Differential Roles of Macrophages and Microglia in Subretinal Fibrosis Secondary to Neovascular Age-Related Macular Degeneration
Bibliographic record
Abstract
Purpose: To investigate the differential role of infiltrating CCR2+ macrophages and CX3CR1+ microglia in neovascular AMD (nAMD)-mediated subretinal fibrosis. Methods: Subretinal fibrosis was induced using the two-stage laser protocol in C57BL/6J or CX3CR1gfp/+ mice. The fibrotic lesion was detected using collagen-1 staining in retinal pigment epithelial /choroidal flatmounts. Infiltrating macrophages and microglial were identified using F4/80, CCR2, and CX3CR1 markers at one, three, six, and 10 days after the second laser. Circulating CCR2+ monocytes were depleted using the MC-21 antibody, whereas CX3CR1+ microglia were depleted using PLX5622. BV2 microglia were treated with TGF-β1 for 96 hours, and their profibrotic potential was examined by quantitative PCR and immunocytochemistry. Results: Subretinal fibrosis lesions developed three days after the second laser, accompanied by persistent CCR2+F4/80+ macrophage and CX3CR1+ cell infiltration. Inflammation in the first three days after the second laser was dominated by filtrating CX3CR1+ cells, and the number increased until day (D) 10 post-second laser. Depletion of CCR2+ monocytes from D5-10 significantly reduced the vascular and fibrotic components of the lesion, while CX3CR1+ cell depletion reduced Isolectin B4+ but not collagen-1+ lesion size. Bone marrow-derived macrophages from D6 and D10 mice expressed significantly higher levels of α-smooth muscle actin (α-SMA) and collagen-1 compared to cells from D1 and D3. TGFβ1 treatment increased TMEM119, CX3CR1, IL1b and iNOS gene expression but did not affect Acta2 and Col1a1 gene expression in BV2 cells. Conclusions: CCR2+ monocytes, but not CX3CR1+ microglia, critically contribute to the development of subretinal fibrosis in nAMD.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".