Development of a new class of aromatase inhibitors: design, synthesis and inhibitory activity of 3-phenylchroman-4-one (isoflavanone) derivatives

Aromatase (CYP19) catalyzes the aromatization reaction of androgen substrates to estrogens, the last and rate-limiting step in estrogen biosynthesis. Inhibition of aromatase is a new and promising approach to treat hormone-dependent breast cancer. We present here the design and development of isoflavanone derivatives as potential aromatase inhibitors. Structural modifications were performed on the A and B rings of isoflavanones via microwave-assisted, gold-catalyzed annulation reactions of hydroxyaldehydes and alkynes. The in vitro aromatase inhibition of these compounds was determined by fluorescence-based assays utilizing recombinant human aromatase (baculovirus/insect cell-expressed). The compounds 3-(4-phenoxyphenyl)chroman-4-one (1h), 6-methoxy-3-phenylchroman-4-one (2a) and 3-(pyridin-3-yl)chroman-4-one (3b) exhibited potent inhibitory effects against aromatase with IC(50) values of 2.4 μM, 0.26 μM and 5.8 μM, respectively. Docking simulations were employed to investigate crucial enzyme/inhibitor interactions such as hydrophobic interactions, hydrogen bonding and heme iron coordination. This report provides useful information on aromatase inhibition and serves as a starting point for the development of new flavonoid aromatase inhibitors.     

Chemotography for multi-target SAR analysis in the context of biological pathways

The increasing amount of chemogenomics data, that is, activity measurements of many compounds across a variety of biological targets, allows for better understanding of pharmacology in a broad biological context. Rather than assessing activity at individual biological targets, today understanding of compound interaction with complex biological systems and molecular pathways is often sought in phenotypic screens. This perspective poses novel challenges to structure-activity relationship (SAR) assessment. Today, the bottleneck of drug discovery lies in the understanding of SAR of rich datasets that go beyond single targets in the context of biological pathways, potential off-targets, and complex selectivity profiles. To aid in the understanding and interpretation of such complex SAR, we introduce Chemotography (chemotype chromatography), which encodes chemical space using a color spectrum by combining clustering and multidimensional scaling. Rich biological data in our approach were visualized using spatial dimensions traditionally reserved for chemical space. This allowed us to analyze SAR in the context of target hierarchies and phylogenetic trees, two-target activity scatter plots, and biological pathways. Chemotography, in combination with the Kyoto Encyclopedia of Genes and Genomes (KEGG), also allowed us to extract pathway-relevant SAR from the ChEMBL database. We identified chemotypes showing polypharmacology and selectivity-conferring scaffolds, even in cases where individual compounds have not been tested against all relevant targets. In addition, we analyzed SAR in ChEMBL across the entire Kinome, going beyond individual compounds. Our method combines the strengths of chemical space visualization for SAR analysis and graphical representation of complex biological data. Chemotography is a new paradigm for chemogenomic data visualization and its versatile applications presented here may allow for improved assessment of SAR in biological context, such as phenotypic assay hit lists.     

Simplifier: a web tool to eliminate redundant NGS contigs

Modern genomic sequencing technologies produce a large amount of data with reduced cost per base; however, this data consists of short reads. This reduction in the size of the reads, compared to those obtained with previous methodologies, presents new challenges, including a need for efficient algorithms for the assembly of genomes from short reads and for resolving repetitions. Additionally after abinitio assembly, curation of the hundreds or thousands of contigs generated by assemblers demands considerable time and computational resources. We developed Simplifier, a stand-alone software that selectively eliminates redundant sequences from the collection of contigs generated by ab initio assembly of genomes. Application of Simplifier to data generated by assembly of the genome of Corynebacterium pseudotuberculosis strain 258 reduced the number of contigs generated by ab initio methods from 8,004 to 5,272, a reduction of 34.14%; in addition, N50 increased from 1 kb to 1.5 kb. Processing the contigs of Escherichia coli DH10B with Simplifier reduced the mate-paired library 17.47% and the fragment library 23.91%. Simplifier removed redundant sequences from datasets produced by assemblers, thereby reducing the effort required for finalization of genome assembly in tests with data from Prokaryotic organisms.

Availability

Simplifier is available at http://www.genoma.ufpa.br/rramos/softwares/simplifier.xhtmlIt requires Sun jdk 6 or higher.     

Father absence predicts age at sexual maturity and reproductive timing in British men

Despite the widespread assumption that paternal investment is substantial in our species, previous studies have shown mixed results in relation to the impact of fathers on both offspring survival and reproductive outcomes. Using data from a large representative sample of British men, we tested whether father absence is associated with the timing of reproduction-related events among boys, while controlling for various cues denoting early childhood adversity. We further tested whether the loss of the father at different childhood stages matters, so as to assess whether early life is the most important period or if effects can be seen during later childhood. The results show that father absence before age seven is associated with early reproduction, while father absence between ages 11 and 16 only is associated with delayed voice-breaking (a proxy for puberty), even after adjusting for other factors denoting childhood adversity. We conclude that fathers do exert an influence on male reproductive outcomes, independently of other childhood adversities and that these effects are sensitive to the timing of father absence.     

