Drosophila Accessory Gland: A Complementary In Vivo Model to Bring New Insight to Prostate Cancer
Bibliographic record
Abstract
Prostate cancer is the most common cancer in aging men. Despite recent progress, there are still few effective treatments to cure its aggressive and metastatic stages. A better understanding of the molecular mechanisms driving disease initiation and progression appears essential to support the development of more efficient therapies and improve patient care. To do so, multiple research models, such as cell culture and mouse models, have been developed over the years and have improved our comprehension of the biology of the disease. Recently, a new model has been added with the use of the Drosophila accessory gland. With a high level of conservation of major signaling pathways implicated in human disease, this functional equivalent of the prostate represents a powerful, inexpensive, and rapid in vivo model to study epithelial carcinogenesis. The purpose of this review is to quickly overview the existing prostate cancer models, including their strengths and limitations. In particular, we discuss how the Drosophila accessory gland can be integrated as a convenient complementary model by bringing new understanding in the mechanisms driving prostate epithelial tumorigenesis, from initiation to metastatic formation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".