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Record W4200270895 · doi:10.1002/jmv.27554

The emerging roles of the CDK/cyclin complexes in antiviral innate immunity

2021· review· en· W4200270895 on OpenAlexaff
Chunfu Zheng, Yan‐Dong Tang

Bibliographic record

VenueJournal of Medical Virology · 2021
Typereview
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCyclin-dependent kinaseBiologyCell biologyInnate immune systemCyclinKinaseCell cycleImmunologyCellImmune systemBiochemistry

Abstract

fetched live from OpenAlex

More than 20 members of the human cyclin-dependent kinases (CDKs) family share the feature of being activated by cyclins. CDKs have been involved in diverse biological processes, such as cell cycle, transcription, DNA damage response, and apoptosis. If CDKs are not properly regulated, they can cause diseases like cancer. CDKs are Ser/Thr kinases that work with cyclins to control cell cycle progression. Various CDK-cyclin complexes phosphorylate particular target proteins and drive different cell cycle stages. Accumulating evidence demonstrated that CDKs play an essential role in the cell cycle; however, their roles in antiviral innate immunity are just emerging. This minireview summarizes how CDKs play their roles in antiviral innate immunity. Our goal is to draw attention to the involvement of CDKs in antiviral innate immunity, whether as separate entities or as components of CDK/cyclin complexes that have gotten less attention in the past.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch 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 score0.992
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.004
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 head0.031
GPT teacher head0.353
Teacher spread0.321 · 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

Citations29
Published2021
Admission routes1
Has abstractyes

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