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Record W2089056356 · doi:10.1126/science.1132430

Dissecting the Functions of the Mammalian Clock Protein BMAL1 by Tissue-Specific Rescue in Mice

2006· article· en· W2089056356 on OpenAlexaff
Erin L. McDearmon, Kush Patel, Caroline H. Ko, Jacqueline A. Walisser, Andrew Schook, Jason Chong, Lisa D. Wilsbacher, Eun Joo Song, Hee-Kyung Hong, Christopher A. Bradfield, Joseph S. Takahashi

Bibliographic record

VenueScience · 2006
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of Toronto
FundersNational Institute of Environmental Health SciencesNational Institute of Mental HealthHoward Hughes Medical Institute
KeywordsCircadian rhythmBiologyGenetically modified mouseTransgeneEndocrinologyCell biologyInternal medicinePeriod (music)Transcription factorCircadian clockGeneGeneticsMedicine

Abstract

fetched live from OpenAlex

The basic helix-loop-helix (bHLH)-Per-Arnt-Sim (PAS) domain transcription factor BMAL1 is an essential component of the mammalian circadian pacemaker. Bmal1-/- mice lose circadian rhythmicity but also display tendon calcification and decreased activity, body weight, and longevity. To investigate whether these diverse functions of BMAL1 are tissue-specific, we produced transgenic mice that constitutively express Bmal1 in brain or muscle and examined the effects of rescued gene expression in Bmal1-/- mice. Circadian rhythms of wheel-running activity were restored in brain-rescued Bmal1-/- mice in a conditional manner; however, activity levels and body weight were lower than those of wild-type mice. In contrast, muscle-rescued Bmal1-/- mice exhibited normal activity levels and body weight yet remained behaviorally arrhythmic. Thus, Bmal1 has distinct tissue-specific functions that regulate integrative 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 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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.240
Teacher spread0.224 · 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

Citations322
Published2006
Admission routes1
Has abstractyes

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