PI3k and Stat3: Oncogenes that are Required for Gap Junctional, Intercellular Communication
Bibliographic record
Abstract
Gap junctional, intercellular communication (GJIC) is interrupted in cells transformed by oncogenes such as activated Src. The Src effector, Ras, is required for this effect, so that Ras inhibition restores GJIC in Src-transformed cells. Interestingly, the inhibition of the Src effector phosphatidyl-inositol-3 kinase (PI3k) or Signal Transducer and Activator of Transcription-3 (Stat3) pathways does not restore GJIC. In the contrary, inhibition of PI3k or Stat3 in non-transformed rodent fibroblasts or epithelial cells or certain human lung carcinoma lines with extensive GJIC inhibits communication, while mutational activation of PI3k or Stat3 increases GJIC. Therefore, it appears that oncogenes such as activated Src have a dual role upon GJIC; acting as inhibitors of communication through the Ras pathway, and as activators through activation of PI3k or Stat3. In the presence of high Src activity the inhibitory functions prevail so that the net effect is gap junction closure. PI3k and Stat3 constitute potent survival signals, so that their inhibition in non-transformed cells triggers apoptosis which, in turn, has been independently demonstrated to suppress GJIC. The interruption of gap junctional communication would confine the apoptotic event to single cells and this might be essential for the maintenance of tissue integrity. We hypothesize that the GJIC activation by PI3k or Stat3 may be linked to their survival function.
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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) | 0.002 | 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".