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Record W4376869889 · doi:10.1126/sciadv.adf2982

Mice with humanized livers reveal the role of hepatocyte clocks in rhythmic behavior

2023· article· en· W4376869889 on OpenAlexaff
Anne-Sophie Delbès, Mar Quiñones, Cédric Gobet, Julien Castel, R Denis, Jérémy Berthelet, Benjamin D. Weger, Étienne Challet, Aline Charpagne, Sylviane Métairon, Julie Piccand, Marine R.-C. Kraus, B Rohde, John Bial, Elizabeth M. Wilson, Lise‐Lotte Vedin, Mirko E. Minniti, Matteo Pedrelli, Paolo Parini, Frédéric Gachon, Serge Luquet

Bibliographic record

VenueScience Advances · 2023
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsCapilano University
Fundersnot available
KeywordsCircadian rhythmCircadian clockSuprachiasmatic nucleusRhythmBiologyLight effects on circadian rhythmCLOCKBacterial circadian rhythmsNeurosciencePeriod (music)Oscillating geneHepatocyteCell biologyEndocrinologyInternal medicineMedicineGenetics

Abstract

fetched live from OpenAlex

The synchronization of circadian clock depends on a central pacemaker located in the suprachiasmatic nuclei. However, the potential feedback of peripheral signals on the central clock remains poorly characterized. To explore whether peripheral organ circadian clocks may affect the central pacemaker, we used a chimeric model in which mouse hepatocytes were replaced by human hepatocytes. Liver humanization led to reprogrammed diurnal gene expression and advanced the phase of the liver circadian clock that extended to muscle and the entire rhythmic physiology. Similar to clock-deficient mice, liver-humanized mice shifted their rhythmic physiology more rapidly to the light phase under day feeding. Our results indicate that hepatocyte clocks can affect the central pacemaker and offer potential perspectives to apprehend pathologies associated with altered circadian physiology.

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 score0.020
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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

Citations19
Published2023
Admission routes1
Has abstractyes

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