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Record W4283265571 · doi:10.1101/2022.06.20.496837

Exercise preserves fitness capacity during aging through AMPK and mitochondrial dynamics

2022· preprint· en· W4283265571 on OpenAlexaff
Juliane C. Campos, Luiz H. M. Bozi, Annika Traa, Alexander M. van der Bliek, Jeremy M. Van Raamsdonk, T. Keith Blackwell, Julio Cesar Batista Ferreira

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institutes of HealthCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoHarvard T.H. Chan School of Public HealthFundação de Amparo à Pesquisa do Estado de São PauloJoslin Diabetes Center
KeywordsAMPKMitochondrial fissionMitochondrial biogenesismitochondrial fusionMitochondrionMitochondrial DNABiologyCell biologyMFN2GeneticsProtein kinase APhosphorylationGene

Abstract

fetched live from OpenAlex

Abstract Exercise is a nonpharmacological intervention that improves health during aging, and a valuable tool in the diagnostics of aging-related diseases. In muscle, exercise transiently alters mitochondrial functionality and metabolism. Mitochondrial fission and fusion are critical effectors of mitochondrial plasticity, which allows a fine-tuned regulation of organelle connectiveness, size and function. Here we have investigated the role of mitochondrial dynamics during exercise in the genetically tractable model Caenorhabditis elegans . We show that in body wall muscle a single exercise session induces a cycle of mitochondrial fragmentation followed by fusion after a recovery period, and that daily exercise sessions delay the mitochondrial fragmentation and fitness capacity decline that occur with aging. The plasticity of this mitochondrial dynamics cycle is essential for fitness capacity and its enhancement by exercise training. Surprisingly, among longevity-promoting mechanisms we analyzed, constitutive activation of AMPK uniquely preserves fitness capacity during aging. As with exercise training, this benefit of AMPK is abolished by impairment of mitochondrial fission or fusion. AMPK is also required for fitness capacity to be enhanced by exercise, with our findings together suggesting that exercise enhances muscle function through AMPK regulation of mitochondrial dynamics. Our results indicate that mitochondrial connectivity and the mitochondrial dynamics cycle are essential for maintaining fitness capacity and exercise responsiveness during aging, and suggest that AMPK activation may recapitulate some exercise benefits. Targeting mechanisms to optimize mitochondrial fission and fusion balance, as well as AMPK activation, may represent promising strategies for promoting muscle function during aging. Significance Statement Exercise is a powerful anti-aging intervention. In muscle exercise remodels mitochondrial metabolism and connectiveness, but the role of mitochondrial dynamics in exercise responsiveness has remained poorly understood. Working in Caenorhabditis elegans , we find that the mitochondrial dynamics cycle of fission and fusion is critical for fitness capacity, that exercise delays an aging-associated decline in mitochondrial connectiveness and fitness capacity, and that the mitochondrial dynamics cycle is required for the latter benefit. AMPK, which regulates mitochondrial dynamics, is needed for exercise to maintain fitness capacity with age and can recapitulate this exercise benefit. Our data identify the mitochondrial dynamics cycle as an essential mediator of exercise responsiveness, and an entry point for interventions to maintain muscle function during aging.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.224
Teacher spread0.210 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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