Laminins and TGF-β maintain cell polarity and functionality of human gastric glandular epithelium
Bibliographic record
Abstract
The human gastric glandular epithelium produces a gastric lipase enzyme (HGL) that plays an important role in digestion of dietary triglycerides. To assess the involvement of extracellular matrix components and transforming growth factor-beta1 (TGF-beta1) in the regulation of this enzymic function, normal gastric epithelial cells were cultured on collagen type I, Matrigel, and laminins (LN)-1 and -2 with or without TGF-beta1. Epithelial morphology and HGL expression were evaluated using microscopy techniques, enzymic assays, Western blot, Northern hybridization, and RT-PCR. A correlation was observed between the cell polarity status and the level of HGL expression. TGF-beta1 alone or individual matrix components stimulated cell spreading and caused a downfall of HGL activity and mRNA. By contrast, Matrigel preserved the morphological features of differentiated epithelial cells and maintained HGL expression. The combination of LNs with TGF-beta1 (two constituents of Matrigel) exerted similar beneficial effects on epithelial cell polarity and evoked a 10-fold increase of HGL levels that was blunted by a neutralizing antibody against the alpha(2)-integrin subunit and by mitogen-activated protein kinase (MAPK) inhibitors PD-98059 (p42/p44) or SB-203580 (p38). This investigation demonstrates for the first time that a powerful synergism between a growth factor and basement membrane LNs positively influences cell polarity and functionality of the human gastric glandular epithelium through an activation of the alpha(2)beta(1)-integrin and effectors of two MAPK pathways.
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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 | 0.000 |
| 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".