Correlation of CX3CL1 and CX3CR1 Levels with Response to Infliximab Therapy in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the relation between serum chemokine levels and patient responsiveness to infliximab, and the influence of infliximab administration on serum chemokine levels. METHODS: Serum levels of the chemokines CX3CL1, CXCL8, CCL3, and CXCL10 were quantified prior to (at baseline) and after 30 weeks of treatment with infliximab in 20 patients using enzyme-linked immunosorbent assays. Disease status was assessed using the Disease Activity Score (DAS28). The response to infliximab was classified according to the European League Against Rheumatism (EULAR) response criteria. RESULTS: By 30 weeks, infliximab produced a significant overall reduction in DAS28 among the 20 patients with RA, although only 12 achieved a good to moderate response based on EULAR response criteria. A significant reduction in CX3CL1 was seen in the responsive group, although infliximab treatment had no significant effect on the serum levels of the other 3 chemokines. Comparison of patients with lower (<2000 pg/ml) and higher (>or=2000 pg/ml) basal CX3CL1 levels revealed that DAS28, erythrocyte sedimentation rate, C-reactive protein, and CX3CL1 levels were all significantly diminished by infliximab in RA patients with lower basal CX3CL1 levels, but not in those with higher basal levels. In addition, cell-surface expression of CX3CR1 protein in peripheral blood CD8+CD3+ T cells and mRNA expression of CX3CR1 in lymphocytes were both significantly downregulated after infliximab treatment in the responsive group. CONCLUSION: Our results suggest that the CX3CL1-CX3CR1 system in patients with active RA may be sensitive to anti-tumor necrosis factor-alpha therapy, and confirm that CX3CL1 plays a crucial role in the pathogenesis of RA.
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 | 0.002 |
| 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 | 0.001 | 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".