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Record W2039596629 · doi:10.1139/h11-076

Skeletal muscle and beyond: the role of exercise as a mediator of systemic mitochondrial biogenesis

2011· review· en· W2039596629 on OpenAlexaffvenue
Jonathan P. Little, Adeel Safdar, Carley R. Benton, David C. Wright

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2011
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of GuelphMcMaster UniversityOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMitochondrial biogenesisSkeletal muscleBiogenesisMediatorContext (archaeology)MitochondrionBiologyAdipose tissueOrganelle biogenesisCell biologyFunction (biology)EndocrinologyNeuroscienceBioinformaticsBiochemistry

Abstract

fetched live from OpenAlex

It has been known for more than 4 decades that exercise causes increases in skeletal muscle mitochondrial enzyme content and activity (i.e., mitochondrial biogenesis). Increasing evidence now suggests that exercise can induce mitochondrial biogenesis in a wide range of tissues not normally associated with the metabolic demands of exercise. Perturbations in mitochondrial content and (or) function have been linked to a wide variety of diseases, in multiple tissues, and exercise may serve as a potent approach by which to prevent and (or) treat these pathologies. In this context, the purpose of this review is to highlight the effects of exercise, and the underlying mechanisms therein, on the induction of mitochondrial biogenesis in skeletal muscle, adipose tissue, liver, brain, and kidney.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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 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

Citations62
Published2011
Admission routes2
Has abstractyes

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