Fractional Analysis of Th2‐Type Cytokines in Sequential Samples of Induced Sputum
Bibliographic record
Abstract
BACKGROUND: Recent studies have demonstrated the usefulness of induced sputum in detecting the expression of Th2-type cytokines in asthmatics and have shown that the profile of inflammatory cells in induced sputum differs with time. OBJECTIVE: To determine whether the duration of sputum induction also affects the expression of Th2-type cytokines in induced sputum. METHODS: Induced sputum was collected from eight atopic asthmatics at two separated intervals (5 min each) during a 15 min sputum induction, and each sample was examined separately for cytokine expression and inflammatory cells. Using immunocytochemistry, interleukin (IL)-4 and IL-5 immunoreactivity, T lymphocytes (CD3), eosinophils (major basic protein), neutrophils (elastase), epithelial cells and macrophages (CD68) were compared in the induced sputum obtained from the 0 min to 5 min and the 10 min to 15 min samples. RESULTS: The number of immunoreactive-positive cells expressing IL-4 and IL-5 were significantly higher in the 10 to 15 min induced sputum sample than in the 0 min to 5 min induced sputum sample (P<0.05). The number of eosinophils was also significantly higher in the 10 min to 15 min sample than in the 0 min to 5 min sample (P<0.05). In contrast, the number of neutrophils was significantly higher in the 0 min to 5 min sample than in the 10 min to 15 min sample (P<0.01); T lymphocytes, macrophages and epithelial cells did not differ between the two samples. CONCLUSION: This study demonstrates that the duration of sputum induction significantly affects the profile of inflammatory cells and Th2-type cytokine expression, and underscores the need for the standardization of induced sputum procedure.
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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 | 0.001 | 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) | 0.001 | 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".