Bibliographic record
Abstract
Accumulating evidence advances the critical role of autophagy in brain pathology after stroke. Investigations employing autophagy induction or inhibition using pharmacological tools or autophagy-related gene knockout mice have recently revealed the biological significance of intact and functional autophagy in stroke. Most of the reported cases attest to a pro-survival role for autophagy in stroke, by facilitating removal of damaged proteins and organelles, which can be recycled for energy generation and cellular defenses. However, these observations are difficult to reconcile with equally compelling evidence demonstrating stroke-induced upregulation of brain cell death index that parallels enhanced autophagy. This begs the question of whether drug-induced autophagy during stroke culminates in improved or worsened pathological outcomes. A corollary fascinating hypothesis, but presents as a tricky conundrum, involves the effects of autophagy on cell death and inflammation, which are two main culprits in the disease progression of stroke-induced brain injury. Evidence has extended the roles of autophagy in inflammation via cytokine regulation in an unconventional secretion manner or by targeting inflammasomes for degradation. Moreover, in the recently concluded Vancouver Autophagy Symposium (VAS) held in 2014, the potential of selective autophagy for clinical treatment has been recognized. The role of autophagy in ischemic stroke has been reviewed previously in detail. Here, we evaluate the strength of laboratory and clinical evidence by providing a comprehensive summary of the literature on autophagy, and thereafter we offer our perspectives on exploiting autophagy as a drug target for cerebral ischemia, especially in hemorrhagic stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".