Effects of omega-3 polyunsaturated fatty-acid supplementation on neuropathic pain symptoms and sphingosine levels in Mexican-Americans with type 2 diabetes
Bibliographic record
Abstract
Purpose: To determine whether dietary supplementation with omega-3 polyunsaturated fatty acids (PUFAs) reduces neuropathic pain symptoms in Mexican-Americans with type 2 diabetes. Methods: Forty volunteers with type 2 diabetes enrolled in the “En Balance-PLUS” program, which provided weekly nutrition–diabetes education and daily supplementation with 1,000 mg docosahexaenoic acid (DHA)–200 mg eicosapentaenoic acid over 3 months. The study assessed self-reported neuropathic pain symptoms pre/postintervention using the short-form McGill Pain Questionnaire (SF-MPQ), monitored clinical laboratory values at baseline and 3 months, and performed baseline and 3-month metabolomic analysis of plasma samples. Results: A total of 26 participants self-reported neuropathic pain symptoms at baseline. After 3 months of omega-3 PUFA supplementation, participants reported significant improvement in SF-MPQ scores (sensory, affective, and visual analogue scale; P <0.001, P =0.012, and P <0.001, respectively). Untargeted metabolomic analysis revealed that participants in the moderate–high SF-MPQ group had the highest relative plasma sphingosine levels at baseline compared to the low SF-MPQ group ( P =0.0127) and the nonpain group ( P =0.0444). Omega-3 PUFA supplementation increased plasma DHA and reduced plasma sphingosine levels in participants reporting neuropathic pain symptoms ( P <0.001 and P <0.001, respectively). Increased plasma DHA levels significantly correlated with improved SF-MPQ sensory scores ( r =0.425, P =0.030). Improved SF-MPQ scores, however, did not correlate with clinical/laboratory parameters. Conclusion: The data suggest that omega-3 PUFAs dietary supplementation may reduce neuropathic pain symptoms in individuals with type 2 diabetes and correlates with sphingosine levels in the plasma. Keywords: lipotoxicity, painful diabetic neuropathy, health disparities, community intervention, neuroprotection, Latinos
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".