Exercise reverses age‐related vulnerability of the retina to injury by preventing complement‐mediated synapse elimination via a <scp>BDNF</scp> ‐dependent pathway
Bibliographic record
Abstract
Retinal ganglion cells (RGCs) become increasingly vulnerable to injury with advancing age. We recently showed that this vulnerability can be strongly modified in mice by exercise. However, the characteristics and underlying mechanisms of retinal protection with exercise remain unknown. Hence, the aim of this study was to investigate cellular changes associated with exercise-induced protection of aging retinal cells and the role of local and peripheral trophic signalling in mediating these effects. We focussed on two molecules that are thought to play key roles in mediating beneficial effects of exercise: brain-derived neurotrophic factor (BDNF) and AMP-activated protein kinase (AMPK). In middle-aged (12 months old) C57BL/6J mice, we found that exercise protected RGCs against dysfunction and cell loss after an acute injury induced by elevation of intra-ocular pressure. This was associated with preservation of inner retinal synapses and reduced synaptic complement deposition. Retinal expression of BDNF was not upregulated in response to exercise alone. Rather, exercise maintained BDNF levels in the retina, which were decreased postinjury in nonexercised animals. Confirming a critical role for BDNF, we found that blocking BDNF signalling during exercise by pharmacological means or genetic knock-down suppressed the functional protection of RGCs afforded by exercise. Protection of RGCs with exercise was independent of activation of AMPK in either retina or skeletal muscle. Our data support a previously unidentified mechanism in which exercise prevents loss of BDNF in the retina after injury and preserves neuronal function and survival by preventing complement-mediated elimination of synapses.
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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 | 0.001 |
| 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".