Crosstalk among apoptosis, inflammation, and autophagy in relation to melatonin protective effect against contrast-induced nephropathy in rats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Contrast medium (CM) is a chemical substance that is used for imaging anatomical boundaries and to explore normal and abnormal physiological findings; the use of CM was associated with kidney injury and acute renal failure. Melatonin (M) possesses antioxidant, anti-inflammatory, and antiapoptotic effects in addition to autophagy modulation. This study aimed to investigate the protective effect of M against contrast-induced nephropathy (CIN) and its impact on the crosstalk between inflammasome, apoptosis, and autophagy in CIN. Male albino rats received M (10, 20, and 40 mg/kg/day, intraperitoneally) for 3 days. One hour after the last administration, rats were subjected to CIN induction (10 mg/kg indomethacin, double doses of l-NAME 10 mg/kg, i.v., and meglumine diatrizoate 60% 6 mL/kg, i.v.). CIN-induced kidney damage was evidenced through elevated kidney function biomarkers and induced renal histopathological changes. Pretreatment with M caused a significant decrease in nephrotoxicity biomarkers and histopathological alterations. Moreover, CIN-induced oxidative stress, NLRP3 inflammasome, and apoptosis were attenuated by M. Furthermore, M modulates autophagy in CIN rats. M inhibits CIN-induced NLRP3-inflammasome activation and apoptosis as well as enhances autophagy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 it