Inhibition of bladder cancer development by allyl isothiocyanate
Bibliographic record
Abstract
Bladder cancer is one of the common human cancers and also has a very high recurrence rate. There is a great need for agents capable of inhibiting bladder cancer development and recurrence. Here, we report that allyl isothiocyanate (AITC), an ingredient of many common cruciferous vegetables, potently inhibited the proliferation of bladder carcinoma cell lines in vitro [half maximal inhibitory concentration (IC(50)) of 2.7-3.3 microM], which was associated with profound G(2)/M arrest and apoptosis. In contrast, AITC was markedly less toxic to normal human bladder epithelial cells (IC(50) of 69.4 microM). AITC was then evaluated in two rat bladder cancer models in vivo (an orthotopic model and a subcutaneous model). The orthotopic model closely mimics human bladder cancer development and recurrence. We show that a low oral dose of AITC (1 mg/kg) significantly inhibited the development and muscle invasion of the orthotopic bladder cancers but was ineffective against the subcutaneous xenografts of the same cancer cells in the same animals. This differential effect was explained by our finding that urinary levels of AITC equivalent were two to three orders of magnitude higher than that in the plasma and that its levels in the orthotopic cancer tissues were also three orders of magnitude higher than that in the subcutaneous cancer tissues. Moreover, we show that AITC is a multi-targeted agent against bladder cancer. In conclusion, AITC is selectively delivered to bladder cancer tissue through urinary excretion and potently inhibits bladder cancer development and invasion.
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) | 0.000 | 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) | 0.001 | 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".