Heightened preclinical dysregulation of distinct adaptive and renal-associated mediators in patients who develop nephritis as they transition to systemic lupus erythematosus classification
Bibliographic record
Abstract
Abstract Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease marked by immune dysregulation. Why some patients have only moderate symptoms and others develop organ-threatening manifestations is unclear. This study evaluates the temporal expression of autoantibodies and cytokines in sera from the Department of Defense Serum Repository during transition from preclinical lupus to SLE in patients (n=83) who do or do not present with nephritis. Patients who met renal criteria (n=30; 36%) did so within 5.2 (±5.5) months of SLE classification (range −5.2 to +12 months). Renal cases experienced earlier onset of autoantibody positivity vs. non-renal cases (mean −3.8 vs −2.6 years relative to SLE classification, p=0.0442). Prior to developing nephritis, renal cases exhibited elevated levels of distinct soluble mediators compared to matched non-renal cases and healthy controls, including adaptive mediators IL-4, IL-5, IL-12, and IFN-γ, chemokines IP-10 and MCP-3, and nephritis-associated mediators SCF and shed TNFRII (all p<0.05), increasing again at the time of nephritis (all p<0.02 compared to pre-nephritis levels). These same mediators were significantly increased at SLE classification in patients with nephritis vs. non-renal patients (all p<0.0001). These data indicate that perturbations in distinct immune mediated inflammatory processes may help identify individuals at high risk of renal involvement for early and continued monitoring and intervention.
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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 | 0.001 | 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".