Purinergic signaling via P2X receptors and mechanisms of unregulated ATP release in the outer retina and age-related macular degeneration
Bibliographic record
Abstract
Age-related macular degeneration (AMD) is a chronic and progressive inflammatory disease of the retina characterized by photoceptor loss and significant central visual impairment due to either choroidal neovascularization or geographic atrophy. The pathophysiology of AMD is complex and multifactorial, driven by a combination of modifiable and non-modifiable risk factors, molecular mechanisms, and cellular processes that contribute to overall disease onset, severity, and progression. Unfortunately, due to the structural, cellular, and pathophysiologic complexity, therapeutic discovery is challenging. While purinergic signaling has been investigated for its role in the development and treatment of ocular pathologies including AMD, the potential crosstalk between known contributors to AMD, such as the complement cascade and inflammasome activation, and other biological systems, such as purinergic signaling, have not been fully characterized. In this review, we explore the interactions between purinergic signaling, ATP release, and known contributors to AMD pathogenesis including complement dysregulation and inflammasome activation. We begin by identifying what is known about purinergic receptors in cell populations of the outer retina and potential sources of extracellular ATP required to trigger purinergic receptor activation. Next, we examine evidence in the literature that the purinergic system accelerates AMD pathogenesis leading to apoptotic and pyroptotic cell death in retinal cells. To fully understand the potential role that purinergic signaling plays in AMD, more research is needed surrounding the expression, distribution, functions, and interactions of purinergic receptors within cells of the outer retina as well as potential crosstalk with other systems. By determining how these processes are affected in the context of purinergic signaling, it will improve our understanding of the mechanisms that drive AMD pathogenesis which is critical in developing treatment strategies that prevent or slow progression of the disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".