Role of IL-4, IL-13, and STAT6 in inflammation-induced hypercontractility of murine smooth muscle cells
Bibliographic record
Abstract
T helper 2 (Th2) cytokines interleukin (IL)-4 and IL-13, which activate signal transducer and activator of transcription 6 (STAT6) are expressed in the muscularis externa during nematode infection and are candidate mediators of the associated hypercontractility. To determine the locus of action of these cytokines, we examined the IL-4- and IL-13-induced hypercontractility of the isolated muscle cells from STAT6 +/+ and STAT6 -/- mice. We compared the results with cells isolated from Trichinella spiralis-infected STAT6 +/+ and STAT6 -/- mice. Carbamylcholine chloride (Carbachol) induced the contraction of jejunal muscle cells in a concentration-dependent manner maximal contraction (R(max) 26.7 +/- 1.9%). Cells from T. spiralis-infected STAT6 -/- mice showed the hypertrophy (cell lengths 41.4 +/- 0.8 to 89.0 +/- 8.7 microm) and hypercontractility (R(max) 37.5 +/- 1.3%) induced by infection. IL-4Ralpha mRNA was detected in dispersed smooth muscle cells. Incubation of longitudinal muscle-myenteric plexus (LMMP) with IL-4 and IL-13 enhanced Carbachol-induced muscle contraction (R(max) 35.5 +/- 1.9 and 32.4 +/- 2.9%, respectively). Incubation of LMMP from STAT6 -/- mice with IL-4 did not enhance the contraction. The hypercontractility in T. spiralis-infected mice was attenuated in STAT6 -/- mice (P < 0.02). These results indicate both IL-4 and IL-13 induce hypercontractility of muscle cells via the STAT6 pathway, and this is the basis for hypercontractility observed in T. spiralis-infected mice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".