Training-specific effects on metabolic-inflammatory mediators: GLP-1 and Dectin-1 changes following resistance, continuous, or interval exercise in overweight women
Bibliographic record
Abstract
The purpose of this study was to examine the effects of eight weeks of resistance, continuous endurance, and interval endurance training on Dectin-1 and Glucagon-Like Peptide-1 levels in overweight women. A total of 40 women, aged between 25 and 35 years with a body mass index (BMI) ranging from 25 to 30 kg/m², voluntarily participated in the study. Participants were randomly assigned to one of four groups: resistance training (n = 10), continuous endurance training (n = 10), interval endurance training (n = 10), and a non-training control group (n = 10). The intervention consisted of three exercise sessions per week over an eight-week period, following structured and group-specific training protocols. Results indicated that all three exercise modalities—resistance, continuous endurance, and interval training— significantly altered Dectin-1 and GLP-1 levels compared to the control group (p < 0.05). Among the training groups, continuous endurance training elicited the greatest reduction in Dectin-1 levels, followed by interval training and then resistance training. However, post hoc analysis revealed no significant difference between resistance and interval training groups for either biomarker. Similarly, GLP-1 levels increased most prominently in the continuous endurance group, followed by the interval and resistance training groups, again with no significant difference between the latter two. In summary, the findings suggest that all three forms of exercise contributed to favorable changes in Dectin-1 and GLP-1 among overweight women. Nonetheless, the magnitude of these changes appears to be influenced by the type and possibly the intensity of the training stimulus, with continuous endurance training demonstrating the most pronounced effects.
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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 | 0.000 |
| 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".