Effects of telmisartan and pioglitazone on high fructose induced metabolic syndrome in rats
Bibliographic record
Abstract
Metabolic syndrome (MS) is a cluster of hypertension, insulin resistance, dyslipidaemia, and hyperuricemia. This study was designed to assess the effect of telmisartan and pioglitazone on high fructose induced MS. Thirty-five male albino rats were classified into 5 groups: A, normal diet; B, high-fructose diet (HFD) subdivided into B1 (HFD only), B2 (telmisartan, 5 mg/kg), B3 (pioglitazone, 10 mg/kg), and B4 (telmisartan + pioglitazone). Administration of the drugs was started after the rats had been on HFD for 4 weeks and continued for 4 weeks. Body mass (BM), blood pressure (BP), uric acid (UA), total cholesterol, triglycerides (TG), high-density lipoprotein (HDL-c), low-density lipoprotein (LDL-c), blood urea nitrogen (BUN), creatinine, and nitric oxide (NO) were measured and the levels of fasting glucose and fasting insulin were estimated. Compared with group B1, telmisartan treatment significantly decreased BP, BM, serum glucose, insulin, UA, urea, cholesterol, TGA, and LDL and significantly increased HDL, whereas pioglitazone treatment significantly decreased BP, serum glucose, insulin, UA, urea, creatinine, cholesterol, TGA, and LDL and significantly increased HDL. Co-administration of pioglitazone + telmisartan significantly decreased insulin, urea, and creatinine compared with telmisartan alone. Combined telmisartan + pioglitazone allowed better control of BP, hyperglycaemia, insulin resistance, and the amelioration of BM increase that may be associated with pioglitazone treatment.
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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 | 0.001 |
| 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".