Differential Trafficking of Transforming Growth Factor-β Receptors and Ligand in Polarized Epithelial Cells
Bibliographic record
Abstract
Epithelial cells in vivo form tight cell-cell associations that spatially separate distinct apical and basolateral domains. These domains provide discrete cellular processes essential for proper tissue and organ development. Using confocal imaging and selective plasma membrane domain activation, the type I and type II transforming growth factor-beta (TGFbeta) receptors were found to be localized specifically at the basolateral surfaces of polarized Madin-Darby canine kidney (MDCK) cells. Receptors concentrated predominantly at the lateral sites of cell-cell contact, adjacent to the gap junctional complex. Cytoplasmic domain truncations for each receptor resulted in the loss of specific lateral domain targeting and dispersion to both the apical and basal domains. Whereas receptors concentrate basolaterally in regions of direct cell-cell contact in nonpolarized MDCK cell monolayers, receptor staining was absent from areas of noncell contact. In contrast to the defined basolateral polarity observed for the TGFbeta receptor complex, TGFbeta ligand secretion was found to be from the apical surfaces. Confocal imaging of MDCK cells with an antibody to TGFbeta1 confirmed a predominant apical localization, with a stark absence at the basal membrane. These findings indicate that cell adhesion regulates the localization of TGFbeta receptors in polarized epithelial cultures and that the response to TGFbeta is dependent upon the spatial distribution and secretion of TGFbeta receptors and ligand, respectively.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".