Serum metabolic fingerprinting of psoriasis and psoriatic arthritis patients using solid-phase microextraction—liquid chromatography—high-resolution mass spectrometry
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Bibliographic record
Abstract
INTRODUCTION: Psoriatic arthritis (PsA), an inflammatory arthritis that develops in individuals with psoriasis, is associated with reduced quality of life. Identifying biomarkers associated with development of PsA as well as with PsA disease activity may help management of psoriatic disease. OBJECTIVES: To use metabolomic fingerprinting to determine potential candidate markers of disease conversion (psoriasis to PsA) and/or PsA activity. METHODS: A novel sample preparation protocol based on solid-phase microextraction (SPME) was used to prepare serum samples obtained from: (1) individuals with psoriasis, some of whom develop psoriatic arthritis (n = 20); (2) individuals with varying PsA activity (mild, moderate, severe; n = 10 each) and (3) healthy controls (n = 10). Metabolomic fingerprinting of the obtained extracts was performed using reversed-phase liquid chromatography coupled to high resolution mass spectrometry. RESULTS: Psoriasis patients who developed PsA had similar metabolomic profiles to patients with mild PsA and were also indistinguishable from patients with psoriasis who did not develop PsA. Elevated levels of selected long-chain fatty acids (e.g., 3-hydroxytetradecanedioic acid) that are associated with dysregulation of fatty acid metabolism, were observed in patients with severe PsA. In addition, 1,11-undecanedicarboxylic acid-an unusual fatty acid associated with peroxisomal disorders-was also identified as a classifier in PsA patients vs. healthy individuals. Furthermore, a number of different eicosanoids with either pro- or anti-inflammatory properties were detected solely in serum samples of patients with moderate and severe PsA. CONCLUSION: A global metabolomics approach was employed to analyze the serum metabolome of patients with psoriasis, PsA, and healthy controls in order to examine potential differences in the biochemical profiles at a metabolite level. A closer examination of circulating metabolites may potentially provide markers of PsA activity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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