Azilsartan ameliorates ventricular hypertrophy in rats suffering from pressure overload-induced cardiac hypertrophy by activating the Keap1-Nrf2 signalling pathway.

Objectives: Investigate if azilsartan protects against myocardial hypertrophy by upregulating nuclear factor erythroid 2-related factor 2 (Nrf2)-mediated pathways.

Methods: Abdominal aortic constriction (AAC)-induced cardiac hypertrophy in rats was applied. Azilsartan or vehicle was administered daily for 6 weeks in sham or AAC rats.

Evolutionary histories of coxsackievirus B5 and swine vesicular disease virus reconstructed by phylodynamic and sequence variation analyses.

Coxsackievirus (CV)-B5 is a common human enterovirus reported worldwide; swine vesicular disease virus (SVDV) is a porcine variant of CV-B5. To clarify the transmission dynamics and molecular basis of host switching between CV-B5 and SVDV, we analysed and compared the VP1 and partial 3D gene regions of these two viruses. Spatiotemporal dynamics of viral transmission were estimated using a Bayesian statistical inference framework.

Synthesis and In Vitro Anti-Influenza Virus Evaluation of Novel Sialic Acid (C-5 and C-9)-Pentacyclic Triterpene Derivatives.

The emergence of drug resistant variants of the influenza virus has led to a great need to identify novel and effective antiviral agents. In our previous study, a series of sialic acid (C-2 and C-4)-pentacyclic triterpene conjugates have been synthesized, and a five-fold more potent antiviral activity was observed when sialic acid was conjugated with pentacyclic triterpene via C-4 than C-2. It was here that we further reported the synthesis and anti-influenza activity of novel sialic acid (C-5 and C-9)-pentacyclic triterpene conjugates.

Phylodynamic Characterization of an Ocular-Tropism Coxsackievirus A24 Variant.

Recent phylodynamic studies have focused on using tree topology patterns to elucidate interactions among the epidemiological, evolutionary, and demographic characteristics of infectious agents. However, because studies of viral phylodynamics tend to focus on epidemic outbreaks, tree topology signatures of tissue-tropism pathogens might not be clearly identified. Therefore, this study used a novel Bayesian evolutionary approach to analyze the A24 variant of coxsackievirus (CV-A24v), an ocular-tropism agent of acute hemorrhagic conjunctivitis.

Phylodynamic reconstruction of the spatiotemporal transmission and demographic history of coxsackievirus B2.

Background: Studies regarding coxsackievirus (CV) tend to focus on epidemic outbreaks, an imbalanced topology is considered to be an indication of acute infection with partial cross-immunity. In enteroviruses, a clear understanding of the characteristics of tree topology, transmission, and its demographic dynamics in viral succession and circulation are essential for identifying prevalence trends in endemic pathogens such as coxsackievirus B2 (CV-B2). This study applied a novel Bayesian evolutionary approach to elucidate the phylodynamic characteristics of CV-B2.

Phylodynamic analysis of the canine distemper virus hemagglutinin gene.

Background: Canine distemper (CD) is one of the most contagious and lethal viral diseases in dogs. Despite the widespread use of vaccines, the prevalence of the CD virus (CDV) has increased at an alarming rate in recent years. In this phylodynamic study, we investigated the spatiotemporal modes of dispersal, viral demographic trends, and effectiveness of vaccines for CDV.

Transmission and Demographic Dynamics of Coxsackievirus B1.

The infectious activity of coxsackievirus B1 (CV-B1) in Taiwan was high from 2008 to 2010, following an alarming increase in severe neonate disease in the United States (US). To examine the relationship between CV-B1 strains isolated in Taiwan and those from other parts of the world, we performed a phylodynamic study using VP1 and partial 3Dpol (414 nt) sequences from 22 strains of CV-B1 isolated in Taiwan (1989-2010) and compared them to sequences from strains isolated worldwide. Phylogenetic trees were constructed by neighbor-joining, maximum likelihood, and Bayesian Monte Carlo Markov Chain methods.