Tetramethylpyrazine attenuates sodium arsenite-induced acute kidney injury by improving the autophagic flux blockade via a YAP1-Nrf2-p62-dependent mechanism
Bibliographic record
Abstract
models using clinically related dosages of AS III. Mitophagy, upregulated YAP1 expression, and Nrf2 activation were observed, with upregulation of p62 representing the occurrence of autophagic flux blockade. In HK-2 cells, oxidative stress induced by AS III promoted sustained Nrf2 activation, which enhanced p62 transcription at an early phase. Subsequently, p62 accumulation induced Nrf2 nuclear translocation, which in turn promoted p62 expression, forming a feedback loop to induce autophagic flux blockade, which was aggravated by the autophagic flux blocker chloroquine (CQ). TMP reversed such processes and protected tubular cells, while silencing YAP1 and Nrf2 attenuated TMP renoprotections. YAP1 agonist PY-60 increased Nrf2 expression, while YAP1 knockdown counteracted it and diminished TMP effect on autophagic flux. Furthermore, blocking Nrf2 caused YAP1 accumulation. CO-IP and immunofluorescence co-localization results confirmed co-nuclear translocations of YAP1 bound to dissociated Nrf2 that induced autophagic flux blockade. In conclusion, the present study identified novel mechanisms that TMP alleviated AI-AKI by improving the autophagic flux blockade via a YAP1-Nrf2-p62-dependent mechanism.
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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) | 0.001 | 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".