THE TYPE I IFN SIGNATURE BETWEEN PATIENTS WITH RA AND SLE.
Bibliographic record
Abstract
PV231 / #297 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose The purpose of the research was to evaluate IFN signature in patients (pts) with SLE and RA; and the relationship between IFN signature and disease activity Methods The analysis included 20 pts with Rheumatoid Arthritis (RA) (18-woman (90%) and 2-man (10%), Me (IQR) age 61.5 (54-66.5) years; 113pts with SLE (99-woman (87%) and 14 men (13%), age 34 (26-41) years. The control group consisted of 20 healthy donors, comparable in sex and age with the examined patients. We selected 3 genes whose expression was studied (MX1, EPSTI1, RSAD2) to evaluate the “IFN signature.” ‘IFN signature» was calculated as the average expression value of the 3 selected genes (IFN score). The level of matrix metalloproteinase 3 (MMP3) in blood serum the upper limit of normal values did not exceed 19.4 ng/ml (n=30) when sera of healthy donors were examined. Results The baseline expression of MX1, RSAD2, EPST1, IFN score in pts with SLE and RA were significantly higher compared to healthy donors, p<0.05 (Table 1). RSAD2 in pts with SLE was also significantly higher compared to RA. Table 1. The baseline expression between pts with RA, SLE and healthy donors. *p<0.05 between pts and healthy donors, $ p<0.05 between pts with SLE and RA Correlations between disease activity and IFN-stimulated gene expression levels presented in Table 2. In pts with RA, a negative correlation between INF score and IFN-stimulated genes with disease activity indices (DAS28), ESR, CRP, MMP3. A positive correlation between IFN score and IFN-stimulated genes with autoantibodies (ds DNA, ANA hep-2) was found in SLE pts., Table 2. Table 2. Conclusions Thus, the presented results indicate increased expression of IFN-stimulated genes in patients with RA and SLE compared to healthy donors. A positive correlation “IFN signature” with laboratory parameters was found in pts with SLE. The obtained negative correlation of INF signature in patients with RA is probably related to the predominance of IFN β, but this requires clarification due to the limited sampling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.005 | 0.001 |
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".