Glucose and protein metabolic responses to an energy‐ but not protein‐ restricted diet in type 2 diabetes
Bibliographic record
Abstract
Abstract Aims To test the effect of energy restriction with maintained protein intake on body composition and on insulin sensitivity of glucose and protein metabolism in adults with type 2 diabetes (T2D). Materials and methods After 3 days of an isoenergetic diet with 1.2 g/kg/d protein, obese adults with T2D (three women, two men) followed a 5‐week diet providing 60% of energy requirements with 45% carbohydrate, and with protein maintained at pre‐intervention level. Isotopic tracers were used to quantify whole‐body glucose (3‐ 3 H‐glucose) and protein ( 13 C‐leucine) metabolism pre‐ (day 4) and post‐intervention (day 39), in the postabsorptive state and during a hyperinsulinaemic, isoglycaemic, isoaminoacidaemic clamp. Body composition was measured using dual‐energy x‐ray absorptiometry. Results After energy restriction, 6% weight loss occurred via total body (11%) and visceral fat losses (25%), but lean mass was preserved. Fasting glucose level, serum insulin level, homeostatic model assessment of insulin resistance index and C‐peptide level decreased significantly (29%, 38%, 54% and 38%, respectively) as did other cardiometabolic risk factors. Between clamp studies, postabsorptive protein turnover and oxidation rates decreased (12% and 32%), resulting in less negative net balance, consistent with protein conservation. The rates of glucose turnover decreased, and glucose metabolic clearance rate improved (24%). During the clamp, protein flux was lower (9%) and breakdown suppressed (12%), and net balance became less negative but not different. Although glucose turnover did not differ, metabolic clearance improved by 47%. Conclusions In obese adults with T2D, an energy‐restricted diet with maintained protein intake of ~1.2 g/kg/d improved the kinetics of protein metabolism (particularly in the postabsorptive state), and preserved lean body mass and increased glucose metabolic clearance rate.
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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 | 0.001 | 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 | 0.001 |
| 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".