Editorial: The innate immune system in rheumatoid arthritis
Bibliographic record
Abstract
The innate immune system in rheumatoid arthritisRheumatoid arthritis (RA) is a chronic autoimmune-mediated inflammatory disease that affects around 1% of world population.It is the consequence of a failure in self-tolerance mechanisms that facilitate the production of autoantibodies such as rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPAs) (1).Although dysregulated adaptive immune system as a key player in the pathogenesis of RA have been thoroughly investigated, increasing attention is also being paid to the involvement of the innate immune system in RA (2, 3).Cells of the innate immune system, such as monocytes, macrophages, neutrophils, dendritic cells, and innate lymphoid cells (ILCs), have been implicated in the development, chronicity and resolution phase of RA (2, 3).Hence, understanding how the innate immune system participates in the mechanisms of inflammatory processes as well as bone damage of RA is of great importance.Activation of the NLRP3 inflammasome and subsequent induction of proinflammatory cytokines like IL-1b and IL-18 have been demonstrated in both arthritic animal models and RA patients (4-6).Yin et al. reviewed the current evidence of NLRP3 inflammasome involvement in RA pathogenesis, indicating that inhibition of NLRP3 inflammasome-related signaling pathway could be employed as a potential therapeutic target.Platelets are recognized as innate immune cells and elevated circulating platelet numbers are associated with more severe RA (7).Jiang et al. summarized the latest knowledge on the role of platelet activation in the pathogenesis of RA.Indeed, plateletbased therapeutic targets for RA have been explored (8).Osteoclasts are the sole bone-resorbing cells that are responsible for the bone erosion in RA.It has been established that FcgR signaling promotes osteoclast differentiation and bone loss in RA, whereas interferon (IFN) g secreted by immune cells blocks osteoclast activation (9, 10).In this Research Topic, Groetsch et al. investigated the interconnection between the two pathways in regulating osteoclast differentiation in RA.Interestingly, they found that the inhibitory effect of IFNg on human osteoclast differentiation depends on the osteoclast differentiation stage indicating that IFNgR activation inhibits the formation of osteoclasts in Frontiers in Immunology frontiersin.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.024 | 0.021 |
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".