Osteoclast-Primed Foxp3+ CD8 T Cells Induce T-bet, Eomesodermin, and IFN-γ To Regulate Bone Resorption
Bibliographic record
Abstract
Osteoimmunology arose from the recognition that cytokines produced by lymphocytes can affect bone homeostasis. We have previously shown that osteoclasts, cells that resorb bone, act as APCs. Cross-presentation of Ags by osteoclasts leads to expression of CD25 and Foxp3, markers of regulatory T cells in the CD8 T cells. Octeoclast-induced Foxp3(+) CD25(+) regulatory CD8 T cells (OC-iTcREG) suppress priming of CD4 and CD8 T cells by dendritic cells. OC-iTcREG also limit bone resorption by osteoclasts, forming a negative feedback loop. In this study, we show that OC-iTcREG express concurrently T-bet and Eomesodermin (Eomes) and IFN-γ. Pharmacological inhibition of IκK blocked IFN-γ, T-bet, and Eomes production by TcREG Furthermore, we show, using chromatin immunoprecipitation, NF-κB enrichment in the T-bet and Eomes promoters. We demonstrate that IFN-γ produced by TcREG is required for suppression of osteoclastogenesis and for degradation of TNFR-associated factor 6 in osteoclast precursors. The latter prevents signaling by receptor activator of NF-κB ligand needed for osteoclastogenesis. Knockout of IFN-γ rendered TcREG inefficient in preventing actin ring formation in osteoclasts, a process required for bone resorption. TcREG generated in vivo using IFN-γ(-/-) T cells had impaired ability to protect mice from bone resorption and bone loss in response to high-dose receptor activator of NF-κB ligand. The results of this study demonstrate a novel link between NF-κB signaling and induction of IFN-γ in TcREG and establish an important role for IFN-γ in TcREG-mediated protection from bone loss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".