Metabonomics Reveals Drastic Changes in Anti-Inflammatory/Pro-Resolving Polyunsaturated Fatty Acids-Derived Lipid Mediators in Leprosy Disease
Why this work is in the frame
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Bibliographic record
Abstract
Despite considerable efforts over the last decades, our understanding of leprosy pathogenesis remains limited. The complex interplay between pathogens and hosts has profound effects on host metabolism. To explore the metabolic perturbations associated with leprosy, we analyzed the serum metabolome of leprosy patients. Samples collected from lepromatous and tuberculoid patients before and immediately after the conclusion of multidrug therapy (MDT) were subjected to high-throughput metabolic profiling. Our results show marked metabolic alterations during leprosy that subside at the conclusion of MDT. Pathways showing the highest modulation were related to polyunsaturated fatty acid (PUFA) metabolism, with emphasis on anti-inflammatory, pro-resolving omega-3 fatty acids. These results were confirmed by eicosanoid measurements through enzyme-linked immunoassays. Corroborating the repertoire of metabolites altered in sera, metabonomic analysis of skin specimens revealed alterations in the levels of lipids derived from lipase activity, including PUFAs, suggesting a high lipid turnover in highly-infected lesions. Our data suggest that omega-6 and omega-3, PUFA-derived, pro-resolving lipid mediators contribute to reduced tissue damage irrespectively of pathogen burden during leprosy disease. Our results demonstrate the utility of a comprehensive metabonomic approach for identifying potential contributors to disease pathology that may facilitate the development of more targeted treatments for leprosy and other inflammatory diseases.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it