The effect of folic acid administration on cardiac tissue matrix metalloproteinase activity and hepatorenal biomarkers in diabetic rats
Bibliographic record
Abstract
Diabetes mellitus (DM) is a metabolic disorder that causes severe complications. Thus, the aims of this study were to investigate the influence of DM and folic acid treatment on liver and renal biomarkers, and heart remodeling through evaluation of cardiac matrix metalloproteinase (MMP) activity. There were 4 groups: control (physiological saline 1 mL/kg, i.p., 28 days), DM (streptozotocin [STZ] 100 mg/kg in physiological saline, i.p., 1 day), folic acid (FA; 5 mg/kg, i.p., 28 days), and DM+FA (STZ 100 mg/kg, i.p., 1 day and folic acid 5 mg/kg, i.p., 28 days). Our results demonstrated increased aminotransferase and alkaline phosphatase activity, urea and creatinine concentration, and decreased albumin and fibrinogen concentration in the DM group. MMP-2 relative activity was elevated in the DM and FA groups; MMP-9 was decreased in the DM and increased in the FA group. The folic acid treatment of diabetic rats did not change aminotransferase activity; it alleviated the increase in alkaline phosphatase and the decrease in albumin and fibrinogen concentration, and reduced MMP-2 activity; however, it increased urea and creatinine concentration. In conclusion, folic acid treatment of diabetic rats has cardio- and hepato-protective effects. However, its dosing should be carefully considered because of possible renal 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".