Knockdown of apoptosis signal‐regulating kinase 1 affects ischaemia‐induced astrocyte activation and glial scar formation
Bibliographic record
Abstract
Reactive astrocytes play an essential role in determining the tissue response to ischaemia. Formation of a glial scar can block the neuronal outgrowth that is required for restoration of damaged tissue. Therefore, regulation of astrocyte activation is important; however, the mediator of this process has not been fully elucidated. Apoptosis signal-regulating kinase 1 (ASK1) is an early responder to oxidative stress, and plays a pivotal role in the intracellular signalling pathway of apoptosis, inflammation, and differentiation. To confirm whether ASK1 mediates astrocyte activation and leads to glial scar formation after cerebral ischaemia, we conducted in vivo and in vitro experiments. C57BL/6 mice were subjected to occlusion of the middle cerebral artery, and astrocyte cultures were exposed to oxygen-glucose deprivation. After silencing of ASK1 , astrocyte-associated genes were downregulated, as seen with the use of microarrays. The glial fibrillary acidic protein (GFAP) level was decreased, and correlated with the reduction in the ASK1 level. In astrocytes, reduction in the ASK1 level decreased the activity of the p38 pathway, and the levels of transcription factors for GFAP and GFAP transcripts after hypoxia. In the chronic phase, ASK1 depletion reduced glial scar formation and conserved neuronal structure, which may lead to better functional recovery. These data suggest that ASK1 may be an important mediator of ischaemia-induced astrocyte activation and scar formation, and could provide a potential therapeutic target for treatment after ischaemic stroke.
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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 | 0.000 | 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".