Effect of soy protein-rich diet on renal function in young adults with insulin-dependent diabetes mellitus
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Diabetic nephropathy is the most frequent cause of end-stage renal disease in the Western world. Dietary intake, including protein amount and type, seems to affect the progression of renal disease. This pilot study tested the hypothesis that substituting soy protein for animal protein in the diets of diabetics would help correct glomerular hyperfiltration. METHODS: Twelve young adults (aged 29.9 +/- 2.4 years) with type 1 diabetes mellitus (duration of diabetes 15.1 +/- 2.3 years) and hyperfiltration (glomerular filtration rate, GFR > 120 ml/min/1.73 m2) completed a crossover, dietary intervention trial. After a four-week assessment of baseline characteristics and dietary habits, subjects were assigned to either a control or soy diet for eight weeks after which each subject was crossed over to the alternative diet for another eight-week period. RESULTS: Mean GFR was significantly reduced (p < 0.02) after eight weeks on the soy diet (143 +/- 7.4 ml/min/1.73 m2) compared with baseline (159 +/- 7.7 ml/min/ 1.73 m2) and control diets (161 +/- 10.0 ml/min/1.73 m2). Urinary excretion of the soy isoflavones was significantly higher (p < 0.01) at the end of the soy diet (genistein 1,014.6 +/- 274.1 nmol/h, daidzein 2,645.1 +/- 989.6 nmol/h) compared with baseline (genistein 53.7 +/- 31.1 nmol/h, daidzein 151.1 +/- 74.1 nmol/h) and control diets (genistein 41.1 +/- 13.3 nmol/h, daidzein 127.5 +/- 54.0 nmol/h). The soy diet significantly reduced total and LDL cholesterol by 7% and 9%, respectively. CONCLUSIONS: Implementation of a soy-based diet appears to reduce the GFR and total and LDL cholesterol of young adults with type 1 diabetes and glomerular hyperfiltration, thus affecting positively their clinical profile.
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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 | 0.002 | 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) | 0.000 | 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 it