Neutrophils homing into the retina trigger pathology in early age-related macular degeneration
Bibliographic record
Abstract
Age-related macular degeneration (AMD) is an expanding problem as longevity increases worldwide. While inflammation clearly contributes to vision loss in AMD, the mechanism remains controversial. Here we show that neutrophils are important in this inflammatory process. In the retinas of both early AMD patients and in a mouse model with an early AMD-like phenotype, we show neutrophil infiltration. Such infiltration was confirmed experimentally using ribbon-scanning confocal microscopy (RSCM) and IFNλ- activated dye labeled normal neutrophils. With neutrophils lacking lipocalin-2 (LCN-2), infiltration was greatly reduced. Further, increased levels of IFNλ in early AMD trigger neutrophil activation and LCN-2 upregulation. LCN-2 promotes inflammation by modulating integrin β1 levels to stimulate adhesion and transmigration of activated neutrophils into the retina. We show that in the mouse model, inhibiting AKT2 neutralizes IFNλ inflammatory signals, reduces LCN-2-mediated neutrophil infiltration, and reverses early AMD-like phenotype changes. Thus, AKT2 inhibitors may have therapeutic potential in early, dry AMD.
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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) | 0.002 | 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".