The Effect of Aerobic Training on Serum Levels of Adiponectin, Hypothalamic-Pituitary-Gonadal Axis and Sperm Quality in Diabetic Rats.
Bibliographic record
Abstract
PURPOSE: The present study aims to investigate the effects of aerobic training on adiponectin, sex hormones, and sperm parameters in Streptozotocin-Nicotinamide induced diabetic rats. MATERIAL AND METHODS: In the experiment, 52 eight-week-old Sprague Dawley rats (200-250 g) were randomly assigned into three groups: healthy control, diabetic control, and diabetic aerobic training. Diabetes was induced by intraperitoneal injection of nicotinamide solution and STZ solution. The aerobic training protocol was performed for ten weeks. Finally, blood serum was used to assess FSH, LH, testosterone and adiponectin levels. Data were analyzed using ANOVA and Tukey's post hoc test using SPSS-22 software at 0.05 level of significance. RESULTS: Results showed an increase in serum adiponectin levels in aerobic training group, which let to a significant difference between aerobic training group and diabetic control group (3.8±1.1 ?vs 1.6±0.6, P = .42). In addition, aerobic training caused significant increases in serum testosterone level and LH in diabetic aerobic training group, so that significant differences were observed between serum testosterone (5.7±2.3 vs 6.6±1.8, P = .117), LH (4.7±1 vs 5.6±2.8, P = .746) and FSH (5.9±5 vs 4.4±1, P = .596) of diabetic aerobic training group and healthy control group. Sperm parameters in the diabetic aerobic training group including sperm count (26±13.2 vs 11.7±5.7, P = .03, motility (40±6.5%vs 32.5±1.1%, P = .41) and viability (41.7±7.2% vs 29.78±16.2%, P = .000) presented significant differences compared to diabetic control group. CONCLUSION: Short term aerobic training can improve serum adiponectin levels and sperm parameters, including sperm count and sperm motility through increasing serum testosterone, LH and FSH levels in type 2 diabetic rats.
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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 | 0.001 |
| 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".