Bystander effect induced changes in apoptosis related proteins and terminal differentiation in<i>in vitro</i>murine bladder cultures
Bibliographic record
Abstract
PURPOSE: Radiation-induced bystander effects are now an established phenomenon seen in numerous cell and tissue culture models. The aim of this investigation was to examine the bystander signal and response in a multicellular primary tissue culture system in vitro. METHODS AND MATERIALS: Murine bladder samples were explanted and directly exposed to gamma radiation, or treated with irradiated tissue conditioned medium (ITCM) generated from the directly irradiated cultures. RESULTS: Results indicated that there was a strong bystander signal produced by the tissue that caused both dose-dependent and -independent changes in the ITCM treated tissue. Significantly increased B-cell lymphoma 2 (Bcl2) expression was noted after treatment with 0.5Gy and 5Gy ITCM (approximately 80%), while dose-dependent changes were observed in c-myelocytomatosis (cMyc) (39.48% at 0.5 Gy ITCM, 81.28% at 5 Gy ITCM) and the terminal differentiation marker uroplakin III (17.88% at 0.5 Gy). Nuclear fragmentation was also significantly increased at both doses of ITCM. CONCLUSION: These data suggest that the bystander signal produced in a multicellular environment induces complex changes in the ITCM-treated culture, and that these changes are reflective of a coordinated response to maintain integrity throughout the tissue.
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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 | 0.000 |
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".