Cooperation between IL-7 Receptor and Integrin α2β1 (CD49b) Drives Th17-Mediated Bone Loss
Bibliographic record
Abstract
Th17 cells are critical effectors in inflammation and tissue damage such as bone erosion, but the mechanisms regulating their activation in this process are not fully understood. In this study, we considered the cooperation between cytokine receptors and integrin pathways in Th17-osteoclast function. We found that human Th17 cells coexpress IL-7R and the collagen-binding integrin α2β1 (CD49b), and IL-7 increases their adhesion to collagen via α2β1 integrin. In addition, coengagement of the two receptors in human Th17 cells cooperatively enhanced their IL-17 production and their osteoclastogenic function. The functional cooperation between IL-7R and α2β1 integrin involves activation of the JAK/PI3K/AKT (protein kinase B) and MAPK/ERK pathways. We also showed that IL-7-induced bone loss in vivo is associated with Th17 cell expansion. Moreover, blockade of α2β1 integrin with a neutralizing mAb inhibited IL-7-induced bone loss and osteoclast numbers by reducing Th17 cell numbers in the bone marrow and reducing the production of IL-17 and the receptor activator of NF-κB ligand. Thus, the cooperation between IL-7R and α2β1 integrin can represent an important pathogenic pathway in Th17-osteoclast function associated with inflammatory diseases.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".