The Effect of a Low Glycemic Index Pulse-Based Diet on Insulin Sensitivity, Insulin Resistance, Bone Resorption and Cardiovascular Risk Factors during Bed Rest
Bibliographic record
Abstract
We determined the effects of a low glycemic-index pulse-based diet (i.e., containing lentils, chick peas, beans, and split peas) compared to a typical hospital diet on insulin sensitivity assessed by the Matsuda index from the insulin and glucose response to a two-hour oral glucose tolerance test, insulin resistance assessed by the homeostatic model assessment of insulin resistance (HOMA-IR), bone resorption assessed by 24 h excretion of urinary n-telopeptides(Ntx) and cardiovascular risk factors (blood lipids, blood pressure, arterial stiffness and heart rate variability) during bed rest. Using a randomized, counter-balanced cross-over design with one-month washout, six healthy individuals (30 ± 12 years) consumed the diets during four days of bed rest. The Matsuda index, HOMA-IR, urinary Ntx and cardiovascular risk factors were determined at baseline and after the last day of bed rest. Compared to the typical hospital diet, the pulse-based diet improved the Matsuda index (indicating increased insulin sensitivity; baseline to post-bed rest: 6.54 ± 1.94 to 6.39 ± 2.71 hospital diet vs. 7.14 ± 2.36 to 8.75 ± 3.13 pulse-based diet; p = 0.017), decreased HOMA-IR (1.38 ± 0.54 to 1.37 ± 0.50 hospital diet vs. 1.48 ± 0.54 to 0.88 ± 0.37 pulse-based diet; p = 0.022), and attenuated the increase in Ntx (+89 ± 75% hospital diet vs. +33 ± 20% pulse-based diet; p = 0.035). No differences for changes in cardiovascular risk factors were found between the two diet conditions, with the exception of decreased diastolic blood pressure during day three of bed rest in the pulse-based versus hospital diet (61 ± 9 vs. 66 ± 7 mmHg; p = 0.03). A pulse-based diet was superior to a hospital diet for maintaining insulin sensitivity, preventing insulin resistance, attenuating bone resorption and decreasing diastolic blood pressure during four days of bed rest.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".