Electrical stimulation-induced muscle damage alters hippocampal BDNF signaling
Bibliographic record
Abstract
This study investigates whether electrical stimulation (ES) could mimic traditional exercise in enhancing brain-derived neurotrophic factor (BDNF)-dependent neuroplasticity via muscle-brain communication, specifically through fibronectin type III domain-containing protein 5 (FNDC5)/Irisin pathway. Male Wistar rats received transcutaneous ES targeting the lumbar nerve roots to induce hindlimb muscle contractions for 30 minutes daily over seven consecutive days. Blood and tissue samples were collected for biochemical, histological, and molecular analyses, one day after the final session. Our findings reveal that ES disrupted BDNF signaling in the hippocampus, reducing synaptic protein expression. At the muscular level, ES caused significant damage, particularly in the soleus muscle, accompanied by muscle satellite cell (MuSC) activation, proliferation, and differentiation. Notably, ES increased FNDC5 expression in injured muscles, but this was associated with MuSC activation rather than humoral communication between muscle and brain. Moreover, a positive correlation was observed between the pro-inflammatory state of the injured muscles and hippocampal glucocorticoid receptor activation, as an indicator of stress, which was linked to impaired BDNF signaling. These results suggest two key conclusions: (1) increased FNDC5 expression in damaged muscle fibers primarily reflects local repair mechanisms rather than a beneficial humoral dialogue and (2) ES protocols that induce muscle injury can negatively impact BDNF-dependent plasticity by triggering maladaptive muscle-brain interactions. These findings highlight the importance of optimizing muscle stimulation protocols to minimize muscle damage, particularly when applied to individuals unable to engage in conventional physical activity or suffering from muscle weakness.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".