Mortality Prediction Modeling for Patients with Breast Cancer Based on Explainable Machine Learning.

: Breast cancer is the most common cancer in women worldwide, requiring strategic efforts to reduce its mortality. This study aimed to develop a predictive classification model for breast cancer mortality using real-world data, including various clinical features. : A total of 11,286 patients with breast cancer from the National Cancer Center were included in this study.

Machine Learning for Movement Pattern Changes during Kinect-Based Mixed Reality Exercise Programs in Women with Possible Sarcopenia: Pilot Study.

Background: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to changes in movement patterns, which can increase the risk of falls and other injuries.

Methods: Older women participants aged ≥65 years who could walk independently were recruited and classified into two groups based on knee extension strength (KES).

Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES).

Background: Sarcopenia, characterized by a progressive decline in muscle mass, strength, and function, is primarily attributable to aging. DNA methylation, influenced by both genetic predispositions and environmental exposures, plays a significant role in sarcopenia occurrence. This study employed machine learning (ML) methods to identify differentially methylated probes (DMPs) capable of diagnosing sarcopenia in middle-aged individuals.

Effects of Exercise on Urinary AD7c-NTP (Alzheimer-Associated Neuronal Thread Protein) Levels and Cognitive Function Among Active Korean Elderly: A Randomized Controlled Trial.

Background: Alzheimer-associated neuronal thread protein (AD7c-NTP) has been demonstrated to have high diagnostic accuracy in differentiating Alzheimer's disease (AD) patients from healthy individuals. However, it is yet unclear whether exercise can lower the level of AD7c-NTP in urine among active Korean elderly.

Objective: To assess the effect of exercise on AD7c-ntp levels in urine and cognitive function among active Korean elderly.

Tankyrase-selective inhibitor STP1002 shows preclinical antitumour efficacy without on-target toxicity in the gastrointestinal tract.

Background: Tankyrase inhibition stabilises AXINs and antagonises the Wnt/β-catenin pathway in adenomatous polyposis coli (APC)-mutated colorectal cancer (CRC), suggesting that tankyrase is a potential therapeutic target for APC-mutated CRC. However, clinical trials on reported tankyrase inhibitors have been severely limited by on-target toxicity in the gastrointestinal (GI) tract. Herein, we report a new tankyrase-selective inhibitor, STP1002, having preclinical antitumour efficacy without on-target toxicity in APC-mutated CRC models.

Anticoagulation therapy promotes the tumor immune-microenvironment and potentiates the efficacy of immunotherapy by alleviating hypoxia.

Purpose: Here, this study verifies that cancer-associated thrombosis (CAT) accelerates hypoxia, which is detrimental to the tumor immune microenvironment by limiting tumor perfusion. Therefore, we designed an oral anticoagulant therapy to improve the immunosuppressive tumor microenvironment and potentiate the efficacy of immunotherapy by alleviating tumor hypoxia.

Experimental Design: A novel oral anticoagulant (STP3725) was developed to consistently prevent CAT formation.

A highly potent and safe pyrrolopyridine-based allosteric HIV-1 integrase inhibitor targeting host LEDGF/p75-integrase interaction site.

Allosteric integrase inhibitors (ALLINIs) are a class of experimental anti-HIV agents that target the noncatalytic sites of the viral integrase (IN) and interfere with the IN-viral RNA interaction during viral maturation. Here, we report a highly potent and safe pyrrolopyridine-based ALLINI, STP0404, displaying picomolar IC50 in human PBMCs with a >24,000 therapeutic index against HIV-1. X-ray structural and biochemical analyses revealed that STP0404 binds to the host LEDGF/p75 protein binding pocket of the IN dimer, which induces aberrant IN oligomerization and blocks the IN-RNA interaction.