Protective effects of kolaviron and gallic acid against cobalt-chloride-induced cardiorenal dysfunction via suppression of oxidative stress and activation of the ERK signaling pathway
Bibliographic record
Abstract
Cobalt (Co) toxicity is a potential public health problem due to recent renewed use of Co in orthopedic implants, dietary supplements, and blood doping in athletes and horses. We investigated the protective roles of kolaviron (KV), a bi-flavonoid of Garcinia kola, and gallic acid (GA) on cobalt chloride (CoCl2)-induced cardiorenal damage in rats. CoCl2 caused significant increases (p < 0.05) in serum creatine kinase–myocardial band (CK-MB), lactate dehydrogenase (LDH), aspartate transaminase (AST), xanthine oxidase (XO), urea, creatinine, malondialdehyde, H2O2, nitric oxide, as well as C-reactive protein expression, along with significant (p < 0.05) reduction in cardiac and renal expression of extracellular signal regulated kinase (ERK) and the activities of superoxide dismutase, catalase, and glutathione S-transferase. KV and GA prevented the toxic effects of CoCl2 by stimulating ERK expression and reversing Co-induced biochemical changes. Administration of CoCl2 alone did not significantly alter ECG patterns in the rats, although co-treatment with KV (200 mg/kg) produced QT-segment prolongation and also appeared to potentiate Co hypotension. Histopathology of the heart and kidneys of rats treated with KV and GA confirmed the biochemical data. KV and GA thus protected against cardiac and renal damage in Co intoxication via antioxidant and (or) cell survival mechanisms, possibly involving ERK activation.
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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 | 0.000 |
| 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".