Determinants of Whole-Body Protein Metabolism in Subjects With and Without Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Whole-body protein metabolism is abnormal in suboptimally controlled type 2 diabetes and obesity. We hypothesized that glycemia, insulin resistance, and waist circumference modulate these alterations in type 2 diabetes and, to a lesser extent, in individuals without type 2 diabetes. RESEARCH DESIGN AND METHODS: In 88 lean and obese subjects without and 40 with type 2 diabetes on an inpatient protein-controlled isoenergetic diet for 7 days, whole-body protein turnover was measured using the fed-fasted 60-h oral (15)N-glycine method. Nitrogen flux was determined from urinary (15)N urea and protein synthesis, breakdown and net balance calculated. Indexes of diabetes control, resting energy expenditure (REE), and body composition were assessed. RESULTS: Higher protein turnover in obese subjects was further increased, and net balance was lower in type 2 diabetes. Waist-to-hip ratio and ln homeostasis model assessment of insulin resistance (HOMA-IR) explained 40% of the variance in flux in type 2 diabetes; fat-free mass and lnHOMA-IR explained 62% in subjects without type 2 diabetes. Overall, fasting glucose explained 16% of the variance in net balance. In type 2 diabetes, net balance correlated negatively with fasting glucose in men and positively with hip circumference in women. CONCLUSIONS: Kinetics of whole-body protein metabolism are elevated, and net balance is diminished in type 2 diabetes, independently of obesity. Elevated flux is associated with greater visceral adiposity, REE, and insulin resistance of glucose. In type 2 diabetic men, these alterations worsened with magnitude of hyperglycemia. In type 2 diabetic women, larger hip circumferences may protect against such alterations. Our findings suggest that dietary protein requirements may be greater in type 2 diabetes to offset a reduced net balance, aggravated as glycemia increases, especially in men.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".