Running from stress: a perspective on the potential benefits of exercise-induced small extracellular vesicles for individuals with major depressive disorder
Bibliographic record
Abstract
Aerobic exercise promotes beneficial effects in the brain including increased synaptic plasticity and neurogenesis and regulates neuroinflammation and stress response via the hypothalamic-pituitary-adrenal axis. Exercise can have therapeutic effects for numerous brain-related pathologies, including major depressive disorder (MDD). Beneficial effects of aerobic exercise are thought to be mediated through the release of "exerkines" including metabolites, proteins, nucleic acids, and hormones that communicate between the brain and periphery. While the specific mechanisms underlying the positive effects of aerobic exercise on MDD have not been fully elucidated, the evidence suggests that exercise may exert a direct or indirect influence on the brain via small extracellular vesicles which have been shown to transport signaling molecules including "exerkines" between cells and across the blood-brain barrier (BBB). sEVs are released by most cell types, found in numerous biofluids, and capable of crossing the BBB. sEVs have been associated with numerous brain-related functions including neuronal stress response, cell-cell communication, as well as those affected by exercise like synaptic plasticity and neurogenesis. In addition to known exerkines, they are loaded with other modulatory cargo such as microRNA (miRNA), an epigenetic regulator that regulates gene expression levels. How exercise-induced sEVs mediate exercise dependent improvements in MDD is unknown. Here, we perform a thorough survey of the current literature to elucidate the potential role of sEVs in the context of neurobiological changes seen with exercise and depression by summarizing studies on exercise and MDD, exercise and sEVs, and finally, sEVs as they relate to MDD. Moreover, we describe the links between peripheral sEV levels and their potential for infiltration into the brain. While literature suggests that aerobic exercise is protective against the development of mood disorders, there remains a scarcity of data on the therapeutic effects of exercise. Recent studies have shown that aerobic exercise does not appear to influence sEV size, but rather influence their concentration and cargo. These molecules have been independently implicated in numerous neuropsychiatric disorders. Taken together, these studies suggest that concentration of sEVs are increased post exercise, and they may contain specifically packaged protective cargo representing a novel therapeutic for MDD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".