A synthetic peptide rescues rat cortical neurons from anesthetic-induced cell death, perturbation of growth and synaptic assembly
Bibliographic record
Abstract
Anesthetics are deemed necessary for all major surgical procedures. However, they have also been found to exert neurotoxic effects when tested on various experimental models, but the underlying mechanisms remain unknown. Earlier studies have implicated mitochondrial fragmentation as a potential target of anesthetic-induced toxicity, although clinical strategies to protect their structure and function remain sparse. Here, we sought to determine if preserving mitochondrial networks with a non-toxic, short-life synthetic peptide-P110, would protect cortical neurons against both inhalational and intravenous anesthetic-induced neurotoxicity. This study provides the first direct and comparative account of three key anesthetics (desflurane, propofol, and ketamine) when used under identical conditions, and demonstrates their impact on neonatal, rat cortical neuronal viability, neurite outgrowth and synaptic assembly. Furthermore, we discovered that inhibiting Fis1-mediated mitochondrial fission reverses anesthetic-induced aberrations in an agent-specific manner. This study underscores the importance of designing mitigation strategies invoking mitochondria-mediated protection from anesthetic-induced toxicity in both animals and humans.
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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 | 0.000 |
| 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".