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Record W4396854298 · doi:10.7554/elife.96584

Microtubule-dependent orchestration of centriole amplification in brain multiciliated cells

2024· preprint· en· W4396854298 on OpenAlexaff
Amélie-Rose Boudjema, Rémi Balagué, Cayla E Jewett, Gina M LoMastro, Olivier Mercey, Adel Al Jord, Marion Faucourt, Alexandre Schaeffer, Camille Noûs, Nathalie Delgehyr, Andrew J. Holland, Nathalie Spassky, Alice Meunier

Bibliographic record

VenueeLife · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsSeagen (Canada)
FundersCentre National de la Recherche ScientifiqueFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la Recherche
KeywordsOrchestrationCentrioleMicrotubuleCiliumCell biologyBiologyArt

Abstract

fetched live from OpenAlex

Multiciliated cell (MCC) differentiation is a calibrated version of the canonical cell cycle. The MCC cell cycle variant sustains amplification of centrioles for the nucleation of dozens of motile cilia, while avoiding cell division. In this study, we show that the MCC cell cycle variant is an accelerated version of the canonical cell cycle, which superposes two cycles of centriole biogenesis, in order to obtain multiple mature centrioles within a single -instead of double- cell cycle iteration. We further show that the precocious maturation of amplified procentrioles is even determinant for their spatial self-organization, disengagement and apical migration for cilia nucleation. Our findings collectively suggest that the decomposition of centriole biogenesis over two cycle iterations in dividing cells may have been adopted to ensure the growth of a solitary primary cilium, and exemplify how minimal deviations of the canonical cell cycle allow MCC progenitors to both amplify, and accelerate, centriole biogenesis for vital motile ciliogenesis.

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 score0.002
Threshold uncertainty score0.004

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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