Prevention of bladder tumor formation in mice by a novel bone marrow-derived factor, reptimed.
Bibliographic record
Abstract
BACKGROUND: Reptimed is a novel, species-conserved, bone marrow-derived molecule which possesses anti-neoplastic activity. Previously, we established an orthotopic murine bladder tumor (MBT-2) model and reported accurate documentation of the presence and the extent of intravesical involvement of bladder tumor implants using magnetic resonance imaging (MRI) (1). Herein, we investigated the activity of exogenously administered Reptimed in the MBT-2 model. MATERIALS AND METHODS: Intravesicular and intraperitoneal administration of Reptimed concurrently with and following transurethral tumor cell implantation was performed and MBT-2 tumor response was assessed at several time points post tumor implant. RESULTS: Serial MRI scans of Reptimed-treated mice at days 14 to 33 post tumor transplant revealed significant inhibition of bladder tumor growth with no significant tumor growth observed by MRI on day 33 post-implant. The corresponding histological examination of the whole mount bladder sections revealed similar inhibitory effects of Reptimed with respect to the topography and depth of intravesical tumor involvement. In contrast, control, untreated bladders revealed extensive exophytic tumors with deeply invasive transitional cell carcinoma. CONCLUSIONS: These studies demonstrate the anti-tumor effect of Reptimed and highlight its importance as a potential therapy for cancer.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".