Increased gut permeability and intestinal inflammation precede arthritis onset in the adjuvant-induced model of arthritis
Bibliographic record
Abstract
Abstract Background Intestinal inflammation, dysbiosis, intestinal permeability (IP), and bacterial translocation (BT) have been identified in patients with spondyloarthritis but the time at which they appear and their contribution to the pathogenesis of the disease is still a matter of debate. Objectives To study the time-course of intestinal inflammation (I-Inf), IP, microbiota modification BT in a rat model of reactive arthritis, the adjuvant-induced arthritis model (AIA). Methods Analysis was performed at 3 phases of arthritis in control and AIA rats: preclinical phase (day 4), onset phase (day 11), and acute phase (day 28). IP was assessed by measuring levels of zonulin and ileal mRNA expression of zonulin. I-inf was assessed by lymphocyte count from rat ileum and by measuring ileal mRNA expression of proinflammatory cytokines. The integrity of the intestinal barrier was evaluated by levels of iFABP. BT and gut microbiota were assessed by LPS, soluble CD14 levels, and 16S RNA sequencing in mesenteric lymph node and by 16S rRNA sequencing in stool, respectively. Results Plasma zonulin levels increased at the preclinical and onset phase in the AIA group. Plasma levels of iFABP were increased in AIA rats at all stages of the arthritis course. The preclinical phase was characterized by a transient dysbiosis and increased mRNA ileal expression of IL-8, IL-33, and IL-17. At the onset phase, TNF-α, IL-23p19, and IL-8 mRNA expression were increased. No changes in cytokines mRNA expression were observed at the acute phase. Increased CD4+ and CD8+ T cell number was measured in the AIA ileum at day 4 and day 11. No increase in BT was observed. Conclusion These data show that intestinal changes precede the development of arthritis but argue against a strict “correlative” model in which arthritis and gut changes are inseparable.
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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 | 0.001 | 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 | 0.002 |
| 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".