Nitric oxide induces apoptosis in renal tubular epithelial cells through activation of caspase-8
Bibliographic record
Abstract
The susceptibility or resistance of tubular epithelial cells (TEC) to apoptosis is pivotal to the long-term maintenance of kidney function following episodes of inflammation, such as graft rejection. TEC apoptosis can occur with ischemia as well as with proinflammatory cytokines and nitric oxide (NO), produced by infiltrating mononuclear cells. TEC can also produce abundant amounts of NO during inflammation but the role and regulation of NO-induced injury of TEC are not well understood. Apoptosis in TEC in vitro was determined by FACS analysis with annexin-V and propidium iodide staining. NO in culture supernatants was measured by Greiss reagent, and protein expression of inducible NO synthetase (NOS2/iNOS) and caspase-8 was examined by Western blot analysis. Here, we showed that murine TEC produced abundant amounts of NO in response to proinflammatory cytokines (IFN-gamma/TNF-alpha) through upregulation of NOS2, and inhibition of endogenous NO production by l-NMMA reduced TEC apoptosis in cytokine-stimulated cultures. Addition of exogenous NO (sodium nitroprusside) induced TEC apoptosis as well as caspase-8 activation in a dose-dependent manner. The key role of caspase-8 in NO-induced TEC apoptosis was demonstrated by that NO-induced TEC apoptosis can be blocked by caspase-8 inhibition using z-IETD-fmk, caspase-8 silencing with shRNA or by overexpressing the endogenous caspase-8 inhibitor c-FLIP (cellular Flice-inhibitory protein). In conclusion, endogenous NO from NOS2 activity as well as exogenous NO can contribute to renal injury through apoptosis of TEC. Activation of caspase-8 plays a central role in NO-induced apoptosis and caspase-8 inhibition may be an important therapeutic target during renal inflammation.
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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".