Effect of high amylose resistant starch (HAM‐RS2) supplementation on biomarkers of inflammation and oxidative stress in hemodialysis patients: a randomized clinical trial
Bibliographic record
Abstract
INTRODUCTION: Systemic inflammation and oxidative stress play a central role in the pathogenesis of cardiovascular disease and numerous other complications of CKD. Recent studies demonstrated that consumption of a diet enriched with amylose (HAM-RS2), attenuates oxidative stress and inflammation, and improves intestinal microbiome in CKD rats. The present study was designed to explore the effect of dietary amylose supplementation in hemodialysis patients. METHODS: Forty-six stable hemodialysis patients were randomized to receive biscuits containing 20 g/day during the first four weeks and 25 g/day in the next four weeks of either HAM-RS2 or wheat-flour. Fasting predialysis blood samples obtained before, during and at the end of trial were processed for biomarkers of oxidative stress and inflammation. FINDINGS: There was no significant difference in baseline clinical or biochemical parameters between the two groups. Serum levels of TNF-α, IL-6, and malondialdehyde declined significantly (P < 0.05) in the HAM-RS2-treated group but remained unchanged in the placebo-treated group. No significant difference was observed in serum Interleukin-1β (IL-1β) and hs-CRP concentrations and total antioxidant activity between two groups. Serum urea and creatinine concentrations significantly declined and severity of constipation improved in HAM-RS2-treated patients (P < 0.05). HAM-RS2 consumption was well tolerated and did not cause discernible side effects. DISCUSSION: Administration of HAM-RS2 for eight weeks significantly reduced levels of inflammatory and oxidative markers in hemodialysis patients confirming the results observed in CKD animals. Long term trials are needed to explore the impact of HAM-RS2 supplementation on clinical outcomes in end stage renal disease population.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".