Calpain-Induced Endoplasmic Reticulum Stress and Cell Death following Cytotoxic Damage to Renal Cells
Bibliographic record
Abstract
Calpains and endoplasmic reticulum (ER) stress have both been implicated in renal cell death following exposure to reactive chemical toxicants (RCTs). Therefore, we explored the link between ER stress, calpain, and cell death in renal cell injury due to model RCTs (iodoacetamide, menadione, tert-butyl hydroperoxide) and ER stress inducers (tunicamycin [TUN], thapsigargin [THAPS]). The calpain inhibitor, PD150606, significantly reduced the RCT and TUN-induced cell death in the renal cell line LLC-PK1, but not death induced by THAPS. ER stress was confirmed by the significant induction of GRP78 following exposure to RCTs and ER stress inducers. While GRP94 induction was observed following RCTs and TUN, it was not statistically significant because of variability. THAPS at 5 microM significantly induced GRP94, while 20 mmicroM caused a calpain-dependent cleavage of GRP94. Caspase-12 and m-calpain were variably induced and/or cleaved following exposure to all toxicants, supporting activation of these signaling pathways. Inhibition of calpain blocked the induction of GRP78 following exposure to RCTs suggesting that calpain was contributing to the observed ER stress following RCTs. In contrast, calpain inhibition did not block ER stress protein induction following exposure to nontoxic concentrations of TUN or THAPS, indicating that calpain inhibition did not block the ER stress protein induction pathways directly. These studies demonstrate a previously unappreciated link between calpain activation and ER stress-associated cell death in renal cells. While further studies are required to clarify the molecular events involved, these results confirm that calpain activation and the ER are important related players in chemically induced renal cell damage.
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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".