Characterizing heterogeneity in the response of synovial mesenchymal progenitor cells to synovial macrophages in normal individuals and patients with osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Resident macrophages in OA synovial tissue contribute to synovitis through pro-inflammatory mediators driving cartilage loss. What remains unknown is how these macrophages interact with synovial mesenchymal progenitor cells (sMPCs) in the joint. sMPCs have the potential to undergo chondrogenesis, but for yet unknown reasons, this ability is decreased in OA patients. In this study, we sought to identify if alteration of macrophage activity regulates the chondrogenic capacity of sMPCs. METHODS: An explant model was developed using human synovium obtained from normal individuals and OA patients. These explants were subjected to macrophage depletion and/or cytokine stimulation in order to regulate/deplete the residing macrophage population. Supernatant was collected following a 12-day treatment phase and subjected to inflammatory secretome analysis. sMPCs from the explants were subsequently placed under 21-day chondrogenic differentiation and levels of type II collagen (Col2a), Aggrecan (Acan), and Sox9 gene expression was quantified. RESULTS: Inflammatory secretome analysis from OA patients revealed the presence of pro-inflammatory analytes following pro- and anti-inflammatory cytokine stimulation and/or macrophage depletion. Additionally, chondrogenic differentiation of sMPCs was heterogeneously impacted across all OA patients following pro-/anti-inflammatory cytokine stimulation and/or macrophage depletion. CONCLUSION: Tissue resident synovial macrophages can regulate the chondrogenic differentiation of sMPCs after cytokine stimulation in a patient specific manner. The secretion profile of OA synovium was also responsive to cytokine stimulation and/or macrophage depletion as observed by the largely pro-inflammatory milieu upregulated following cytokine stimulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".