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Record W2901935922 · doi:10.1016/j.stemcr.2018.10.010

Intestinal Stem Cells Exhibit Conditional Circadian Clock Function

2018· article· en· W2901935922 on OpenAlexafffund
Kathyani Parasram, Nathaniel James Bernardon, Maha Hammoud, Hanna Chang, Li He, Norbert Perrimon, Phillip Karpowicz

Bibliographic record

VenueStem Cell Reports · 2018
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaHoward Hughes Medical Institute
KeywordsBiologyCircadian rhythmStem cellCircadian clockCell biologyWnt signaling pathwaySignal transductionNeuroscience

Abstract

fetched live from OpenAlex

The circadian clock is a molecular pacemaker that produces 24-hr physiological cycles known as circadian rhythms. How the clock regulates stem cells is an emerging area of research with many outstanding questions. We tested clock function in vivo at the single cell resolution in the Drosophila intestine, a tissue that is exquisitely sensitive to environmental cues and has circadian rhythms in regeneration. Our results indicate that circadian clocks function in intestinal stem cells and enterocytes but are downregulated during enteroendocrine cell differentiation. Drosophila intestinal cells are principally synchronized by the photoperiod, but intestinal stem cell clocks are highly responsive to signaling pathways that comprise their niche, and we find that the Wnt and Hippo signaling pathways positively regulate stem cell circadian clock function. These data reveal that intestinal stem cell circadian rhythms are regulated by cellular signaling and provide insight as to how clocks may be altered during physiological changes such as regeneration and aging.

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 score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.231
Teacher spread0.207 · 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

Citations49
Published2018
Admission routes2
Has abstractyes

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