Hopeahainol A attenuates memory deficits by targeting β‐amyloid in APP/PS1 transgenic mice

Increasing evidence demonstrates that amyloid beta (Aβ) elicits mitochondrial dysfunction and oxidative stress, which contributes to the pathogenesis of Alzheimer's disease (AD). Identification of the molecules targeting Aβ is thus of particular significance in the treatment of AD. Hopeahainol A (HopA), a polyphenol with a novel skeleton obtained from Hopea hainanensis, is potentially acetylcholinesterase‐inhibitory and anti‐oxidative in H₂O₂‐treated PC12 cells. In this study, we reported that HopA might bind to Aβ_1–42 directly and inhibit the Aβ_1–42 aggregation using a combination of molecular dynamics simulation, binding assay, transmission electron microscopic analysis and staining technique. We also demonstrated that HopA decreased the interaction between Aβ_1–42 and Aβ‐binding alcohol dehydrogenase, which in turn reduced mitochondrial dysfunction and oxidative stress in vivo and in vitro. In addition, HopA was able to rescue the long‐term potentiation induction by protecting synaptic function and attenuate memory deficits in APP/PS1 mice. Our data suggest that HopA might be a promising drug for therapeutic intervention in AD.     

Autophagy and ethanol neurotoxicity

Excessive ethanol exposure is detrimental to the brain. The developing brain is particularly vulnerable to ethanol such that prenatal ethanol exposure causes fetal alcohol spectrum disorders (FASD). Neuronal loss in the brain is the most devastating consequence and is associated with mental retardation and other behavioral deficits observed in FASD. Since alcohol consumption during pregnancy has not declined, it is imperative to elucidate the underlying mechanisms and develop effective therapeutic strategies. One cellular mechanism that acts as a protective response for the central nervous system (CNS) is autophagy. Autophagy regulates lysosomal turnover of organelles and proteins within cells, and is involved in cell differentiation, survival, metabolism, and immunity. We have recently shown that ethanol activates autophagy in the developing brain. The autophagic preconditioning alleviates ethanol-induced neuron apoptosis, whereas inhibition of autophagy potentiates ethanol-stimulated reactive oxygen species (ROS) and exacerbates ethanol-induced neuroapoptosis. The expression of genes encoding proteins required for autophagy in the CNS is developmentally regulated; their levels are much lower during an ethanol-sensitive period than during an ethanol-resistant period. Ethanol may stimulate autophagy through multiple mechanisms; these include induction of oxidative stress and endoplasmic reticulum stress, modulation of MTOR and AMPK signaling, alterations in BCL2 family proteins, and disruption of intracellular calcium (Ca2+) homeostasis. This review discusses the most recent evidence regarding the involvement of autophagy in ethanol-mediated neurotoxicity as well as the potential therapeutic approach of targeting autophagic pathways.     

Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection

Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B₂, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169–SOHLH2, both of which are related to gamete functions. We further applied B₂ on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.     

Large scale maximum average power multiple inference on time-course count data with application to RNA-seq analysis

Experiments that longitudinally collect RNA sequencing (RNA-seq) data can provide transformative insights in biology research by revealing the dynamic patterns of genes. Such experiments create a great demand for new analytic approaches to identify differentially expressed (DE) genes based on large-scale time-course count data. Existing methods, however, are suboptimal with respect to power and may lack theoretical justification. Furthermore, most existing tests are designed to distinguish among conditions based on overall differential patterns across time, though in practice, a variety of composite hypotheses are of more scientific interest. Finally, some current methods may fail to control the false discovery rate. In this paper, we propose a new model and testing procedure to address the above issues simultaneously. Specifically, conditional on a latent Gaussian mixture with evolving means, we model the data by negative binomial distributions. Motivated by Storey (2007) and Hwang and Liu (2010), we introduce a general testing framework based on the proposed model and show that the proposed test enjoys the optimality property of maximum average power. The test allows not only identification of traditional DE genes but also testing of a variety of composite hypotheses of biological interest. We establish the identifiability of the proposed model, implement the proposed method via efficient algorithms, and demonstrate its good performance via simulation studies. The procedure reveals interesting biological insights, when applied to data from an experiment that examines the effect of varying light environments on the fundamental physiology of the marine diatom Phaeodactylum tricornutum.     

