Newly Developed Highly Bioavailable Curcumin Formulation, curcuRouge<sup>TM</sup>, Reduces Neutrophil/Lymphocyte Ratio in the Elderly: A Double-Blind, Placebo-Controlled Clinical Trial
Bibliographic record
Abstract
Elevated neutrophil/lymphocyte ratio (NLR) has been reported as a sensitive marker for predicting poor prognosis in chronic inflammation-based diseases such as stroke, heart failure, cancers, and diabetes, as well as acute inflammatory diseases such as bacterial and viral infections, including COVID-19. NLR is also known to increase with age and is considered to be an aging marker. We conducted a double-blind, placebo-controlled trial in elderly volunteers to examine the effect of a newly developed, highly bioavailable curcumin formulation (curcuRougeTM) on NLR. Both the white blood cell count and the neutrophil rate decreased significantly, and the lymphocyte rate increased significantly from baseline to after curcuRougeTM administration for 4 wk. curcuRougeTM significantly reduced the NLR (p=0.020). On the other hand, in the placebo group, there were no changes in white blood cell count, neutrophil ratio, lymphocyte ratio, or NLR. The present study demonstrates for the first time, in elderly volunteers, that administration of curcuRougeTM significantly reduces NLR, an indicator of prognosis in cardiovascular diseases, cancer, infectious diseases, and aging. Thus, curcuRougeTM might be expected to improve the prognosis of these diseases as well as exhibit anti-aging effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".