Synthesis and characterization of hybrid organic-inorganic materials based on sulphonated polyamideimide and silica

The preparation of hybrid organic–inorganic membrane materials based on a sulphonated polyamideimide resin and silica filler has been studied. The method allows the sol–gel process to proceed in the presence of a high molecular weight polyamideimide, resulting in well dispersed silica nanoparticles (<50 nm) within the polymer matrix with chemical bonding between the organic and inorganic phases. Tetraethoxysilane (TEOS) was used as the silica precursor and the organosilicate networks were bonded to the polymer matrix via a coupling agent aminopropyltriethoxysilane (APTrEOS). The structure and properties of these hybrid materials were characterized via a range of techniques including FTIR, TGA, DSC, SEM and contact angle analysis. It was found that the compatibility between organic and inorganic phases has been greatly enhanced by the incorporation of APTrEOS. The thermal stability and hydrophilic properties of hybrid materials have also been significantly improved

Synthetic RGDS peptide attenuates lipopolysaccharide-induced pulmonary inflammation by inhibiting integrin signaled MAP kinase pathways

<p>Abstract</p> <p>Background</p> <p>Synthetic peptides containing the RGD sequence inhibit integrin-related functions in different cell systems. Here, we investigated the effects of synthetic Arg-Gly-Asp-Ser (RGDS) peptide on key inflammatory responses to intratracheal (<it>i.t.</it>) lipopolysaccharide (LPS) treatment and on the integrin signaled mitogen-activated protein (MAP) kinase pathway during the development of acute lung injury.</p> <p>Methods</p> <p>Saline or LPS (1.5 mg/kg) was administered <it>i.t. </it>with or without a single dose of RGDS (1, 2.5, or 5 mg/kg, i.p.), anti-α_vor anti-β₃mAb (5 mg/kg, i.p.). Mice were sacrificed 4 or 24 h post-LPS.</p> <p>Results</p> <p>A pretreatment with RGDS inhibited LPS-induced increases in neutrophil and macrophage numbers, total protein levels and TNF-α and MIP-2 levels, and matrix metalloproteinase-9 activity in bronchoalveolar lavage (BAL) fluid at 4 or 24 h post-LPS treatment. RGDS inhibited LPS-induced phosphorylation of focal adhesion kinase and MAP kinases, including ERK, JNK, and p38 MAP kinase, in lung tissue. Importantly, the inhibition of the inflammatory responses and the kinase pathways were still evident when this peptide was administered 2 h after LPS treatment. Similarly, a blocking antibody against integrin α_vsignificantly inhibited LPS-induced inflammatory cell migration into the lung, protein accumulation and proinflammatory mediator production in BAL fluid, at 4 or 24 h post-LPS. Anti-β₃also inhibited all LPS-induced inflammatory responses, except the accumulation of BAL protein at 24 h post-LPS.</p> <p>Conclusion</p> <p>These results suggest that RGDS with high specificity for α_vintegrins attenuates inflammatory cascade during LPS-induced development of acute lung injury.</p

Abundance of the Quorum-Sensing Factor Ax21 in Four Strains of Stenotrophomonas maltophilia Correlates with Mortality Rate in a New Zebrafish Model of Infection

Stenotrophomonas maltophilia is a Gram-negative pathogen with emerging nosocomial incidence. Little is known about its pathogenesis and the genomic diversity exhibited by clinical isolates complicates the study of pathogenicity and virulence factors. Here, we present a strategy to identify such factors in new clinical isolates of S. maltophilia, incorporating an adult-zebrafish model of S. maltophilia infection to evaluate relative virulence coupled to 2D difference gel electrophoresis to explore underlying differences in protein expression. In this study we report upon three recent clinical isolates and use the collection strain ATCC13637 as a reference. The adult-zebrafish model shows discrimination capacity, i.e. from very low to very high mortality rates, with clinical symptoms very similar to those observed in natural S. maltophilia infections in fish. Strain virulence correlates with resistance to human serum, in agreement with previous studies in mouse and rat and therefore supporting zebrafish as a replacement model. Despite its clinical origin, the collection strain ATCC13637 showed obvious signs of attenuation in zebrafish, with null mortality. Multilocus-sequence-typing analysis revealed that the most virulent strains, UV74 and M30, exhibit the strongest genetic similitude. Differential proteomic analysis led to the identification of 38 proteins with significantly different abundance in the three clinical strains relative to the reference strain. Orthologs of several of these proteins have been already reported to have a role in pathogenesis, virulence or resistance mechanisms thus supporting our strategy. Proof of concept is further provided by protein Ax21, whose abundance is shown here to be directly proportional to mortality in the zebrafish infection model. Indeed, recent studies have demonstrated that this protein is a quorum-sensing-related virulence factor

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding

A multilevel analysis of neighborhood and individual effects on individual smoking and drinking in Taiwan

