Transforming growth factor-β as a differentiating factor for cultured smooth muscle cells
Bibliographic record
Abstract
The aim of the present study was to determine whether the development of supercontractile smooth muscle cells, contributing to the nonspecific hyperreactivity of airways in asthmatic patients, is due to transforming growth factor (TGF)-beta. In cultured smooth muscle cells starved by removal of 10% foetal bovine serum for 7 days, growth arrest was seen; 30% became elongated and demonstrated super contractility. Study of conditioned medium suggested that the differentiating factor was TGF-beta. Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) was carried out on conditioned medium from the arrested cells. Two protein bands were identified as matrix metalloproteinase (MMP)-2 and TGF-beta1. To determine second messenger signalling by SMAD2, Western blotting and confocal microscopy were employed. Conditioned medium from arrested cultures showed the presence of MMP-2 and TGF-beta1, as revealed by SDS-PAGE; 68- and 25-kDa bands were seen. Differentiation was confirmed by upregulation of marker proteins, smooth muscle type myosin heavy chain and myosin light chain kinase. Confirmation was obtained by downregulating these proteins with decorin treatment, which reduces the levels of active TGF-beta and an adenoviral dominant-negative vector coding for a mutated type II TGF-beta-receptor. Activation of second messenger signalling was demonstrated immunocytochemically by the presence of phosphorylated SMAD2 and SMAD4. Transforming growth factor-beta is likely to be the differentiating factor responsible for the development of these supercontractile smooth muscle cells. The development of such cells in vivo after cessation of an asthmatic attack could contribute to the nonspecific hyperreactivity of airways seen in 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 | 0.000 | 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 | 0.001 |
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".