A Bayesian nonparametric testing procedure for paired samples

We propose a Bayesian hypothesis testing procedure for comparing the distributions of paired samples. The procedure is based on a flexible model for the joint distribution of both samples. The flexibility is given by a mixture of Dirichlet processes. Our proposal uses a spike-slab prior specification for the base measure of the Dirichlet process and a particular parametrization for the kernel of the mixture in order to facilitate comparisons and posterior inference. The joint model allows us to derive the marginal distributions and test whether they differ or not. The procedure exploits the correlation between samples, relaxes the parametric assumptions, and detects possible differences throughout the entire distributions. A Monte Carlo simulation study comparing the performance of this strategy to other traditional alternatives is provided. Finally, we apply the proposed approach to spirometry data collected in the United States to investigate changes in pulmonary function in children and adolescents in response to air polluting factors.     

Herbal remedies for the management of seed-borne fungal pathogens by an edible plant Decalepis hamiltonii (Wight & Arn)

Abstract

Antifungal activity-guided assay of solvent extracts of Decalepis hamiltonii (Wight & Arn) (Asclepiadaceae) against important phytopathogenic fungi, known to cause diseases in sorghum, maize and paddy proved to be highly significant. Among the five solvent extracts tested, Petroleum ether extract showed highly significant antifungal activity. Phytochemical analysis revealed that the antifungal active principle is a phenolic compound. TLC separation of the phenolic fraction using chloroform as an eluting solvent revealed the presence of seven bands but the antifungal activity was observed only in band five with R_f value 0.77. The antifungal active compound is identified as 2-hydroxy-4-methoxybenzaldehyde based on Nuclear Magnetic Resonance (NMR) and mass spectral analysis. The Minimal inhibitory concentration (MIC) varied between 200 μg ml^?1 and 700 μg ml^?1 depending on the fungal species. Seed treatment of the active principle significantly increased seed germination and seed vigour with a corresponding decrease in seed mycoflora. The antifungal active compound was effective against all the 24 fungal species tested suggesting broad-spectrum antifungal activity. Comparative evaluation of the active principle with the synthetic fungicides revealed that the antifungal activity of the active principle obtained from the plant is better than that of synthetic fungicide. This plant being an edible one can be exploited in the management of seed-borne pathogenic fungi and the prevention of biodeterioration of grains and mycotoxin elaboration during storage.     

Biological control of onion leaf blight disease by bulb and foliar application of powder formulation of antagonist mixture

Abstract

Three antagonists: Pseudomonas fluorescens (Pf1), Bacillus subtilis and Trichoderma viride, were tested alone and in combination for suppression of onion leaf blight (Alternaria palandui) disease under glasshouse and field conditions. The average mean of disease reduction was 24.81% for single strains and 42.44% for mixtures. In addition to disease suppression, treatment with a mixture of antagonists promoted plant growth in terms of increased plant height and ultimately bulb yield. Though seed treatment of either single strain or strain mixtures alone could reduce the disease, subsequent application to root, leaves or soil further reduced the disease and enhanced the plant growth. The mixture consisting of Pseudomonas fluorescens Pf1 plus Bacillus subtilis plus Trichoderma viride was the most effective in reducing the disease and in promoting plant growth and bulb yield in greenhouse and field tests.     

Association of genetic polymorphisms in ADH and ALDH2 with risk of coronary artery disease and myocardial infarction: A meta-analysis

Alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) are the major enzymes responsible for alcohol metabolism in humans. Emerging evidences have shown that functional polymorphisms in ADH and ALDH genes might play a critical role in increasing coronary artery disease (CAD) and myocardial infarction (MI) risks; however, individually published studies showed inconclusive results. The aim of this meta-analysis is to evaluate the associations between the genetic polymorphisms of ADH and ALDH genes with susceptibility to CAD and MI. A literature search was conducted on PubMed, Embase, Web of Science and Chinese BioMedical databases from inception through December 1st, 2012. Crude relative risks (RRs) with 95% confidence intervals (CIs) were calculated. Twelve case–control studies were included with a total of 9616 subjects, including 2053 CAD patients, 1436 MI patients, and 6127 healthy controls. Meta-analysis showed that mutant genotypes (GA + AA) of the rs671 polymorphism in the ALDH2 gene were associated with increased risk of both CAD and MI (CAD: RR = 1.20, 95%CI: 1.03–1.40, P = 0.021; MI: RR = 1.32, 95%CI: 1.11–1.57, P = 0.002). However, there were no significant associations of ADH genetic polymorphisms to CAD and MI risks (CAD: RR = 0.92, 95%CI: 0.73–1.15, P = 0.445; MI: RR = 0.93, 95%CI: 0.84–1.03, P = 0.148). In conclusion, this meta-analysis provides strong evidence that ALDH2 rs671 polymorphism may be associated with increased risks of CAD and MI. However, further studies are still needed to accurately determine whether ADH genetic polymorphisms are associated with susceptibility to CAD and MI.