MétaCan
Menu
Back to cohort
Record W2145735545 · doi:10.1002/ddr.20263

New cancer drugs targeting the biosynthesis of estrogens and androgens

2008· article· en· W2145735545 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDrug Development Research · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsAromataseAntiestrogenSteroid sulfataseEndometrial cancerEnzymeProstate cancerCancerSulfatasePharmacologyAntiandrogenCancer researchChemistryBiologyMedicineInternal medicineBiochemistryBreast cancerSteroidTamoxifenHormone

Abstract

fetched live from OpenAlex

Abstract The enzymes involved in the synthesis of steroids are very interesting therapeutic targets. By reducing the levels of androgens and estrogens that stimulate the proliferation of cancer cells, a potent and selective inhibitor of a key‐steroidogenic enzyme may become an alternative or a complementary strategy to the use of an antiandrogen or an antiestrogen for the treatment of prostate cancer or breast and endometrial cancers, respectively. Five enzymes, namely 17α‐hydroxylase 17α‐lyase, aromatase, 17β‐hydroxysteroid dehydrogenases, 5α‐reductases, and steroid sulfatase were especially studied and found to be interesting targets for the development of inhibitors as potential cancer drugs. The present review will summarize the role of these five enzymes and their inhibitors with a special highlight about the molecules more recently reported in the literature and exhibiting dual therapeutic action. Drug Dev Res 69:304–318, 2008. © 2008 Wiley‐Liss, Inc.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.303
Teacher spread0.279 · 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