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Kallikreins

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Rotational paper-based electrochemiluminescence immunodevices for sensitive and multiplexed detection of cancer biomarkers.

Analytica chimica acta
This paper describes a novel rotational paper-based analytical device (RPAD) to implement multi-step electrochemiluminescence (ECL) immunoassays. The integrated paper-based rotational valves can be easily controlled by rotating paper discs manually a...

Post prostatectomy outcomes of patients with high-risk prostate cancer treated with neoadjuvant androgen blockade.

Prostate cancer and prostatic diseases
BACKGROUND: Patients with high-risk prostate cancer have an increased likelihood of experiencing a relapse following radical prostatectomy (RP). We previously conducted three neoadjuvant androgen-deprivation therapy (ADT) trials prior to RP in unfavo...

Seven-Month Prostate-Specific Antigen Is Prognostic in Metastatic Hormone-Sensitive Prostate Cancer Treated With Androgen Deprivation With or Without Docetaxel.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Purpose We evaluated the relationship between prostate-specific antigen (PSA) and overall survival in the context of a prospectively randomized clinical trial comparing androgen-deprivation therapy (ADT) plus docetaxel with ADT alone for initial meta...

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

Computational biology and chemistry
The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular...

Prostate Cancer: Early Detection and Assessing Clinical Risk Using Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

Frontiers in immunology
Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of...

Application of machine learning to large in vitro databases to identify drug-cancer cell interactions: azithromycin and KLK6 mutation status.

Oncogene
Recent advances in machine learning promise to yield novel insights by interrogation of large datasets ranging from gene expression and mutation data to CRISPR knockouts and drug screens. We combined existing and new algorithms with available experim...

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Journal of proteome research
Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, t...