Early-life peripheral infections reprogram retinal microglia and aggravate neovascular age-related macular degeneration in later life
Bibliographic record
Abstract
Pathological neovascularization in age-related macular degeneration (nvAMD) drives the principal cause of blindness in the elderly. While there is a robust genetic association between genes of innate immunity and AMD, genome-to-phenome relationships are low, suggesting a critical contribution of environmental triggers of disease. Possible insight comes from the observation that a past history of infection with pathogens such as Chlamydia pneumoniae, or other systemic inflammation, can predispose to nvAMD in later life. Using a mouse model of nvAMD with prior C. pneumoniae infection, endotoxin exposure, and genetic ablation of distinct immune cell populations, we demonstrated that peripheral infections elicited epigenetic reprogramming that led to a persistent memory state in retinal CX3CR1+ mononuclear phagocytes (MNPs). The immune imprinting persisted long after the initial inflammation had subsided and ultimately exacerbated choroidal neovascularization in a model of nvAMD. Single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) identified activating transcription factor 3 (ATF3) as a central mediator of retina-resident MNP reprogramming following peripheral inflammation. ATF3 polarized MNPs toward a reparative phenotype biased toward production of proangiogenic factors in response to subsequent injury. Therefore, a past history of bacterial endotoxin-induced inflammation can lead to immunological reprograming within CNS-resident MNPs and aggravate pathological angiogenesis in the aging retina.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| 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".