Corticosteroids reduce pathological angiogenesis yet compromise reparative vascular remodeling in a model of retinopathy
Bibliographic record
Abstract
Tissue inflammation is often broadly associated with cellular damage, yet sterile inflammation also plays critical roles in beneficial tissue remodeling. In the central nervous system, this is observed through a predominantly innate immune response in retinal vascular diseases such as age-related macular degeneration, diabetic retinopathy, and retinopathy of prematurity. Here, we set out to elucidate the dynamics of the immune response during progression and regression of pathological neovascularization in retinopathy. In a mouse model of oxygen-induced retinopathy, we report that dexamethasone, a broad-spectrum corticosteroid, suppresses initial formation of pathological preretinal neovascularization in early stages of disease, yet blunts reparative inflammation by impairing distinct myeloid cell populations, and hence reduces beneficial vascular remodeling in later stages of disease. Using genetic depletion of distinct components of the innate immune response, we demonstrate that CX3C chemokine receptor 1-expressing microglia contribute to angiogenesis. Conversely, myeloid cells expressing lysozyme 2 are recruited to sites of damaged blood vessels and pathological neovascularization where they partake in a reparative process that ultimately restores circulatory homeostasis to the retina. Hence, the Janus-faced properties of anti-inflammatory drugs should be considered, particularly in stages associated with persistent neovascularization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".