calcineurin/NFAT interaction, NFAT stability and translocation, NFAT-DNA-binding activity and NFAT-transcription partner interaction. Therefore, the NFAT signalling pathway can be regarded as a promising target to control viral infections. This review discusses the dynamic interactions between the NFAT signalling pathway and viral pathogens. It also addresses several drugs and agents that can target the NFAT signalling pathway at different levels to control viral infections.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.021
GPT teacher head0.343
Teacher spread0.322 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2025
Admission routes1
Has abstractyes

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