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Record W4312064967 · doi:10.1038/s41514-022-00097-8

Multiple pathways promote microtubule stabilization in senescent intestinal epithelial cells

2022· article· en· W4312064967 on OpenAlexafffund
Siwei Chu, Ossama Moujaber, Serge Lemay, Ursula Stochaj

Bibliographic record

Venuenpj Aging · 2022
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsMcGill University Health CentreMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMicrotubuleCell biologySenescenceBiologyTubulinPhenotypeHomeostasisIntestinal epitheliumEpitheliumGeneticsGene

Abstract

fetched live from OpenAlex

Intestinal epithelial cells are critical for gastrointestinal homeostasis. However, their function declines during aging. The aging-related loss of organ performance is largely driven by the increase in senescent cells. To date, the hallmarks and molecular mechanisms related to cellular senescence are not fully understood. Microtubules control epithelial functions, and we identified microtubule stabilization as a phenotypic marker of senescent intestinal epithelial cells. The senescence inducer determined the pathway to microtubule stabilization. Specifically, enhanced microtubule stability was associated with α-tubulin hyperacetylation or increased abundance of the microtubule-binding protein tau. We show further that overexpression of MAPT, which encodes tau, augmented microtubule stability in intestinal epithelial cells. Notably, pharmacological microtubule stabilization was sufficient to induce cellular senescence. Taken together, this study provides new insights into the molecular mechanisms that control epithelial cell homeostasis. Our results support the concept that microtubule stability serves as a critical cue to trigger intestinal epithelial cell senescence.

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 score0.043
Threshold uncertainty score0.674

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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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