Increased Production of a Proliferation-inducing Ligand (APRIL) by Peripheral Blood Mononuclear Cells Is Associated with Antitopoisomerase I Antibody and More Severe Disease in Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: A proliferation-inducing ligand (APRIL), a member of the tumor necrosis factor (TNF) family, plays a crucial role in the survival of peripheral B cells, and may contribute to the pathogenesis of systemic sclerosis (SSc) through upregulation of autoantibody production and maintenance of autoimmune phenomena. We evaluated the capacity of peripheral blood mononuclear cells from patients with SSc (SSc-PBMC) to produce APRIL; and investigated correlations between production of APRIL by SSc-PBMC and clinical and laboratory features of the disease. METHODS: PBMC from 20 patients with SSc and 14 healthy subjects were incubated in fetal calf serum-supplemented RPMI medium. APRIL levels were determined in cell culture supernatants by ELISA. RESULTS: PBMC from patients with SSc produced significantly more APRIL (961 ± 151 pg/ml/10⁵ cells) than control PBMC (798 ± 219 pg/ml/10⁵ cells; p < 0.01). In patients with SSc, increased production of APRIL was associated with the presence of diffuse skin involvement, scleroderma lung disease, peripheral vasculopathy, greater capillary damage on capillaroscopy, and presence of anti-topoisomerase I (anti-topo I) antibodies. Multivariate regression analysis revealed anti-topo I antibodies as the only independent predictor of high production of APRIL by PBMC. CONCLUSION: Production of APRIL is increased in SSc-PBMC and is associated with the presence of anti-topo I antibodies and more severe disease. Targeting the APRIL pathway might represent a therapeutic possibility for treatment of patients with SSc, in particular those with anti-topo I antibodies.
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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) | 0.002 | 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".