Enhanced Mortality to Metastatic Bladder Cancer Cell Line MB49 in Vasoactive Intestinal Peptide Gene Knockout Mice
Bibliographic record
Abstract
To identify if the absence of the Vasoactive Intestinal Peptide (VIP) gene enhances susceptibility to death from metastatic bladder cancer, two strains of mice were injected with MB49 murine bladder cancer cells. The growth and spread of the cancer was measured over a period of 4 weeks in C57BL/6 mice and 5 weeks in VIP knock-out (KO) mice. A Kaplan-Meier plot was constructed to compare control C57BL/6 mice and C57BL/6 mice with MB49 vs. VIP KO controls and VIP KO mice with MB49. The wild type (WT) strain (C57BL/6) contained the VIP gene, while the other strain, VIP knock-out backcrossed to C57BL/6 (VIP KO) did not, and was thus unable to endogenously produce VIP. VIP KO mice had increased mortality compared to C57BL/6 mice at 4 weeks. The number of ulcers between both groups was not statistically significant. In vitro studies indicated that the presence VIP in high doses reduced MB49 cell growth, as well as Macrophage Inhibitory Factor (MIF), a growth factor in bladder cancer cells. These findings support the concept that VIP may attenuate susceptibility to death from bladder cancer, and that it exerts its effect via downregulation of MIF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".