Elevated frequencies of total and MAIT cell subsets in patients with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is characterized by the degeneration of joint cartilage, with concomitant changes in the synovium and subchondral bone. Recently, the inflammatory response and involvement of several types of T-cells has been implicated in the development of OA. This study investigated the frequency of MR1-restricted mucosal-associated invariant T (MAIT) cells in patients with knee OA. METHODS: Forty-five patients recently diagnosed with knee OA and 21 age- and gender-matched healthy controls were recruited for this study. Percentages of circulating MAIT cells were assessed by flow cytometry. Plasma cytokine levels were measured using cytometric bead arrays. Associations between the percentages of MAIT cells, plasma cytokine levels, and clinical parameters of OA (erythrocyte sedimentation rate [ESR] and the Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]) were analyzed using the Spearman correlation test. RESULTS: The percentages of total, CD8αα, and CD8αβ MAIT cells were higher in patients with OA compared to healthy controls. The percentages of total and CD8αα MAIT cells were higher in patients with multi-joint OA (MOA) compared to patients with knee-only OA (KOA). Plasma IFN-γ and TNF-α levels were elevated in patients with OA compared to healthy controls, and there was a positive correlation between plasma IFN-γ levels and the percentages of total, CD8αα, and CD8αβ MAIT cells. Plasma IFN-γ and IL-17 levels were higher in patients with MOA compared to healthy controls or patients with KOA. There were positive correlations between the percentages of total and CD8αα MAIT cells and clinical parameters (ESR and WOMAC scores) in patients with OA or MOA. Binary logistic regression analysis shown the frequency of MAIT cells was associated with the risk of OA. CONCLUSIONS: MAIT cells and their subpopulations were significantly increased in patients with OA and have potential as biological markers of OA disease severity, especially in patients with MOA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".