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Record W4312094040 · doi:10.1017/s1092852922001195

The concept of “metabolic jet lag” in the pathophysiology of bipolar disorder: implications for research and clinical care

2022· review· en· W4312094040 on OpenAlexafffund
Elena Koning, Alexandra McDonald, Alexander Bambokian, Fabiano A. Gomes, Jacob Vorstman, Michael Berk, Jennifer Fabe, Roger S. McIntyre, Roumen Milev, Rodrigo B. Mansur, Elisa Brietzke

Bibliographic record

VenueCNS Spectrums · 2022
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsProvidence Health CareQueen's UniversityMcMaster UniversityMcMaster Children's HospitalUniversity of TorontoBrain and Cognition Discovery Foundation
FundersNational Health and Medical Research CouncilQueen's University
KeywordsCircadian rhythmBipolar disorderChronobiologyMedicinePsychologyBiologyNeurosciencePsychiatryMood

Abstract

fetched live from OpenAlex

Bipolar disorder (BD) is a potentially chronic mental disorder marked by recurrent depressive and manic episodes, circadian rhythm disruption, and changes in energetic metabolism. "Metabolic jet lag" refers to a state of shift in circadian patterns of energy homeostasis, affecting neuroendocrine, immune, and adipose tissue function, expressed through behavioral changes such as irregularities in sleep and appetite. Risk factors include genetic variation, mitochondrial dysfunction, lifestyle factors, poor gut microbiome health and abnormalities in hunger, satiety, and hedonistic function. Evidence suggests metabolic jet lag is a core component of BD pathophysiology, as individuals with BD frequently exhibit irregular eating rhythms and circadian desynchronization of their energetic metabolism, which is associated with unfavorable clinical outcomes. Although current diagnostic criteria lack any assessment of eating rhythms, technological advancements including mobile phone applications and ecological momentary assessment allow for the reliable tracking of biological rhythms. Overall, methodological refinement of metabolic jet lag assessment will increase knowledge in this field and stimulate the development of interventions targeting metabolic rhythms, such as time-restricted eating.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.141
GPT teacher head0.472
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2022
Admission routes2
Has abstractyes

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