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Record W4406940291 · doi:10.1101/2025.01.28.635321

Endurance training restores ageing-impaired lysosomal biogenesis factors in rest and response to acute exercise in rat skeletal muscle

2025· preprint· en· W4406940291 on OpenAlexaff
Hamid Rajabi, Benyamin Askari, David C. Clarke

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEndurance trainingAgeingRest (music)Training (meteorology)Skeletal muscleBiogenesisMedicineInternal medicinePhysical medicine and rehabilitationEndocrinologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Purpose Lysosomes, crucial for autophagy, play a pivotal role in cellular processes influenced by exercise. This study investigates the impact of ageing on lysosomal function, focusing on Transcription Factor E3 and its regulators, mTORC1 and Calcineurin, emphasizing their response and adaptation to endurance training Methods Twenty-five male Sprague-Dawley rats were categorised into Young (2 months), Aged sedentary and Aged sedentary single session (18 months), Aged long-term trained, and Aged trained-single session (17 months). Changes in variables were explored concerning sarcopenia by Soleus muscle fibre diameter and number measured via Eosin & Hematoxylin, phosphorylated and total TFE3 protein levels via western blot, mTORC1 and Calcineurin mRNA levels via real-time PCR. Results Ageing occurred with increased pTFE3/TFE3 total protein (BF=579), declined mTORC1 mRNA (BF=3.99), and muscle diameter (BF=87), signifying sarcopenia and potential contributors. Conversely, Calcineurin mRNA (BF=0.67) and muscle fibre number (BF=0.31) remained unaltered during ageing. Exercise elicited acute responses, reducing pTFE3/TFE3 total protein (BF=306), elevating mTORC1 (BF=1.57) and Calcineurin mRNA levels (BF=3.19). Three weeks of endurance training further decreased resting pTFE3/TFE3 total protein (BF=174) while increasing Calcineurin mRNA (BF=12) and muscle fibre diameter (BF=126), with no changes in mTORC1 mRNA levels (BF=0.46) and muscle fibre number. Post-exercise, trained rats sustained decreased pTFE3/TFE3 total protein (BF=56) and elevated mTORC1 mRNA (BF=1.16). Conclusion This study underscores the involvement of TFE3, MTORC1, and Calcineurin in sarcopenia, proposing endurance training as an effective strategy to mitigate age-related changes and enhance muscle function in aged rats. Additionally, it suggests impairments in TFE3 possibly contribute to sarcopenia. key point Given the pivotal role lysosomes play in multiple homeostatic processes, investigating mTORC1, Calcineurin, and TFE3, an overlooked lysosome biogenesis factor involved in the metabolic effects of exercise, could help understand the metabolic state of sarcopenia and the role exercise plays. Through eosin & hematoxylin, western blotting and real-time PCR, we found Ageing results in sarcopenia, reduced TFE3 activity and mTORC1 gene expression. We saw a single bout of Endurance training elicited a response by increasing TFE3 protein activation, mTORC1, and Calcineurin gene expression, which is directed to improved sarcopenia. Three weeks of endurance training improved sarcopenia and was accompanied by elevated resting levels of TFE3 protein activation, and Calcineurin gene expression. Endurance training was still able to elicit post exercise response in TFE3 protein activation, and Calcineurin gene expression. Endurance training is a beneficial for sarcopenia, and TFE3 protein is a major player in inducing its effects.

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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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