A possible link between polyunsaturated fatty acids and uremic toxins from the gut microbiota in hemodialysis patients: A hypothesis
Bibliographic record
Abstract
INTRODUCTION: Indoxyl sulfate (IS) and p-cresyl sulfate (p-CS) are albumin-bound uremic toxins that are difficult to remove by hemodialysis (HD). Human serum albumin (HSA) carries several compounds, including fatty acids that can bind to site II of HSA and represent competing ligands for uremic toxins. The aim of this study was to investigate the association between fatty acids and uremic toxin plasma levels in patients undergoing HD. METHODS: Thirty-three HD patients (51.5% male, 54.9 ± 10.2 years old, 44.63 ± 28.4 months on HD, albumin level of 3.8 ± 0.3 g/dL) were evaluated. The erythrocyte fatty acid content (saturated fatty acid [SFA], monounsaturated fatty acid [MUFA], and polyunsaturated fatty acid [PUFA]) was measured by gas chromatography, and total IS and p-CS plasma levels were measured by reversed-phase high-performance liquid chromatography. FINDINGS: The mean percentages of docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) + DHA and gamma-linolenic (GLA) acid in the erythrocyte membrane were 1.35% ± 0.74%, 1.85% ± 0.79%, and 0.33% ± 0.26%, respectively. The mean levels of IS and p-CS were 19.4 ± 11.9 mg/dL and 101.5 ± 57.2 mg/dL, respectively. There was no significant association between SFA and MUFA and IS and p-CS; however, a negative correlation was found between p-CS and specific PUFAs, and the association between GLA and p-CS levels was retained after adjusting for potential confounding variables (β = -0.49, P = 0.007). DISCUSSION: Polyunsaturated fatty acids may contribute to the decrease in p-CS uremic toxin plasma levels in patients with chronic kidney disease undergoing HD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".