Expansion of myeloid-derived suppressor cells contributes to metabolic osteoarthritis through subchondral bone remodeling
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) subsequent to acute joint injury accounts for a significant proportion of all arthropathies. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of myeloid progenitor cells classically known for potent immune-suppressive activity; however, MDSCs can also differentiate into osteoclasts. In addition, this population is known to be expanded during metabolic disease. The objective of this study was to determine the role of MDSCs in the context of OA pathophysiology. METHODS: In this study, we examined the differentiation and functional capacity of MDSCs to become osteoclasts in vitro and in vivo using mouse models of OA and in MDSC quantitation in humans with OA pathology relative to obesity status. RESULTS: We observed that MDSCs are expanded in mice and humans during obesity. MDSCs were expanded in peripheral blood of OA subjects relative to body mass index and in mice fed a high-fat diet (HFD) compared to mice fed a low-fat diet (LFD). In mice, monocytic MDSC (M-MDSC) was expanded in diet-induced obesity (DIO) with a further expansion after destabilization of the medial meniscus (DMM) surgery to induce post-traumatic OA (PTOA) (compared to sham-operated controls). M-MDSCs from DIO mice had a greater capacity to form osteoclasts in culture with increased subchondral bone osteoclast number. In humans, we observed an expansion of M-MDSCs in peripheral blood and synovial fluid of obese subjects compared to lean subjects with OA. CONCLUSION: These data suggest that MDSCs are reprogrammed in metabolic disease, with the potential to contribute towards OA progression and severity.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".