A low-calorie diet with or without interval exercise training improves adiposopathy in obese women
Bibliographic record
Abstract
The objective of this study was to test if a low-calorie diet plus interval exercise (LCD+INT) improves adiposopathy, an endocrine dysfunction, when compared with an energy-deficit–matched LCD in obese women. Subjects (age: 48.2 ± 2.4 years, body mass index: 37.8 ± 1.3 kg/m2) were randomized to a 13-day LCD (n = 12; mixed meals of ∼1200 kcal/day) or LCD+INT (n = 12; 12 sessions of 60 min/day alternating 3 min at 50% and 90% peak heart rate). Exercise was estimated to expend 350 kcal per oxygen uptake–heart rate regression analysis and individuals were refed calories expended to match energy availability between groups. Absolute (post – pre caloric intake) and relative (total daily and exercise energy expenditure relative to calorie intake) energy deficits were calculated. Fitness (peak oxygen uptake) and body composition (BodPod; Cosmed USA Inc.) were measured and a 120-min, 75g oral glucose tolerance test was performed at pre- and post-intervention to assess adiposopathy (i.e., ratio of high molecular weight–adiponectin to leptin) and estimate insulin sensitivity. LCD and LCD+INT had similar absolute (P = 0.55) and relative (P = 0.76) energy deficits. LCD and LCD+INT had similar reductions in fat mass (both P < 0.001), despite LCD inducing greater weight loss (P = 0.02) than LCD+INT. Both treatments improved adiposopathy (P = 0.003) and peripheral insulin sensitivity (P = 0.02). Absolute energy deficit correlated to improved adiposopathy (r = –0.41, P = 0.05), and absolute and relative energy deficits were associated with increased insulin sensitivity (r = –0.47, P = 0.02; and r = –0.40, P = 0.05, respectively), independent of body composition changes and increased peak oxygen uptake. Taken together, LCD, with or without INT, improves adiposopathy in relation to insulin sensitivity in obese women, suggesting that a short-term energy deficit is key for reducing risk of type 2 diabetes.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".