Circulating T helper 9 cells and increased serum interleukin‐9 levels in patients with knee osteoarthritis
Bibliographic record
Abstract
The purpose of this study was to examine the roles of T helper 9 (Th9) cells and the serum interleukin (IL)-9 level in the pathogenesis of osteoarthritis (OA). The numbers of IL-9(+) CD4(+) CD8(-) T cells, interferon (IFN)-γ+ CD4(+) CD8(-) T cells, IL-4(+) CD4(+) CD8(-) T cells, and IL-17A(+) CD4(+) CD8(-) T cells in 25 OA patients and 13 healthy controls (HC) were examined by flow cytometry. The serum concentrations of IL-9, IL-4, IL-17A, and IFN-γ were also determined. The numbers of CD4(+) CD45RO(+) T cells, Th9 cells, Th1 cells, and Th17 cells in OA patients were significantly higher than those in HCs. Furthermore, serum IL-9, IL-17A, and IFN-γ levels in OA patients were higher than those in HCs. The number of Th9 cells was positively correlated with the number of Th17 cells in OA patients. Furthermore, greater numbers of Th9 cells were positively associated with elevated C-reactive protein, and both Th9 cells and IL-9 levels were positively correlated with the Western Ontario and McMaster Universities Osteoarthritis index in OA patients. Th9 cell numbers and IL-9 levels are correlated with OA patient symptoms and joint functionality and may be a marker of disease activity.
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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 | 0.000 |
| 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".