DcR3 as a diagnostic parameter and risk factor for systemic lupus erythematosus
Bibliographic record
Abstract
In this study, we investigated the diagnostic value of serum death decoy receptor 3 (DcR3) for systemic lupus erythematosus (SLE). The possible pathogenic role of DcR3 in SLE was also assessed. Serum DcR3 levels of 90 SLE patients, 11 patients with rheumatic conditions and 123 healthy controls were determined by ELISA. In all, 43% of the SLE patients, 9% of patients with rheumatic conditions and 2.4% of the normal healthy individuals presented elevated serum DcR3 levels. A higher percentage of DcR3-positive SLE patients, compared with DcR3-negative SLE patients, showed abnormally high serum IgE levels, a surrogate marker of T(h)2-type immune responses. To determine the cause and effect relationship of DcR3 expression and a T(h)2-prone status, we studied young DcR3 transgenic (Tg) mice, whose transgene was driven by an actin promoter. These mice had IL-4 overproduction and augmented serum IgE levels, signs of dominant T(h)2 immune responses. To determine possible SLE pathogenic roles of DcR3, the T-cell-depleted bone marrow of DcR3 Tg mice was transplanted into lethally irradiated syngeneic C57BL/6 female mice. The recipients developed an SLE-like syndrome. They presented anti-dsDNA and anti-nuclear antibodies, along with renal and liver pathology compatible with that of SLE. In total, 90% of Tg bone marrow-transplanted mice, compared with 20% of wild-type bone marrow-transplanted mice, perished within 12 months after the transplantation. Our results showed that serum DcR3 could serve as an additional parameter for SLE diagnosis and that DcR3 secreted from cells of hematopoietic origin was SLE pathogenic in mice.
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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 | 0.001 | 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) | 0.001 | 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".