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Record W3095806137 · doi:10.1161/res.127.suppl_1.463

Abstract 463: Circadian <i>Clock</i> Disruption Promotes Cardiac Cell Death During Hypoxic Injury

2020· article· en· W3095806137 on OpenAlexaff
Lorrie A. Kirshenbaum, Inna Rabinovich, Tami A. Martino

Bibliographic record

VenueCirculation Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsZeitgeberBiologyCircadian rhythmCircadian clockCell biologyCLOCKOscillating geneProgrammed cell deathMyocyteInternal medicineEndocrinologyApoptosisGeneticsMedicine

Abstract

fetched live from OpenAlex

Circadian rhythms play a fundamental role in cell metabolism and tissue homeostasis as well as in the diurnal oscillation of physiological processes such as blood pressure. Zeitgebers influence the circadian rhythms by serving as molecular switches for re-setting the intrinsic cellular clock. Herein, we show that oxygen is a Zeitgeber for the circadian rhythm and regulator of clock gene expression in cardiac myocytes. We further show that clock gene regulation promotes survival of cardiac myocytes by a mechanism that bi-directionally influences mitochondrial clearance and autophagy. Cardiac myocytes exhibited phasic oscillations in clock gene expression under basal conditions which was disrupted during hypoxia. This was accompanied by a marked time dependent decline in clock gene transcription that was maximal at ZT+18 and coincided with a reciprocal increase in mitochondrial clearance. Loss of function mutations of clock that disrupted nuclear localization or DNA binding to BMAL-1 promoted wide-spread cell death. Hence, the findings of the present study provide a novel signaling axis that operationally links hypoxia regulated clock gene expression and mitochondrial turn-over to cell survival.

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 score0.312
Threshold uncertainty score0.579

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 head0.053
GPT teacher head0.322
Teacher spread0.269 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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