Cardiovascular risk profiling among South Asian adults in Hong Kong: a latent class analysis.

Background: South Asians living in urbanized settings are facing disproportionate cardiovascular burden largely attributable to modifiable risk factors. Given the rapid surge in South Asian population in Hong Kong, this study aims to identify and distinguish clusters of cardiovascular risk profiles among community-dwelling South Asian adults.

Methods: Between June 2022 and December 2023, 1181 South Asian adults were recruited through territory-wide outreach health assessments on lifestyle, psychological distress, obesity, clinical cardiovascular conditions, and sociodemographic factors.

A Novel Point-of-Care Prediction Model for Steatotic Liver Disease: Expected Role of Mass Screening in the Global Obesity Crisis.

Background/aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.

Revolutionizing drug delivery: low-intensity pulsed ultrasound (LIPUS)-driven deep penetration into hypoxic tumor microenvironments of cholangiocarcinoma.

Hypoxia is a major obstacle in the treatment of solid tumors because it causes immune escape and therapeutic resistance. Drug penetration into the hypoxic regions of tumor microenvironment (TME) is extremely limited. This study proposes using the unidirectional fluid flow property of low-intensity pulsed ultrasound (LIPUS) to overcome drug penetration limitations in the TME.

A prospective comparison of two computer aided detection systems with different false positive rates in colonoscopy.

This study evaluated the impact of differing false positive (FP) rates in two computer-aided detection (CADe) systems on the clinical effectiveness of artificial intelligence (AI)-assisted colonoscopy. The primary outcomes were adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The ADR in the control, system A (3.

TeloSearchLR: an algorithm to detect novel telomere repeat motifs using long sequencing reads.

Telomeres are eukaryotic chromosome end structures that guard against sequence loss and aberrant chromosome fusions. Telomeric repeat motifs (TRMs), the minimal repeating unit of a telomere, vary from species to species, with some evolutionary clades experiencing a rapid sequence divergence. To explore the full scope of this evolutionary divergence, many bioinformatic tools have been developed to infer novel TRMs using repetitive sequence search on short sequencing reads.