The biosynthesis of nanoparticles has received increasing attention due to the growing need to develop safe, cost-effective and environmentally friendly technologies for nano-materials synthesis. In this report, silver nanoparticles (AgNPs) were synthesized using a reduction of aqueous Ag+ ion with the culture supernatants of Aspergillus terreus. The reaction occurred at ambient temperature and in a few hours. The bioreduction of AgNPs was monitored by ultraviolet-visible spectroscopy, and the AgNPs obtained were characterized by transmission electron microscopy and X-ray diffraction. The synthesized AgNPs were polydispersed spherical particles ranging in size from 1 to 20 nm and stabilized in the solution. Reduced nicotinamide adenine dinucleotide (NADH) was found to be an important reducing agent for the biosynthesis, and the formation of AgNPs might be an enzyme-mediated extracellular reaction process. Furthermore, the antimicrobial potential of AgNPs was systematically evaluated. The synthesized AgNPs could efficiently inhibit various pathogenic organisms, including bacteria and fungi. The current research opens a new avenue for the green synthesis of nano-materials.

Motivation: Haplotype inference is an important step for many types of analyses of genetic variation in the human genome. Traditional approaches for obtaining haplotypes involve collecting genotype information from a population of individuals and then applying a haplotype inference algorithm. The development of high-throughput sequencing technologies allows for an alternative strategy to obtain haplotypes by combining sequence fragments. The problem of ‘haplotype assembly’ is the problem of assembling the two haplotypes for a chromosome given the collection of such fragments, or reads, and their locations in the haplotypes, which are pre-determined by mapping the reads to a reference genome. Errors in reads significantly increase the difficulty of the problem and it has been shown that the problem is NP-hard even for reads of length 2. Existing greedy and stochastic algorithms are not guaranteed to find the optimal solutions for the haplotype assembly problem.Results: In this article, we proposed a dynamic programming algorithm that is able to assemble the haplotypes optimally with time complexity O(m × 2k × n), where m is the number of reads, k is the length of the longest read and n is the total number of SNPs in the haplotypes. We also reduce the haplotype assembly problem into the maximum satisfiability problem that can often be solved optimally even when k is large. Taking advantage of the efficiency of our algorithm, we perform simulation experiments demonstrating that the assembly of haplotypes using reads of length typical of the current sequencing technologies is not practical. However, we demonstrate that the combination of this approach and the traditional haplotype phasing approaches allow us to practically construct haplotypes containing both common and rare variants.Contact: danhe@cs.ucla.edu

There is an enormous interest in developing safe, cost-effective and environmentally friendly technologies for nano-materials synthesis. In the present study, extracellular biosynthesis of silver nanoparticles was achieved by Epicoccum nigrum, an endophytic fungus isolated from the cambium of Phellodendron amurense. The reduction of the silver ions was monitored by UV-visible spectrophotometry, and the characterization of the Ag NPs was carried out by X-ray diffraction and transmission electron microscopy. The synthesized Ag NPs were exceptionally stable. It was found that an alkaline pH favored the formation of Ag NPs and elevated temperature accelerated the reduction process. Furthermore, the antifungal activity of the Ag NPs was assessed using a microdilution method. The biosynthesized Ag NPs showed considerable activity against the pathogenic fungi. The current research opens a new path for the green synthesis of Ag NPs and the process is easy to scale up for biomedical applications.

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Bmi-1 is a member of the Polycomb group family of proteins that function in the epigenetic silencing of genes governing self-renewal, differentiation, and proliferation. Bmi-1 was first identified through its ability to accelerate c-Myc-induced lymphomagenesis. Subsequent studies have further supported an oncogenic role for Bmi-1 in several cancers including those of the breast, lung, prostate, and brain. Using a stable and inducible shRNA system to silence Bmi-1 gene expression, we show a novel role for Bmi-1 in regulating the growth and clonogenic capacity of multiple myeloma cells both in vitro and in vivo. Moreover, to elucidate novel gene targets controlled by Bmi-1, global transcriptional profiling studies were performed in the setting of induced loss of Bmi-1 function. We found that the expression of the proapoptotic gene Bim is negatively regulated by Bmi-1 and that Bim knockdown functionally rescues the apoptotic phenotype induced upon loss of Bmi-1. Therefore, these studies not only highlight Bmi-1 as a cancer-dependent factor in multiple myeloma, but also elucidate a novel antiapoptotic mechanism for Bmi-1 function involving the suppression of Bim.