<p>Abstract</p> <p>Background</p> <p>We assessed direct effects of neighborhood-level characteristics and interactive effects of neighborhood-level characteristics and individual socioeconomic position on adult smoking and drinking, after consideration of individual-level characteristics in Taiwan.</p> <p>Methods</p> <p>Data on individual sociodemographic characteristics, smoking, and drinking were obtained from Taiwan Social Change Survey conducted in 1990, 1995, and 2000. The overall response rate was 67%. A total of 5883 women and men aged over 20 living in 434 neighborhoods were interviewed. Participants' addresses were geocoded and linked with Taiwan census data for measuring neighborhood-level characteristics including neighborhood education, neighborhood concentration of elderly people, and neighborhood social disorganization. The data were analyzed with multilevel binomial regression models.</p> <p>Results</p> <p>Several interaction effects between neighborhood characteristics and individual socioeconomic status (SES) were found in multilevel analyses. Our results indicated that different neighborhood characteristics led to different interaction patterns. For example, neighborhood education had a positive effect on smoking for low SES women, in contrast to a negative effect on smoking for high SES women. This result supports the hypothesis of "relative deprivation," suggesting that poor people living in affluent neighborhoods suffer from relative deprivation and relative standing. On the other hand, neighborhood social disorganization has positive effects on drinking for low SES individuals, but not for high SES individuals. These interactive effects support the hypothesis of the double jeopardy theory, suggesting that living in neighborhoods with high social disorganization will intensify the effects of individual low SES.</p> <p>Conclusion</p> <p>The findings of this study show new evidence for the effects of neighborhood characteristics on individual smoking and drinking in Taiwan, suggesting that more studies are needed to understand neighborhood effects in Asian societies.</p

Nuclear Export and Import of Human Hepatitis B Virus Capsid Protein and Particles

It remains unclear what determines the subcellular localization of hepatitis B virus (HBV) core protein (HBc) and particles. To address this fundamental issue, we have identified four distinct HBc localization signals in the arginine rich domain (ARD) of HBc, using immunofluorescence confocal microscopy and fractionation/Western blot analysis. ARD consists of four tight clustering arginine-rich subdomains. ARD-I and ARD-III are associated with two co-dependent nuclear localization signals (NLS), while ARD-II and ARD-IV behave like two independent nuclear export signals (NES). This conclusion is based on five independent lines of experimental evidence: i) Using an HBV replication system in hepatoma cells, we demonstrated in a double-blind manner that only the HBc of mutant ARD-II+IV, among a total of 15 ARD mutants, can predominantly localize to the nucleus. ii) These results were confirmed using a chimera reporter system by placing mutant or wild type HBc trafficking signals in the heterologous context of SV40 large T antigen (LT). iii) By a heterokaryon or homokaryon analysis, the fusion protein of SV40 LT-HBc ARD appeared to transport from nuclei of transfected donor cells to nuclei of recipient cells, suggesting the existence of an NES in HBc ARD. This putative NES is leptomycin B resistant. iv) We demonstrated by co-immunoprecipitation that HBc ARD can physically interact with a cellular factor TAP/NXF1 (Tip-associated protein/nuclear export factor-1), which is known to be important for nuclear export of mRNA and proteins. Treatment with a TAP-specific siRNA strikingly shifted cytoplasmic HBc to nucleus, and led to a near 7-fold reduction of viral replication, and a near 10-fold reduction in HBsAg secretion. v) HBc of mutant ARD-II+IV was accumulated predominantly in the nucleus in a mouse model by hydrodynamic delivery. In addition to the revised map of NLS, our results suggest that HBc could shuttle rapidly between nucleus and cytoplasm via a novel TAP-dependent NES

Multi-Parametric Analysis and Modeling of Relationships between Mitochondrial Morphology and Apoptosis

Mitochondria exist as a network of interconnected organelles undergoing constant fission and fusion. Current approaches to study mitochondrial morphology are limited by low data sampling coupled with manual identification and classification of complex morphological phenotypes. Here we propose an integrated mechanistic and data-driven modeling approach to analyze heterogeneous, quantified datasets and infer relations between mitochondrial morphology and apoptotic events. We initially performed high-content, multi-parametric measurements of mitochondrial morphological, apoptotic, and energetic states by high-resolution imaging of human breast carcinoma MCF-7 cells. Subsequently, decision tree-based analysis was used to automatically classify networked, fragmented, and swollen mitochondrial subpopulations, at the single-cell level and within cell populations. Our results revealed subtle but significant differences in morphology class distributions in response to various apoptotic stimuli. Furthermore, key mitochondrial functional parameters including mitochondrial membrane potential and Bax activation, were measured under matched conditions. Data-driven fuzzy logic modeling was used to explore the non-linear relationships between mitochondrial morphology and apoptotic signaling, combining morphological and functional data as a single model. Modeling results are in accordance with previous studies, where Bax regulates mitochondrial fragmentation, and mitochondrial morphology influences mitochondrial membrane potential. In summary, we established and validated a platform for mitochondrial morphological and functional analysis that can be readily extended with additional datasets. We further discuss the benefits of a flexible systematic approach for elucidating specific and general relationships between mitochondrial morphology and apoptosis