IL-17A-producing CD4+Foxp3+ T cells in chronic pulmonary aspergillosis
Bibliographic record
Abstract
Abstract Chronic pulmonary aspergillosis (CPA) is a severe pulmonary disease caused by aspergillus fumigatus infection. However, immune responses in CPA patients remained to be elucidated. In humans, the CD4+Foxp3+regulatory T cell (Treg) population are classified into the following three subsets based on their expression of CD45RA and Foxp3: CD45RA+Foxp3lo resting Treg cells (subset I), CD45RA−Foxp3high activated Treg cells (subset II), and CD45RA−Foxp3locytokine-secreting non-suppressive cells (subset III). In the present study, we investigated these three CD4+Foxp3+cell subsets and their clinical implication in CPA patients. The frequency of total CD4+Foxp3+ cells did not differ between CPA patients and healthy controls. Whereas the frequency of subset I or II also did not differ between the two groups, the frequency of subset III was significantly increased in CPA patients compared with healthy controls. Interestingly, IL-17A production was observed in the subset III CD4+Foxp3+ T cells, and the frequency of subset III significantly correlated with IL-17A production from the CD4+ T cell population. Moreover, we found that better clinical prognosis, evaluated by less hospitalization incident, was associated with higher IL-17A production from the CD4+ T cell population and higher frequency of subset III CD4+Foxp3+ cells among CPA patients. In summary, the frequency of IL-17A-producing CD4+Foxp3+ T cells was increased and correlated with the frequency of IL-17A+ CD4+ T cells, and the higher frequency of IL-17A-producing CD4+Foxp3+ T cells was related with better clinical prognosis. We suggest that IL-17A-producing CD4+Foxp3+ T cells (subset III) may have a role in Th17 regulation and antifungal immune responses in CPA patients.
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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 | 0.000 |
| 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".