Potential Role of Microglia in Retinal Blood Vessel Formation
Bibliographic record
Abstract
PURPOSE: The role of microglia, present in the retina early in development before vascularization, remains ill defined. The authors investigated whether microglia are implicated in retinal blood vessel formation. METHODS: The microglia and vasculature of developing human fetal and rodent retinas were examined by labeling the endothelial cells with lectin and the microglia with CD18 antibody or green fluorescent protein driven by the promoter of the chemokine receptor CX(3)CR1. Rodent ischemic proliferative retinopathy induced by hyperoxia or hypercapnia, which model retinopathy of prematurity, and ex vivo retinal explants were used to assess microglial involvement in vascular pathology. Microglial participation in developmental retinal vessel formation was further studied in neonatal rats after pharmacologic macrophage depletion with the use of clodronate liposomes and subsequent intravitreal injection of microglia. RESULTS: Microglia intimately appose developing vessels of human and murine retinas. Ischemic retinopathy models exhibit decreased microglia concomitant with the characteristic reductions in vasculature observed in these retinopathies. Retinal explants exposed to conditions resulting in ischemic retinopathies (in vivo) reveal that antioxidants protect against microglial loss. Depletion of resident retinal microglia, but not systemic macrophages, reduced developmental vessel growth and density, which were restored by intravitreal microglial injection. CONCLUSIONS: These observations suggest that proper retinal blood vessel formation requires an adequate resident microglial population because diminished microglia are associated with decreased vascularity in models of ischemic retinopathy and retinal vascular development. In light of these findings, the traditional definition of microglia as merely immunocompetent cells should be reconsidered to encompass this new function related to blood vessel formation.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".