Soya protein does not affect glycaemic control in adults with type 2 diabetes
Bibliographic record
Abstract
Evidence from observational, animal and human studies supports a role for soya protein and its isoflavones in the improvement of glycaemic control in type 2 diabetes. The objective of the present study was to determine the effect of isoflavone-rich soya protein on markers of glycaemic control in adults with type 2 diabetes. Using a randomised, crossover, double-blind, placebo-controlled design, adults with diet-controlled type 2 diabetes (n 29) consumed soya protein isolate (SPI) and milk protein isolate (MPI) for 57 d each separated by a 4-week washout. Blood was collected on days 1 and 57 of each treatment period for analysis of fasting HbA1C, and fasting and postprandial glucose, insulin and calculated indices of insulin sensitivity and resistance. Urine samples of 24 h were collected at the end of each treatment period for analysis of isoflavones. Urinary isoflavone excretion was significantly greater following consumption of SPI compared with MPI, and 20.7 % of the subjects (n 6) were classified as equol excretors. SPI consumption did not significantly affect fasting or postprandial glucose or insulin, fasting HbA1C, or indices of insulin sensitivity and resistance. These data do not support a role for soya protein in the improvement of glycaemic control in adults with diet-controlled type 2 diabetes and contribute to a limited literature of human studies on the effects of soya protein on the management of type 2 diabetes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".