The Role of the Microbiome in Gut and Joint Inflammation in Psoriatic Arthritis and Spondyloarthritis
Bibliographic record
Abstract
Spondyloarthritis (SpA) encompasses a group of diseases characterized by an inflammatory arthritis involving both joints and entheses. However, extraarticular symptoms constitute a large element of the pathology and should not be underestimated. Microscopic gut inflammation is observed in 50% of patients with SpA and has been linked to disease activity, underscoring the effect of gut inflammation in SpA. In this review, we discuss the influence of gut microbiota on SpA pathogenesis. A change in microbiota composition has been linked to the development of various inflammatory arthritides, and dysbiosis is a potential factor in the pathogenesis of multiple inflammatory diseases. In this context, several groups have reported the modulatory effects of gut microbiota-derived metabolites on the effect of immune cells. The gut mucosa is populated by several types of regulatory T cells, but also some specialized unconventional innate-like T cells. These cells are predominantly found at mucosal and epithelial barrier sites, where they serve an essential role in modulating host-microbial interplay. Apart from the close association between the composition of the microbiota and inflammatory diseases, the therapeutic value of dysbiosis needs further investigation, and the identification of a causal inflammatory pathway between gut dysbiosis and musculoskeletal inflammation could revolutionize the therapeutic approach in SpA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".