Regulatory T cell dysfunction in lipocalin 2 knockout mice exacerbates serum-induced arthritis (P1326)
Bibliographic record
Abstract
Abstract Lipocalin 2 (Lcn2), a 25KDa innate immune protein, known to be dramatically up regulated in various inflammatory disorders including antibody-mediated arthritis, yet its biological role remains unclear. More recently our studies have suggested that the regulation might be necessary for the initiation and further resolution of inflammatory process. However, the exact mechanism involved in this process is still unknown. In this study, we report that Lcn2 is up regulated up to 5 fold during the course of serum-induced arthritis (SIA) in wild type (WT) mice. Likewise, Lcn2KO mice suffered a severe arthritic disease with elevated systemic proinflammatory cytokines as compared to their WT littermates. Immunological analysis revealed a considerable increase in granulocytic population (Gr1+, CD11b+, CD11c+), and a significant decrease (4.2 fold) in regulatory T cell (CD4+, CD25+ and FoxP3+) population in Lcn2KO arthritic mice as compared to their WT littermates. Accordingly, Lcn2KO mice exhibited a defect in T cell proliferation as compared to their WT counterparts, suggesting a novel role for Lcn2 in splenocyte proliferation and T-reg expansion. Collectively, our data suggests a crucial role of Lcn2 in resolution of arthritic inflammation via T-reg expansion, making it a promising target in designing better therapeutic strategies for the treatment of rheumatoid arthritis.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".