Reduced T‐bet in addition to enhanced <scp>STAT</scp>6 and <scp>GATA</scp>3 expressing T cells contribute to human allergen‐induced late responses
Bibliographic record
Abstract
BACKGROUND: T-bet and GATA-3 are transcriptional factors involved in Th1 and Th2 cell differentiation, although their concomitant roles at protein levels in target organs during human allergic disease have not been assessed. OBJECTIVES: We investigated the expression of T-bet and GATA-3 in nasal and cutaneous models of Th2 (grass-pollen allergen) and a cutaneous model of Th1 (PPD) responses in man. METHODS: Nasal biopsies were obtained at 8 h and skin biopsies at 8 and 48 h after allergen and PPD challenges, respectively, from 10 allergic rhinitics and 6 non-atopic controls. T cells were assessed using immunofluorescence microscopy. RESULTS: There were increases in CD3(+)STAT6(+)cells (P = 0.01 for nose and skin) and CD3(+)GATA3(+)cells (P = 0.03 for skin) in response to allergen compared with diluent in allergics. When compared with non-atopics after allergen challenge the difference between the two groups was also significant for CD3(+)STAT6(+) (P = 0.001 and 0.03) and for CD3(+)GATA3(+)cells (P = 0.04 and 0.001) for nose and skin respectively. Following PPD challenge CD3(+)STAT4(+)cells and CD3(+)T-bet(+)cells increased in both groups compared with diluent (P = 0.02 and 0.03 for both TFs), whereas only CD3(+)T-bet(+) cells were significantly greater in non-atopics compared with allergics (P = 0.04). The ratio of GATA3(+):T-bet(+) T cells in allergen-induced responses was significantly greater in the allergics (P = 0.008 and 0.01 nose and skin respectively), whereas the ratio of T-bet:GATA3(+)T cells was significantly higher in the non-atopics during PPD-induced responses (P = 0.003). CONCLUSIONS AND CLINICAL RELEVANCE: Dysregulation of Th1 transcription may contribute to heightened expression of STAT6 and GATA3 leading to exaggerated Th2-driven manifestations of allergic disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".