P652The effects of two exercise therapy methods on cardio-metabolic risk factors in diabetic overweight middle-aged females
Bibliographic record
Abstract
Background/Introduction: The beneficial effects of exercise on glucose control in individuals with type 2 diabetes have been shown to be associated with reduction of several cardiometabolic risk factors.Therefore, the purpose of this study was to investigate the effects of two different exercise training on cardiometabolic risk factors in diabetic overweight middle-aged females. Methods: Fifty two overweight and diabetic females (age; 45–60 years old and fasting blood glucose ≥126 mg/dL) were recruited to participate in this study. Participants were randomly assigned into sprint interval training (SIT) group (n=17), concurrent resistance-endurance training (CRET) group (n=17) and control group (n=18). The combined strength-endurance group completed 12 weeks, three sessions per week of endurance training at 60% of maximal heart rate and two sessions of resistance training at 70% 1-RM. Intense interval training group completed three sessions/week of four to ten repetitions during 30 seconds. Wingate on ergometer included 10 weeks of concurrent resistance-endurance training and intense interval training. Fasting glucose, insulin, insulin resistance, high sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), systolic blood pressure, diastolic blood pressure, body fat, waist circumference (WC), waist to hip ratio (WHR) and body mass index (BMI) were measured before and after the both training interventions.
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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) | 0.001 | 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) | 0.003 | 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".