Ethanolic extract and ethyl acetate fraction of <i>Coutoubea spicata</i> attenuate hyperglycemia, oxidative stress, and muscle damage in alloxan-induced diabetic rats subjected to resistance exercise training program
Bibliographic record
Abstract
Gentianaceae family (such as Coutoubea spicata) contains iridoids and flavonoids with antidiabetic properties. However, there is no information available about the antidiabetic effects of C. spicata when combined with resistance exercise training (RET). This study evaluated the effects of the ethanolic extract (EE) and ethyl acetate fraction (EAF) of C. spicata on biochemical markers, muscle damage, and oxidative stress in diabetic rats submitted to RET. Alloxan-induced diabetic rats were distributed into 4 groups (each group, n = 8) treated with distilled water (TD), EE, EAF, or metformin and submitted to RET. Two groups without the disease (each group, n = 8) (sedentary control and trained control), as well as a sedentary diabetic group (n = 8) were included. Body weight and glycemia were evaluated weekly. After 30 days, lipid/lipoprotein profile, aspartate aminotransferase, alanine aminotransferase, muscle damage ((creatine kinase (CK) and lactate dehydrogenase (LDH)), and oxidative stress (malondialdehyde (MDA), sulfhydryl groups (SH), and ferric reducing antioxidant power) were evaluated. MDA and SH for pancreas, liver, heart, and muscle were evaluated. C. spicata extract and fraction combined with RET recovered body weight and reduced glycemia, muscle damage (CK: 36.83% and 21.45%; LDH: 49.83% and 68.55%), and low-density lipoprotein cholesterol (70.63%; 59.18%) and improved redox status (MDA: 50.33%, 39.74%; and SH: 53.97%; 76.41%), respectively, when compared with the TD group. C. spicata plus RET promoted anti-hyperglycemic, lipid-reducing, and antioxidant effects in diabetic rats. Novelty C. spicata presents anti-hyperglycemic and lipid-lowering effects potentiated by RET. C. spicata reduces muscle injury and increases antioxidant defense.
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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 | 0.001 | 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 | 0.000 |
| 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".