Isoflurane and low-level carbon monoxide exposures increase expression of pro-survival miRNA in neonatal mouse heart
Bibliographic record
Abstract
Anesthetics such as isoflurane are known to cause apoptosis in the developing mammalian brain. However, isoflurane may have protective effects on the heart via relieving ischemia and downregulating genes related to apoptosis. Ischemic preconditioning, e.g. through the use of low levels of carbon monoxide (CO), has promise in preventing ischemia-reperfusion injury and cell death. However, it is still unclear how it either triggers the stress response in neonatal hearts. For this reason, thirty-three microRNAs (miRNAs) known to be differentially expressed following anesthesia and/or ischemic or hypoxic heart damage were investigated in the hearts from neonatal mice exposed to isoflurane or low level of CO, using an air-exposed control group. Only miR-93-5p increased with isoflurane exposure, which may be associated with the suppression of cell death, autophagy, and inflammation. By contrast, twelve miRNAs were differentially expressed in the heart following CO treatment. Many miRNAs previously shown to be responsible for suppressing cell death, autophagy, and myocardial hypertrophy were upregulated (e.g., 125b-3p, 19-3p, and 21a-5p). Finally, some miRNAs (miR-103-3p, miR-1a-3p, miR-199a-1-5p) which have been implicated in regulating energy balance and cardiac contraction were also differentially expressed. Overall, this study demonstrated that CO-mediated miRNA regulation may promote ischemic preconditioning and cardioprotection based on the putative protective roles of the differentially expressed miRNAs explored herein and the consistency of these results with those that have shown positive effects of CO on heart viability following anesthesia and ischemia-reperfusion stress.
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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 | 0.001 |
| 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".