Intranasal insulin rescues repeated anesthesia-induced deficits in synaptic plasticity and memory and prevents apoptosis in neonatal mice via mTORC1
Bibliographic record
Abstract
Long-lasting cognitive impairment in juveniles undergoing repeated general anesthesia has been observed in numerous preclinical and clinical studies, yet, the underlying mechanisms remain unknown and no preventive treatment is available. We found that daily intranasal insulin administration to juvenile mice for 7 days prior to repeated isoflurane anesthesia rescues deficits in hippocampus-dependent memory and synaptic plasticity in adulthood. Moreover, intranasal insulin prevented anesthesia-induced apoptosis of hippocampal cells, which is thought to underlie cognitive impairment. Inhibition of the mechanistic target of rapamycin complex 1 (mTORC1), a major intracellular effector of insulin receptor, blocked the beneficial effects of intranasal insulin on anesthesia-induced apoptosis. Consistent with this finding, mice lacking mTORC1 downstream translational repressor 4E-BP2 showed no induction of repeated anesthesia-induced apoptosis. Our study demonstrates that intranasal insulin prevents general anesthesia-induced apoptosis of hippocampal cells, and deficits in synaptic plasticity and memory, and suggests that the rescue effect is mediated via mTORC1/4E-BP2 signaling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".