efficacy and safety of systemically administered serinol nucleic acid-modified antisense oligonucleotides in mouse kidney.

Nucleic acid medicine encompassing antisense oligonucleotides (ASOs) has garnered interest as a potential avenue for next-generation therapeutics. However, their therapeutic application has been constrained by challenges such as instability, off-target effects, delivery issues, and immunogenic responses. Furthermore, their practical utility in treating kidney diseases remains unrealized.

Small molecules and heat treatments reverse vernalization via epigenetic modification in Arabidopsis.

Monocarpic plants flower only once and then produce seeds. Many monocarpic plants require a cold treatment known as vernalization before they flower. This requirement delays flowering until the plant senses warm temperatures in the spring.

Action of GABAB receptor on local network oscillation in somatosensory cortex of oral part: focusing on NMDA receptor.

The balance of activity between glutamatergic and GABAergic networks is particularly important for oscillatory neural activities in the brain. Here, we investigated the roles of GABA receptors in network oscillation in the oral somatosensory cortex (OSC), focusing on NMDA receptors. Neural oscillation at the frequency of 8-10 Hz was elicited in rat brain slices after caffeine application.

A surgical case of right ventricular outpouching.

Unlabelled: Outpouching of the heart ventricles, especially of the right ventricle, is rare. Here, we report the case of a 60-year-old male, referred to our institution with an outpouched structure at the right ventricular apex. The patient had no cardiac events.

Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predicting cardiovascular risk among Sri Lankans: a cohort study.

Introduction: Models derived from non-Sri Lankan cohorts are used for cardiovascular (CV) risk stratification of Sri Lankans.

Objective: To develop a CV risk prediction model using machine learning (ML) based on data from a Sri Lankan cohort followed up for 10 years, and to compare the predictions with WHO risk charts.

Design: Cohort study.