Plasma Kynurenine to Tryptophan Ratio Is Not Associated with Undernutrition in Adults but Reduced after Nutrition Intervention: Results from a Community-Based Study in Bangladesh
Bibliographic record
Abstract
Infections and persistent immunological activation are linked to increased kynurenine (KYN) and the KYN-to-Tryptophan (TRP) or KT ratio and may be critical factors in undernutrition. We sought to determine the association between the KT ratio and adult malnutrition, as well as investigate if nutritional supplementation had any influence on the decrease of the KT ratio. A total of 525 undernourished adults aged 18–45 years were recruited and provided a nutrition intervention for 60 feeding days. TRP and KYN concentrations were determined from plasma samples using LC-MS/MS. At baseline, the median (interquartile range (IQR)) TRP, KYN and KT ratios were 24.1 (17.6, 34.3) µmol/L, 0.76 (0.53, 1.18) µmol/L and 30.9 (24.5, 41.7), respectively. Following intervention, the median (IQR) KYN and KT ratios were significantly reduced to 0.713 (0.46, 1.12) µmol/L and 27.5 (21.3, 35.8). The KT ratio was found to be inversely linked with adult BMI (coefficient: −0.09; 95% CI: −0.18, 0.004; p-value = 0.06) but not statistically significant. Additionally, Plasma CRP was correlated positively, while LRP1 was inversely correlated with the KT ratio. Our data suggest that in Bangladeshi adults, the KT ratio is not related to the pathophysiology of malnutrition but correlated with inflammatory and anti-inflammatory biomarkers, and the ratio can be reduced by a nutrition intervention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".