Guardians on call: neutrophils, macrophages and dendritic cells in arthritis pathogenesis
Bibliographic record
Abstract
Several immune/inflammatory components have been associated with arthritis. The role of monocytes/macrophages in inflammatory arthritis has been explored over the last years; however, the role of other myeloid cells, such as neutrophils and dendritic cells, in driving the pathophysiology of arthritis is largely overlooked. In this article, we aim to discuss literature pointing to the role of these immune cells in inflammatory arthritis and emphasize the multiple and dynamic phenotypic roles these cells can hold either in the persistence or in the resolution of inflammation. We also highlight the interactions between neutrophils, macrophages, and/or dendritic cells in the arthritic joint space. We further discuss pathways and features that may be of importance for characterizing neutrophils and dendritic cells, the phenotype of which can be "reprogrammed" to direct the resolution of inflammation efficiently in the arthritic joint. Identifying novel and patient-tailored approaches for addressing persistent or recurrent inflammation through these cellular pathways, might address unmet needs in arthritis management. Types of arthritides discussed in this review include osteoarthritis, spondyloarthritis and rheumatoid arthritis. Brief reference to the role of these immune cells in the acute gouty inflammation is also included.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".