Extreme Phenotypic Variability of -Related Disorders in Hearing Loss.

Hearing loss is the most common sensory defect in humans, affecting normal communication. In most cases, hearing loss is a multifactorial disorder caused by both genetic and environmental factors, but single-gene mutations can lead to syndromic or non-syndromic hearing loss. Monoallelic variants in , coding for gamma (γ)-actin, are associated with classical Baraitser-Winter Syndrome type 2 (BRWS2, nonsyndromic deafness, and a variety of clinical presentations not fitting the original BRWS2 description or nonsyndromic deafness.

The MDM2 SNP309 differentially impacts cardiorespiratory fitness in young healthy women and men.

Purpose: Maximal oxygen consumption (VOmax), the predominant index of cardiorespiratory fitness (CRF), is a predictor of whole-body function and longevity in humans. The central cardiac function and the skeletal muscle's capacity to use oxygen are key determinants of VOmax. Murine Double Minute 2 (MDM2), mainly known as an oncogene, could regulate myocardial hypertrophy, skeletal muscle angiogenesis, and oxidative phosphorylation.

Type 2 diabetes and the minor allele of PNPLA3 consistently identify high-risk metabolic dysfunction associated steatotic liver disease.

Background: Association of genetic factors with non-invasive tests (NITs) for MASLD has not been well established.

Methods: Clinical and laboratory data, liver biopsy and/or liver stiffness measurement (LSM) by transient elastography were collected from MASLD patients seen in tertiary care hepatology practices. Minor allele frequency for genomic loci rs641738 (MBOAT7), rs58542926 (TM6SF2), rs738409 (PNPLA3), rs62305723 (HSD1713B) were evaluated for association with high ELF (≥11.

From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management.

The high incidence of venous thromboembolism (VTE) globally and the morbidity and mortality burden associated with the disease make it a pressing issue. Machine learning (ML) can improve VTE prevention, detection, and treatment. The ability of this novel technology to process large amounts of high-dimensional data can help identify new risk factors and better risk stratify patients for thromboprophylaxis.

Automation of multiplex biochemical assays to enhance productivity and reduce cycle time using a modular robotic platform.

Pharmaceutical and biotechnology companies are increasingly being challenged to shorten the cycle time between design, make, test, and analyze (DMTA) compounds. Automation of multiplex assays to obtain multiparameter data on the same robotic run is instrumental in reducing cycle time. Consequently, an increasing need in automated systems to streamline laboratory workflows with the goal to expedite assay cycle time and enhance productivity has grown in industrial and academic institutions in the past decades.