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Record W4386574271 · doi:10.1016/j.smhs.2023.09.001

Nrf2 modulates the benefits of evening exercise in type 2 diabetes

2023· review· en· W4386574271 on OpenAlexaff
Babatunde Fasipe, Ismail Laher

Bibliographic record

VenueSports Medicine and Health Science · 2023
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEveningCircadian rhythmMorningEndocrinologyInternal medicineType 2 diabetesDiabetes mellitusRhythmMedicineBiology

Abstract

fetched live from OpenAlex

Exercise has well-characterized therapeutic benefits in the management of type 2 diabetes mellitus (T2DM). Most of the beneficial effects of exercise arise from the impact of nuclear factor erythroid 2 related factor-2 (Nrf2) activation of glucose metabolism. Nrf2 is an essential controller of cellular anti-oxidative capacity and circadian rhythms. The circadian rhythm of Nrf2 is influenced by circadian genes on its expression, where the timing of exercise effects the activation of Nrf2 and the rhythmicity of Nrf2 and signaling, such that the timing of exercise has differential physiological effects. Exercise in the evening has beneficial effects on diabetes management, such as lowering of blood glucose and weight. The mechanisms responsible for these effects have not yet been associated with the influence of exercise on the circadian rhythm of Nrf2 activity. A better understanding of exercise-induced Nrf2 activation on Nrf2 rhythm and signaling can improve our appreciation of the distinct effects of morning and evening exercise. This review hypothesizes that activation of Nrf2 by exercise in the morning, when Nrf2 level is already at high levels, leads to hyperactivation and decrease in Nrf2 signaling, while activation of Nrf2 in the evening, when Nrf2 levels are at nadir levels, improves Nrf2 signaling and lowers blood glucose levels and increases fatty acid oxidation. Exploring the effects of Nrf2 activators on rhythmic signaling could also provide valuable insights into the optimal timing of their application, while also holding promise for timed treatment of type 2 diabetes.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.143
GPT teacher head0.390
Teacher spread0.247 · 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 designOther design
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

Citations9
Published2023
Admission routes1
Has abstractyes

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