<scp>P</scp>eroxiredoxin 1 inhibits the oxidative stress induced apoptosis in renal tubulointerstitial fibrosis
Bibliographic record
Abstract
AIM: Apoptosis is one of the most important mechanisms underlying renal tubulointerstitial fibrosis. We identified a role of protein Peroxiredoxin 1 (Prx1) in protecting apoptosis occurred in tubular epithelial cells of the rat and human kidney. METHODS: Immunohistochemistry (IHC) staining was used to detect Prx1 expression in kidney derived from unilateral-ureteral obstruction (UUO) rats or patients with obstructive nephropathy. Modulation of Prx1 expression by transfecting siRNA and overexpression plasmid approach were carried out in NRK-52E (rat kidney tubular epithelial cell line) cells. UUO-induced apoptosis was determined using TUNEL assay. RESULTS: Immunohistochemistry staining showed that Prx1 expressed in the cytoplasm of renal tubular epithelial cells, in the kidneys of UUO rats. The reduction was confirmed by both IHC and real-time polymerase chain reaction following a course of renal tubulointerstitial fibrosis in UUO rats and a decrease of Prx1 occurred concomitantly with an elevation of TUNEL-positive cells. Fluorofenidone (AKF-PD), a new anti-tubulointerstitial fibrotic agent, attenuated Prx1 reduction in UUO rats. Furthermore, hydrogen peroxide (H2 O2 )-derived oxidative stress activated p38 MAPK, and induced apoptosis in NRK-52E cells; knockdown of Prx1 sensitized both events in NRK-52E cells, and overexpression of Prx1 diminished the apoptosis and the phosphorylation of p38 CONCLUSION: Downregulation of Prx1 occurred in renal tubular epithelial cells of UUO rats and patients with obstructive nephropathy. Prx1 may alleviate the pathogenesis by inhibiting H2 O2 -induced apoptosis via inhibiting the p38 MAPK pathway. Prx1 may represent a useful target for a protective therapy towards renal tubulointerstitial fibrosis.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".