The pathogenesis of ankylosing spondylitis
Bibliographic record
Abstract
Ankylosing spondylitis (AS) is a chronic inflammatory disease that can cause significant functional complications by affecting the sacroiliac joints and axial skeleton. Despite a longstanding knowledge about the familial associations of this disease, particularly among patients positive for human leukocyte antigen (HLA)-B27, the fundamental pathogenetic mechanism by which this disease arises in genetically susceptible individuals remains ill defined. Furthermore, the molecular predilection for characteristic articular site involvement remains under ongoing investigation. Current theories about the HLA-B27 association range from the presentation of novel arthritogenic peptides, to abnormal autoimmune stimulation, to anomalous microbial tolerance. The immune effectors of this damage include CD4+, CD8+, and natural killer cells, with marked heterogeneity at different sites. Biomechanical stresses may trigger this disease by exposing the body to previously immune-sequestered autoantigens or by providing a route for bacterial seeding. Environmental triggers such as infection have not been definitively established but may represent a primary pathogenic step in a molecular-mimicry process. In this article, the authors review the current literature on the origin and pathophysiology of AS, focusing on genetic and molecular associations, consequent pathomechanisms, and associated triggers. An improved understanding of the sequence of molecular events that predispose and initiate the onset of this disease will allow for more specific and targeted therapy and better avoidance of the significant side effects of systemic immunomodulation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".