Nod-like receptors in inflammatory arthritis
Bibliographic record
Abstract
Nod-like receptors (NLRs) are innate immune receptors that play a key role in sensing components from pathogens and from damaged cells or organelles. NLRs form signaling complexes that can lead to activation of transcription factors or effector caspases - by means of inflammasome activation -Inflammatory arthritis (IA) culminating in promoting inflammation. An increasing body of research supports the role of NLRs in driving pathogenesis of IA, a collection of diseases that include rheumatoid arthritis (RA), psoriatic arthritis (PsA), ankylosing spondylitis, and pediatric arthritis. In this review, we briefly discuss the main drivers of IA diseases and dive into the evidence for - and against - various NLRs in driving these diseases. We also review the studies examining the use of NLR and inflammasome inhibitors as potential therapies for IA.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".