The influence of nighttime feeding of carbohydrate or protein combined with exercise training on appetite and cardiometabolic risk in young obese women
Bibliographic record
Abstract
Single macronutrient intake prior to sleep reduces appetite but may negatively impact insulin sensitivity in sedentary obese women. The present study examined the additive impact of nighttime feeding of whey (WH), casein (CAS), or carbohydrate (CHO) combined with exercise training on appetite, cardiometabolic health, and strength in obese women. Thirty-seven sedentary obese women (WH, n = 13, body mass index (BMI) 34.4 ± 1.3 kg/m(2); CAS, n = 14, BMI 36.5 ± 1.8 kg/m(2); CHO, n = 10, BMI 33.1 ± 1.7 kg/m(2)) consumed WH, CAS, or CHO (140-150 kcal/serving), every night of the week, within 30 min of sleep, for 4 weeks. Supervised exercise training (2 days of resistance training and 1 day of high-intensity interval training) was completed 3 days per week. Pre- and post-testing measurements included appetite ratings, mood state, resting metabolic rate, fasting lipids, glucose, and hormonal responses (insulin, leptin, adiponectin, hs-CRP, IGF-1, and cortisol), body composition, and strength. Nighttime intake of CAS significantly (p < 0.05) increased morning satiety (pretraining, 25 ± 5; post-training 41 ± 6) more than WH (pretraining, 34 ± 5; post-training, 35 ± 6) or CHO (pre 40 ± 8, post 43 ± 7). Exercise training increased lean mass and strength, decreased body fat, and improved mood state in all groups. No other differences were noted. Nighttime feeding of CAS combined with exercise training increased morning satiety more than WH or CHO. Nighttime feeding for 4 weeks did not impact insulin sensitivity (assessed via homeostatic model assessment of insulin resistance) when combined with exercise training in obese women. ClinicalTrial.gov: NCT01830946.
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 | 0.000 |
| 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".