Neurovascular cross talk in diabetic retinopathy: Pathophysiological roles and therapeutic implications
Bibliographic record
Abstract
Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population in developed countries, and its prevalence will increase as the global incidence of diabetes grows exponentially. DR begins with an early nonproliferative stage in which retinal blood vessels and neurons degenerate as a consequence of chronic hyperglycemia, resulting in vasoregression and persistent retinal ischemia, metabolic disequilibrium, and inflammation. This is conducive to overcompensatory pathological neovascularization associated with advanced proliferative DR. Although DR is considered a microvascular complication, the retinal microvasculature is intimately associated with and governed by neurons and glia; neurodegeneration, neuroinflammation, and dysregulation of neurovascular cross talk are responsible in part for vascular abnormalities in both early nonproliferative DR and advanced proliferative DR. Neuronal activity directly regulates microvascular dilation and blood flow in the process of neurovascular coupling. Retinal neurons also secrete guidance cues in response to injury, ischemia, or metabolic stress that may either promote or suppress vascular outgrowth, either alleviating or exacerbating DR, contingent on the stage of disease and retinal microenvironment. Neurodegeneration, impaired neurovascular coupling, and dysregulation of neuronal guidance cues are key events in the pathogenesis of DR, and correcting these events may prevent or delay development of advanced DR. The review discusses the mechanisms of neurovascular cross talk and its dysregulation in DR, and their potential therapeutic implications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".