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Record W2076068021 · doi:10.2174/187152009788680000

Advances in Development of Inhibitors of 17β-Hydroxysteroid Dehydrogenases

2009· review· en· W2076068021 on OpenAlexfundno aff
Donald Poirier

Bibliographic record

VenueAnti-Cancer Agents in Medicinal Chemistry · 2009
Typereview
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchCentre Hospitalier Universitaire de Québec
KeywordsHydroxysteroid DehydrogenasesChemistryComputational biologyBiologyBiochemistryEnzymeDehydrogenase

Abstract

fetched live from OpenAlex

The 17beta-hydroxysteroid dehydrogenases (17beta-HSDs) are involved in the regulation of estrogens and androgens by catalyzing the reduction of 17-ketosteroids or the oxidation of 17beta hydroxysteroids. The enzyme activities associated with the different 17beta-HSD isoforms are widespread in human tissues, not only in classic steroidogenic tissues but also in a large series of peripheral intracrine tissues. Being involved at the end of steroidogenesis, the numerous members of 17beta-HSD family constitute interesting therapeutic targets for controlling the concentration of estrogens and androgens. Thus, inhibitors of reductive 17beta-HSD isoforms are attractive to block the formation of hydroxysteroids that stimulate estrogeno-sensitive pathologies (breast, ovarian, and endometrium cancers) and androgeno-sensitive pathologies (prostate cancer, benign prostatic hyperplasia, acne, and hirsutism). The inhibitors could be used to block the degradation of estradiol, an attractive strategy for treating osteoporosis and Alzheimer's disease. In addition to their classical use as anti-cancer agents and therapeutic agents, inhibitors of 17beta-HSDs are also useful tools to elucidate the role of these enzymes in particular biological systems. The present review article gives a description of novel inhibitors of 17beta-HSDs that were published in 2003-2006.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.065
GPT teacher head0.393
Teacher spread0.328 · 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 designOther design
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

Citations57
Published2009
Admission routes1
Has abstractyes

Explore more

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