The prevalence of Th17 cells in patients with dilated cardiomyopathy
Bibliographic record
Abstract
PURPOSE: Dilated cardiomyopathy (DCM) is a chronic disease characterized by autoimmunity. Th17 cells are a distinct subset from Th1 and Th2 cells and play crucial regulatory functions in inflammatory and autoimmune processes. The current study was designed to investigate the possible involvement of Th17 cells in DCM. METHODS: Th17 cells were detected in blood from DCM subjects and healthy blood donors using several methods including Th17 frequencies by flow cytometric analysis, cytokine (IL-17, IL-6 and IL-23) secretion by enzyme-linked immunosorbent assay and key transcription factor (RORgammat) by real time-PCR. RESULTS: Patients with DCM demonstrated increased peripheral Th17 cells (2.2+/-1.2% vs 0.4+/-0.3%,P < 0.01), Th17 related cytokines (IL-17: 62.7+/-22.8 vs 15.6+/-8.6pg/ml, IL-6: 40.7+/-16.6 vs 10.9+/-5.3pg/ml, IL-23: 210.7+/-89.9 vs 90.6+/-38.8pg/ml, P < 0.01) and RORgammat (24.6+/-6.5 vs 3.2+/-1.1,P < 0.01) compared with healthy blood donors (HBD). Furthermore, there was a consistent differential sex-defined cytokine profile. Males showed higher frequencies of IL-17, IL-6 and IL-23 than females (IL-17: 70.7+/-20.7 vs 54.7+/-22.2pg/ml, P < 0.01; IL-6: 46.0+/-18.2 vs 35.4+/-13.0pg/ml, P < 0.05; IL-23: 238.1+/-106.2 vs 183.4+/-60.2pg/ml, P < 0.05) in patients with DCM . CONCLUSION: Th17 function is increased in patients with DCM, suggesting a role for Th17 cells in the pathogenesis of DCM.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".