Inhibition of MicroRNA 195 Prevents Apoptosis and Multiple-Organ Injury in Mouse Models of Sepsis
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miRs) are a class of short RNA molecules, which negatively regulate gene expression. The levels of circulating miR-15 family members are elevated in septic patients and may be associated with septic death. This study investigated whether inhibition of miR-195, a member of the miR-15 family, provided beneficial effects in sepsis. METHODS AND RESULTS: Sepsis was induced by injection of feces into the peritoneum in mice. miR-195 was upregulated in the lung and liver of septic mice. Silencing of miR-195 increased the protein levels of BCL-2, Sirt1, and Pim-1; prevented apoptosis; reduced liver and lung injury; and improved the survival in septic mice. Silencing of miR-195 provided similar protection in lipopolysaccharide-induced endotoxemic mice. In endothelial cells, upregulation of miR-195 induced apoptosis, and inhibition of miR-195 prevented lipopolysaccharide-induced apoptosis. miR-195 repressed expression of its protein targets, BCL-2, Sirt1, and Pim-1. Furthermore, overexpression of Pim-1 prevented apoptosis induced by lipopolysaccharide and miR-195 mimic. Inhibition of Pim-1 attenuated the protective effects of miR-195 silencing in septic mice. CONCLUSIONS: Silencing of miR-195 reduced multiple-organ injury and improved the survival in sepsis, and the protective effects of miR-195 inhibition were associated with upregulation of Bcl-2, Sirt1, and Pim-1. Thus, inhibition of miR-195 may represent a new therapeutic approach for sepsis.
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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 | 0.001 |
| 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 | 0.001 | 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".