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Record W3200144780 · doi:10.3390/cells10092387

Drosophila Accessory Gland: A Complementary In Vivo Model to Bring New Insight to Prostate Cancer

2021· review· en· W3200144780 on OpenAlexaff
Amandine Rambur, Marine Vialat, Claude Beaudoin, Corinne Lours-Calet, Jean‐Marc A. Lobaccaro, Silvère Baron, Laurent Morel, Cyrille de Joussineau

Bibliographic record

VenueCells · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsMcGill University Health Centre
FundersLigue Contre le Cancer
KeywordsProstate cancerCarcinogenesisDiseaseProstateMetastasisCancerBiologyIn vivoNeuroscienceDrosophila melanogasterProstate glandDrosophila (subgenus)BioinformaticsCancer researchComputational biologyMedicinePathologyGeneticsGene

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.063
GPT teacher head0.347
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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