Neurovascular dysfunction in glaucoma
Bibliographic record
Abstract
Retinal ganglion cells, the neurons that die in glaucoma, are endowed with a high metabolism requiring optimal provision of oxygen and nutrients to sustain their activity. The timely regulation of blood flow is, therefore, essential to supply firing neurons in active areas with the oxygen and glucose they need for energy. Many glaucoma patients suffer from vascular deficits including reduced blood flow, impaired autoregulation, neurovascular coupling dysfunction, and blood-retina/brain-barrier breakdown. These processes are tightly regulated by a community of cells known as the neurovascular unit comprising neurons, endothelial cells, pericytes, Müller cells, astrocytes, and microglia. In this review, the neurovascular unit takes center stage as we examine the ability of its members to regulate neurovascular interactions and how their function might be altered during glaucomatous stress. Pericytes receive special attention based on recent data demonstrating their key role in the regulation of neurovascular coupling in physiological and pathological conditions. Of particular interest is the discovery and characterization of tunneling nanotubes, thin actin-based conduits that connect distal pericytes, which play essential roles in the complex spatial and temporal distribution of blood within the retinal capillary network. We discuss cellular and molecular mechanisms of neurovascular interactions and their pathophysiological implications, while highlighting opportunities to develop strategies for vascular protection and regeneration to improve functional outcomes in glaucoma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".