Restoring Balance: Immune Tolerance in Rheumatoid Arthritis
Bibliographic record
Abstract
Rheumatoid arthritis (RA) is a systemic musculoskeletal disease where immune dysregulation and subsequent autoimmunity induce significant synovial joint inflammation and damage, causing pain and disability. RA disease onset is promoted through multifaceted interactions between genetic and environmental risk factors. However, the mechanisms of disease onset are not completely understood and disease-specific treatments are yet to be developed. Current RA treatments include nonspecific disease-modifying antirheumatic drugs (DMARDs) that suppress destructive immune responses and prevent damage. However, DMARDs are not curative, and relapses are common, necessitating lifelong therapy in most patients. Additionally, DMARD-induced systemic immunosuppression increases the risk of serious infections and malignancies. Herein, we review the current understanding of RA disease pathogenesis, with a focus on T and B cell immune tolerance breakdown, and discuss the development of antigen-specific RA therapeutics that aim to restore a state of immune tolerance, with the potential for disease prevention and reduction of treatment-associated adverse effects.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".