Cell receptor-ligand interaction, signalling activation and apoptosis
Bibliographic record
Abstract
by arthroscopy of RA patients before starting anti-TNF therapy.The clinical response was determined after 20 weeks of therapy using the EULAR criteria.The genes most significantly associated with the anti-TNF response were validated by quantitative RT-PCR.Changes in ST protein expression induced by anti-TNF therapy were quantified by immunochemistry and Digital Image Analysis.Results: Eleven RA patients were included and a total of 135 genes were found to be differentially expressed between responders and non-responders after multiple test correction.The functional analysis of the overexpressed genes in the non-responder group (n ¼ 76 genes) identified a highly significant enrichment of genes expressed in peripheral blood CD14þ monocytes (similarity score Kappa ¼ 1.00, P ¼ 3.56e-5).We validated by RT-PCR the genes showing the most significant differential expression: PIK3CD (P ¼ 7.11E-18) and CX3CL1 (P ¼ 7.39E-12).Synovial tissue expression of PIK3CD protein before and after 5 months of anti-TNF therapy showed a significant reduction (P ¼ 0.035) only in those patients with a positive clinical response.Conclusion: Our findings suggest that PIK3CD could be a useful biomarker of response to TNF blockade.
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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 | 0.000 |
| 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) | 0.003 | 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".