Retinal Astrocytes Mediate Neuroprotective Effects Through p38 MAPK Dependent Activation
Bibliographic record
Abstract
Astrocytes play a fundamental role in maintaining a delicate neuronal homeostasis. In response to injury and stress, astrocytes undergo a switch; becoming hypertrophic and migratory, secreting cytokines, coordinating tissue remodeling, and increasing production of antioxidants. However, the cellular signals regulating this switch are still not well understood, and its impact on neurons remains unclear. As a developmental outpocketing of the forebrain, the retina is a bellwether and model for damage to the central nervous system (CNS). In the rodent eye, astrocytes remain tightly restricted to a single layer on the inner retinal surface, beside a single layer of retinal ganglion cell neurons. This relatively simple system provides an accessible model of glial‐neuronal interactions. We have used the retina to develop and establish robust models of astrocyte activation in response to oxidative, metabolic, and hypoxic stresses. Characteristic molecular and biochemical changes in activated cells have implicated signals through the p38 MAPK (mitogen activated protein kinase) pathway as a key mediator of this process. We demonstrate that modulation of this pathway is necessary for the cells to mount an appropriate injury response. However, quiescent cells produce a neuroprotective effect on retinal neurons, while activated cells exacerbate injury.
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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 | 0.000 | 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 | 0.001 |
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".