Interleukins 4 and 13 Increase Intestinal Epithelial Permeability by a Phosphatidylinositol 3-Kinase Pathway
Bibliographic record
Abstract
Interleukins 4 and 13 can affect their target cells by activation of signal transducer and activator of transcription 6 (STAT 6) or phosphatidylinositol 3-kinase (PI3K). We examined the signal transduction events involved in IL-4 and IL-13 regulation of epithelial paracellular permeability using T84 cells, a model human colonic epithelium. T84 cells treated with IL-4 or IL-13 displayed virtually identical dose- and time-dependent STAT 6 activation as assessed by electrophoretic mobility shift assay (EMSA) and decreases in transepithelial resistance (TER). STAT 6 DNA binding activity was maximal in nuclear extracts 30 min after exposure to IL-4 or IL-13, and TER was maximally reduced by 24 h post-treatment. Pretreatment of epithelia with transcription factor decoys (phosphorothioated DNA oligonucleotides containing the STAT 6 binding site) dramatically reduced STAT 6 activation as detected by EMSA, but did not attenuate the TER reduction by IL-4 or IL-13. In contrast, although the PI3K inhibitors wortmannin and LY294002 did not affect IL-4 or IL-13 STAT 6 activation, they significantly inhibited the ability of either cytokine to lower TER. Thus, we provide evidence for PI3K as the major proximal signaling event in IL-4 and IL-13 regulation of TER and speculate that pharmacological targeting of enterocytic PI3K activity may represent a means to manipulate epithelial permeability.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".