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Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prost...

Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prost...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11432266

Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prostate Cancer among Patients with Moderately Altered PSA Levels

About this item

Full title

Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prostate Cancer among Patients with Moderately Altered PSA Levels

Publisher

Switzerland: MDPI AG

Journal title

International journal of molecular sciences, 2024-09, Vol.25 (18), p.10122

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

PSA screening has led to an over-diagnosis of prostate cancer (PCa) and unnecessary biopsies of benign conditions due to its low cancer specificity. Consequently, more accurate, preferentially non-invasive, tests are needed. We aim to evaluate the potential of semen sEV (small extracellular vesicles) tsRNAs (tRNA-derived small RNAs) as PCa indicato...

Alternative Titles

Full title

Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prostate Cancer among Patients with Moderately Altered PSA Levels

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11432266

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11432266

Other Identifiers

ISSN

1422-0067,1661-6596

E-ISSN

1422-0067

DOI

10.3390/ijms251810122

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