Exosomes as Mediators of the Systemic Adaptations to Endurance Exercise
Bibliographic record
Abstract
Habitual endurance exercise training is associated with multisystemic metabolic adaptations that lower the risk of inactivity-associated disorders such as obesity and type 2 diabetes mellitus (T2DM). Identification of complex systemic signaling networks responsible for these benefits are of great interest because of their therapeutic potential in metabolic diseases; however, specific signals that modulate the multisystemic benefits of exercise in multiple tissues and organs are only recently being discovered. Accumulated evidence suggests that muscle and other tissues have an endocrine function and release peptides and nucleic acids into the circulation in response to acute endurance exercise to mediate the multisystemic adaptations. Factors released from skeletal muscle have been termed myokines and we propose that the total of all factors released in response to endurance exercise (including peptides, nucleic acids, and metabolites) be termed, "exerkines." We propose that many of the exerkines are released within extracellular vesicles called exosomes, which regulate peripheral organ cross talk. Exosomes (30-140 nm) and larger microvesicles [MVs] (100-1000 nm) are subcategories of extracellular vesicles that are released into the circulation. Exosomes contain peptides and several nucleic acids (microRNA [miRNA], messenger RNA [mRNA], mitochondrial DNA [mtDNA]) and are involved in intercellular/tissue exchange of their contents. An acute bout of endurance exercise increases circulating exosomes that are hypothesized to mediate organ cross talk to promote systemic adaptation to endurance exercise. Further support for the role of exosomes (and possibly MVs) in mediating the systemic benefits of exercise comes from the fact that the majority of the previously reported myokines/exerkines are found in extracellular vesicles databases (Vesiclepedia and ExoCarta). We propose that exosomes isolated from athletes following exercise or exosomes bioengineered to incorporate one or many of known exerkines will be therapeutically useful in the treatment of obesity, T2DM, and other aging-associated metabolic disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".