Investigating the Impact of Time of Day on Glycaemia in Response to Postprandial Supramaximal Sprints in Adults With Type 1
Bibliographic record
Abstract
OBJECTIVES: In this study, we explore the impact of postprandial exercise timing (morning vs evening) on glycemia in individuals with type 1 diabetes (T1D) during short all-out sprints on a cycle ergometer. METHODS: Ten healthy, physically sedentary male (n=7) and female (n=3) volunteers with T1D, 22.8±2.8 years of age, and with a diabetes duration of 9.7±5.5 years and glycated hemoglobin level of 8.6±1.2%, underwent comprehensive screening and assessment of their physical health and fitness status before study participation, under the guidance of a physician. Each participant underwent 2 postprandial exercise sessions on separate days: the first in the morning at 8:00 AM and the second in the evening at 8:00 PM, both conducted 60 minutes after a standardized meal. RESULTS: Morning exercise showed a less pronounced reduction in plasma glucose (PG) levels compared with evening exercise (-2.01±1.24 vs -3.56±1.6 mmol/L, p=0.03). In addition, higher cortisol levels were observed in the morning vs evening (128.59±34 vs 67.79±26 ng/mL, p<0.001). CONCLUSIONS: Morning repeated sprint exercise conducted in the postprandial state consistent with the protective effect of higher cortisol levels resulted in a smaller reduction in PG levels compared with evening exercise. This highlights the potential influence of exercise timing on glycemic responses and cortisol secretion in the management of T1D.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".