Ischemic neurons prevent vascular regeneration of neural tissue by secreting semaphorin 3A
Bibliographic record
Abstract
The failure of blood vessels to revascularize ischemic neural tissue represents a significant challenge for vascular biology. Examples include proliferative retinopathies (PRs) such as retinopathy of prematurity and proliferative diabetic retinopathy, which are the leading causes of blindness in children and working-age adults. PRs are characterized by initial microvascular degeneration, followed by a compensatory albeit pathologic hypervascularization mounted by the hypoxic retina attempting to reinstate metabolic equilibrium. Paradoxically, this secondary revascularization fails to grow into the most ischemic regions of the retina. Instead, the new vessels are misdirected toward the vitreous, suggesting that vasorepulsive forces operate in the avascular hypoxic retina. In the present study, we demonstrate that the neuronal guidance cue semaphorin 3A (Sema3A) is secreted by hypoxic neurons in the avascular retina in response to the proinflammatory cytokine IL-1β. Sema3A contributes to vascular decay and later forms a chemical barrier that repels neo-vessels toward the vitreous. Conversely, silencing Sema3A expression enhances normal vascular regeneration within the ischemic retina, thereby diminishing aberrant neovascularization and preserving neuroretinal function. Overcoming the chemical barrier (Sema3A) released by ischemic neurons accelerates the vascular regeneration of neural tissues, which restores metabolic supply and improves retinal function. Our findings may be applicable to other neurovascular ischemic conditions such as stroke.
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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".