Protection of Renal Ischemia Injury using Combination Gene Silencing of Complement 3 and Caspase 3 Genes
Bibliographic record
Abstract
BACKGROUND: Ischemia/reperfusion (I/R) injury occurs in clinical kidney transplantation, which results in graft dysfunction and rejection. It has been documented that I/R injury is associated with complement activation and renal cell apoptosis. The purpose of this study was to develop a strategy to prevent I/R injury using small interfering RNA (siRNA) that target complement 3 (C3) and caspase 3 genes. METHODS: siRNA-expression vectors were constructed to target C3 and caspase 3 genes. Gene silencing efficacy was assessed using real-time polymerase chain reaction. In vivo gene silencing was performed by hydrodynamic injection with C3 and caspase 3 siRNA. Renal I/R injury was induced through clamping the renal vein and artery for 25 min. I/R injury was evaluated using kidney histopathology, blood urea nitrogen (BUN), serum levels of creatinine, and survival. RESULTS: Effective gene silencing was first confirmed in vitro. Notably upregulated expression of C3 and caspase 3 genes was observed from 2 to 48 hr after I/R injury, which were effectively and specifically inhibited by C3 and caspase 3 siRNA. In comparison with control mice, serum levels of creatinine and BUN were also significantly decreased in C3 and caspase 3 siRNA-treated mice. Furthermore, the therapeutic effect of siRNA was assessed in a severe, lethal I/R injury experiment, in which siRNA treatment significantly reduced mortality. Tissue histopathology showed an overall reduction in injury area in siRNA-treated mice. CONCLUSIONS: This is the first demonstration that renal I/R injury can be prevented through silencing the complement gene and apoptosis gene, highlighting the potential for siRNA-based clinical therapy.
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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 | 0.000 | 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) | 0.001 | 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".