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Record W2138376454 · doi:10.1517/14712598.4.6.927

Antisense approaches in prostate cancer

2004· review· en· W2138376454 on OpenAlexaff
Kim N., Martin Gleave

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2004
Typereview
Languageen
FieldMedicine
TopicClusterin in disease pathology
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsProstate cancerClusterinCancer researchCancerGeneBiologyOligonucleotideAntisense therapyProstateApoptosisGenetics

Abstract

fetched live from OpenAlex

Patients with hormone refractory prostate cancer have limited treatment options and new therapies are urgently needed. Advances in the understanding of the molecular mechanisms implicated in prostate cancer progression have identified many potential therapeutic gene targets that are involved in apoptosis, growth factors, cell signalling and the androgen receptor (AR). Antisense oligonucleotides are short sequences of synthetic modified DNA that are designed to be complimentary to a selected gene's mRNA and thereby specifically inhibit expression of that gene. The antisense approach continues to hold promise as a therapeutic modality to target genes involved in cancer progression, especially those in which the gene products are not amenable to small molecule inhibition or antibodies. The current status and future direction of a number of antisense oligonucleotides targeting several genes, including BCL-2, BCL-XL, clusterin, the inhibitors of apoptosis (IAP) family, MDM2, protein kinase C-alpha, c-raf, insulin-like growth factor binding proteins and the AR, that have potential clinical use in prostate cancer are reviewed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.418
GPT teacher head0.470
Teacher spread0.053 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2004
Admission routes1
Has abstractyes

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