Additional file 1 of Lipoxygenase-derived oxylipins are enriched in anti-citrullinated protein antibody (ACPA)-positive individuals at risk for developing rheumatoid arthritis
Bibliographic record
Abstract
Additional file1: Table S1. Effect of storage time on the levels of individual FAs – Columns highlighted in bold represent FAs that showed significant differential expression. Data was analyzed by student t test (assuming unequal variance) and q<0.05 was considered significant. Benjamini-Hochberg method was used to correct of false discovery rate (represented as q-values). Table S2. Clinical features of ACPA− and ACPA+ FDR. RF=rheumatoid factor; CRP = C-reactive protein; DAS28 = disease activity score 28; anti-CCP = anti-cyclic citrullinated protein antibodies; BMI = Body Mass Index. #Pearson Chi-square test; $Mann-Whitney U test; statistically significant values are indicated in bold. ‘-‘ indicates absence of any value. Table S3. Characteristics of ACPA+ samples selected for fatty acid and oxylipin analysis, categorized by either i. sample acquired at inception study visit or ii. sample acquired after longitudinal follow-up. Table S4. Table showing differences in FA levels between ACPA+ and ACPA− FDR. Data analyzed Mann-Whitney U test and false-discovery rate was corrected using Benjamini-Hochberg method. Significant values are indicated in bold. Table S5. Table showing differences in individual oxylipin levels between ACPA+ and ACPA− FDR. Data is represented as mean ± SD. P values were obtained after performing Student t-test and correcting for multiple comparisons using Bonferroni-Dunn method. Significant values were indicated in bold. Table S6. Characteristics of ACPA+ and ACPA+ Progressors. Figure S1. (A) Scatter plot showing the total FA levels quantified in samples segregated based on the year of sample collection and the Spearman rank correlation with years of storage. (B) Scatter plot showing the total oxylipins in samples segregated based on the year of sample collection and the Spearman rank correlation with years of storage. (C) Scatter plot showing the concentrations of total FA mass and total oxylipin mass in all individuals segregated based on (+/-) NSAID use. Data analyzed by Mann-Whitney U test. Samples used for this analysis were collected between 2007-2017. (D) Scatter plot showing the concentrations of total FA mass and total oxylipin mass in all individuals segregated based on enzymatic pathway and (+/-) NSAID use. Data analyzed by Mann-Whitney U test. Samples used for this analysis were collected after 2013. Figure S2. Analysis and distribution of FAs in FDR. Samples used for this analysis were collected in/after 2013. Box-Whiskers plots showing the % distribution of serum (A) MUFA and PUFA (B) SFA and UFA and (C) ω3, ω6, ω9, ω7 and ω5 FA subtypes in ACPA− FDR, and ACPA+ FDR. **** = P < 0.0001, ns = not significant; data analyzed by Mann-Whitney U test. Figure S3. Levels of serum oxylipins in ACPA+, ACPA− and ACPA+ Progressors after adjustment for sample storage time. Figure S4. Box-Whiskers plot showing levels of ω3 and ω6 oxylipins in ACPA− FDR (N = 10) and ACPA+ FDR (n = 31). ** = P < 0.01, ns = not significant. Data was analyzed using Mann-Whitney U test. Figure S5. Consensus clustering of oxylipins revealed 8 distinct clusters, 2 of which were higher in ACPA+ FDR samples compared with ACPA−. Analyzed by Wilcoxon rank sum test. MDS: Multi-dimensional scaling. Figure S6. Total Oxylipin levels in ACPA− FDR, ACPA+ FDR, and ACPA+ Progressors (top). Levels of AA-, LA-, DGLA-, ALA-, EPA-, and DHA-derived oxylipins split by group.
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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 | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.873 | 0.147 |
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".