Interleukin-4– and Interleukin-13–Enhanced Transforming Growth Factor- β 2 Production in Cultured Human Bronchial Epithelial Cells Is Attenuated by Interferon- γ
Why this work is in the frame
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Bibliographic record
Abstract
Cytokines derived from lymphocytes are believed to play key roles in a variety of diseases, including airway diseases such as asthma. The current study was designed to evaluate the hypothesis that cytokines derived from Th2 cells, interleukin (IL)-4 and IL-13, might contribute to tissue remodeling by modulating the production of transforming growth factor (TGF)-beta. In addition, the ability of interferon (IFN)-gamma, a cytokine derived from Th1 cells that can antagonize many effects of IL-4 and IL-13, was also assessed for its effects on TGF-beta production. IL-4 and IL-13 both stimulated production of TGF-beta2 release from human bronchial epithelial cells in a time- and concentration-dependent manner. Both with and without acidification, TGF-beta2 were detected. Neither TGF-beta1 nor TGF-beta3 was released. In contrast to the stimulatory effect on human bronchial epithelial cells, neither IL-4 nor IL-13 stimulated release of any TGF-beta isoform from human lung fibroblasts. IFN-gamma reduced both basal, IL-4-, and IL-13-stimulated release of TGF-beta2 in human bronchial epithelial cells. The stimulatory effects of IL-4 and IL-13 and the inhibitory effect of IFN-gamma on TGF-beta2 release were paralleled by mRNA levels, as assessed by real-time reverse transcriptase-polymerase chain reaction (RT-PCR). In summary, the Th2-derived cytokines, IL-4 and IL-13, can stimulate production of TGF-beta from airway epithelial cells but not from lung fibroblasts. IFN-gamma, in contrast, can inhibit TGF-beta2 release both under basal conditions and following IL-4 or IL-13 stimulation. The ability of these cytokines to modulate TGF-beta release may contribute to both normal airway repair and to the development of subepithelial fibrosis in asthma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it