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Record W4399258864 · doi:10.1016/j.prp.2024.155381

Implications of c-Myc in the pathogenesis and treatment efficacy of urological cancers

2024· article· en· W4399258864 on OpenAlexaff
Kiavash Hushmandi, Seyed Hassan Saadat, Mehdi Raei, Salman Daneshi, Amir Reza Aref, Noushin Nabavi, Afshin Taheriazam, Mehrdad Hashemi

Bibliographic record

VenuePathology - Research and Practice · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineProstate cancerCancer researchProstateCarcinogenesisCancerMetastasisProto-Oncogene Proteins c-mycOncogeneTargeted therapyOncologyInternal medicineBiologyTranscription factorGene

Abstract

fetched live from OpenAlex

Urological cancers, including prostate, bladder, and renal cancers, are significant causes of death and negatively impact the quality of life for patients. The development and progression of these cancers are linked to the dysregulation of molecular pathways. c-Myc, recognized as an oncogene, exhibits abnormal levels in various types of tumors, and current evidence supports the therapeutic targeting of c-Myc in cancer treatment. This review aims to elucidate the role of c-Myc in driving the progression of urological cancers. c-Myc functions to enhance tumorigenesis and has been documented to increase growth and metastasis in prostate, bladder, and renal cancers. Furthermore, the dysregulation of c-Myc can result in a diminished response to therapy in these cancers. Non-coding RNAs, β-catenin, and XIAP are among the regulators of c-Myc in urological cancers. Targeting and suppressing c-Myc therapeutically for the treatment of these cancers has been explored. Additionally, the expression level of c-Myc may serve as a prognostic factor in clinical settings.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.144

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 head0.106
GPT teacher head0.438
Teacher spread0.332 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations8
Published2024
Admission routes1
Has abstractyes

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