Synergistic action of brain-derived neurotrophic factor and lens injury promotes retinal ganglion cell survival, but leads to optic nerve dystrophy in vivo
Bibliographic record
Abstract
Trauma or disease in the CNS often leads to neuronal death and consequent loss of functional connections. The idea has been put forward that strategies aimed at repairing the injured CNS involve stimulation of both neuronal survival and axon regeneration. We tested this hypothesis in the adult rat retinocollicular system by combining two strategies: (i) exogenous administration of brain-derived neurotrophic factor (BDNF), a potent survival factor for damaged retinal ganglion cells (RGCs) and (ii) lens injury, which promotes robust growth of transected RGC axons. Our results demonstrate that BDNF and lens injury interact synergistically to promote neuronal survival: 71% of RGCs were alive at 2 weeks after optic nerve injury, a time when only approximately 10% of these neurons remain without treatment. Intravitreal injection of BDNF, however, led to regeneration failure following lens injury. The effect of BDNF could not be generalized to other growth factors, as ciliary neurotrophic factor did not cause a significant reduction of lens injury-induced regeneration. Growth arrest in optic nerves treated with BDNF and lens injury correlated with the formation of hypertrophic axonal swellings in the proximal optic nerve. These swellings were filled with numerous vesicular bodies, disorganized neurofilaments and degenerating organelles. Our results demonstrate that: (i) increased neuronal survival does not necessarily lead to enhanced axon regeneration and (ii) activation of survival and growth pathways may produce axonal dystrophy similar to that found in neurodegenerative disorders including glaucoma, Alzheimer's disease and multiple sclerosis. We propose that loss of axonal integrity may limit neuronal recovery in the injured, adult CNS.
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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) | 0.000 | 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) | 0.000 | 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".