Stat3 Activity Is Required for Gap Junctional Permeability in Normal Rat Liver Epithelial Cells
Bibliographic record
Abstract
Neoplastic transformation by oncogenes such as activated Src is known to suppress gap junctional, intercellular communication (GJIC). One of the Src effector pathways leading to GJIC suppression and transformation is the Ras/Raf/Mek/Erk, so that inhibition of this pathway in vSrc-transformed cells restores GJIC. A distinct Src downstream effector required for neoplasia is the signal transducer and activator of transcription-3 (Stat3). To examine the role of Stat3 upon the Src-mediated, GJIC suppression, Stat3 was downregulated in rat liver epithelial cells expressing activated Src through treatment with the CPA7, Stat3 inhibitor, or through infection with a retroviral vector expressing a Stat3-specific shRNA. GJIC was examined by electroporating the fluorescent dye, Lucifer yellow, into cells grown on two coplanar electrodes of electrically conductive, optically transparent, indium-tin oxide, followed by observation of the migration of the dye to the adjacent, nonelectroporated cells under fluorescence illumination. The results demonstrate that, contrary to inhibition of the Ras pathway, Stat3 inhibition in cells expressing activated Src does not restore GJIC. On the contrary, Stat3 inhibition in normal cells with high GJIC levels eliminated junctional permeability. Therefore, Stat3's function is actually required for the maintenance of junctional permeability, although Stat3 generally promotes growth and in an activated form can act as an oncogene.
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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) | 0.002 | 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".