A study protocol to assess the effectiveness of tocotrienol-rich fraction in older adults : a randomised, double-blind, placebo-controlled
Bibliographic record
Abstract
Abstract Background Tocotrienol, a naturally occurring form of vitamin E, has been extensively studied for its potent antioxidant, anti-inflammatory, and immune-stimulating properties. However, the clinical impact of tocotrienol supplementation on older adults' overall health and well-being remains relatively unexplored. This research aims to investigate the efficacy of tocotrienol-rich fraction (TRF), on various health parameters associated with general well-being in individuals aged between 50–75 years. Methods The present study is a randomised, double-blind, placebo-controlled trial designed to investigate the effectiveness of TRF supplementation on overall health in healthy elderly individuals. The study aims to assess the impact of a daily dosage of 200mg of TRF over a period of 6 months. A total of 220 participants are enrolled in the study, with half receiving the placebo and the other half receiving TRF supplementation. The study comprises three endpoints: baseline, 3 months, and 6 months. At each endpoint, various measurements are taken to evaluate different aspects of health. These measurements include blood biochemistry assessments such as liver function tests, renal profile, lipid profile, and full blood count. Oxidative stress markers, including malondialdehyde, advanced glycation end-products, protein carbonyl, and isoprostane, are also evaluated. Immune response markers such as interleukin-6 and tumour necrosis factor-alpha are assessed. Satiety regulation is examined through measurements of leptin and ghrelin. Body composition and skin health parameters, including wrinkling, pigmentation, elasticity, hydration, and sebum secretion, are evaluated. Additionally, arterial stiffness is assessed by arteriography, bone mineral density is measured using dual x-ray absorptiometry, and cognitive function is assessed through the Montreal Cognitive Assessment, Rey Auditory Verbal Learning Test, and digital span, are measured at baseline and at the 6-month endpoint. Discussion By comprehensively evaluating these health aspects, this study seeks to provide valuable insights into the potential benefits of tocotrienol supplementation for promoting the overall health and well-being of the ageing population. Trial registration National Medical Research Register (NMRR), no. NMRR19-2972-51179
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.013 |
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".