Nonadherence to treatment protocol in published randomised controlled trials: a review

ABSTRACT: This review aimed to ascertain the extent to which nonadherence to treatment protocol is reported and addressed in a cohort of published analyses of randomised controlled trials (RCTs). One hundred publications of RCTs, randomly selected from those published in BMJ, New England Journal of Medicine, the Journal of the American Medical Association and The Lancet during 2008, were reviewed to determine the extent and nature of reported nonadherence to treatment protocol, and whether statistical methods were used to examine the effect of such nonadherence on both benefit and harms analyses. We also assessed the quality of trial reporting of treatment protocol nonadherence and the quality of reporting of the statistical analysis methods used to investigate such nonadherence. Nonadherence to treatment protocol was reported in 98 of the 100 trials, but reporting on such nonadherence was often vague or incomplete. Forty-two publications did not state how many participants started their randomised treatment. Reporting of treatment initiation and completeness was judged to be inadequate in 64% of trials with short-term interventions and 89% of trials with long-term interventions. More than half (51) of the 98 trials with treatment protocol nonadherence implemented some statistical method to address this issue, most commonly based on per protocol analysis (46) but often labelled as intention to treat (ITT) or modified ITT (23 analyses in 22 trials). The composition of analysis sets for their benefit outcomes were not explained in 57% of trials, and 62% of trials that presented harms analyses did not define harms analysis populations. The majority of defined harms analysis populations (18 out of 26 trials, 69%) were based on actual treatment received, while the majority of trials with undefined harms analysis populations (31 out of 43 trials, 72%) appeared to analyse harms using the ITT approach. Adherence to randomised intervention is poorly considered in the reporting and analysis of published RCTs. The majority of trials are subject to various forms of nonadherence to treatment protocol, and though trialists deal with this nonadherence using a variety of statistical methods and analysis populations, they rarely consider the potential for bias introduced. There is a need for increased awareness of more appropriate causal methods to adjust for departures from treatment protocol, as well as guidance on the appropriate analysis population to use for harms outcomes in the presence of such nonadherence.     

Measurement of a model of implementation for health care: toward a testable theory

ABSTRACT: BACKGROUND: Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a first step in operationalizing Greenhalgh et al.'s model by providing background, rationale, working definitions, and measurement of key constructs. METHODS: A systematic review of the literature was conducted for key words representing 53 separate sub-constructs from six of the model's broad constructs. Using an iterative process, we reviewed existing measures and utilized or adapted items. Where no one measure was deemed appropriate, we developed other items to measure the constructs through consensus. RESULTS: The review and iterative process of team consensus identified three types of data that can been used to operationalize the constructs in the model: survey items, interview questions, and administrative data. Specific examples of each of these are reported. CONCLUSION: Despite limitations, the mixed-methods approach to measurement using the survey, interview measure, and administrative data can facilitate research on implementation by providing investigators with a measurement tool that captures most of the constructs identified by the Greenhalgh model. These measures are currently being used to collect data concerning the implementation of two evidence-based psychotherapies disseminated nationally within Department of Veterans Affairs. Testing of psychometric properties and subsequent refinement should enhance the utility of the measures.     

Bioengineered nisin derivatives with enhanced activity in complex matrices

Nisin A is the best known and most extensively characterized lantibiotic. As it is ribosomally synthesized, bioengineering‐based strategies can be used to generate variants. We have previously demonstrated that bioengineering of the hinge region of nisin A can result in the generation of variants with enhanced anti‐microbial activity against Gram‐positive pathogens. Here we created a larger bank of hinge variant producers and screened for producers that exhibit enhanced bioactivity as assessed by agar‐based assays against a selection of target strains. Further analysis of 12 ‘lead’ variants reveals that in many cases enhanced bioactivity is not attributable to enhanced specific activity but is instead as a consequence of an enhanced ability to diffuse through complex polymers. In the case of two variants, which contain the residues SVA and NAK, respectively, within the hinge region, we demonstrate that this enhanced trait enables the peptides to dramatically outperform nisin A with respect to controlling Listeria monocytogenes in commercially produced chocolate milk that contains carrageenan as a stabilizer.     

Increased hepatic expression of TLR2 and TLR4 in the hepatic inflammation-fibrosis-carcinoma sequence

We evaluated expression of TLR2, TLR4 and proinflammatory genes [NF-κB, TNF-α, cyclooxygenase-2 (COX-2)] in liver samples of patients in different stages of liver disease. Fifteen patients with unexplained transaminases elevation (reference group), 22 with viral chronic hepatitis (hepatitis group), 14 with virus-induced severe fibrosis/cirrhosis (cirrhosis group) and 10 with hepatocarcinoma (hepatocarcinoma group) were consecutively included in the study. Quantification of TLR2, TLR4, NF-κB, TNF-α and COX-2 mRNA was done by real-time RT-PCR and TLR2 and TLR4 protein expression was evaluated by immunohistochemistry. Compared with reference, TLR2 and TLR4 mRNA was increased in hepatitis (TLR2: 2.66?±?0.69; TLR4: 3.11?±?0.79; P?相似文献   

Fc Gamma Receptor IIIB (FcγRIIIB) Polymorphisms Are Associated with Clinical Malaria in Ghanaian Children

Plasmodium falciparum malaria kills nearly a million people annually. Over 90% of these deaths occur in children under five years of age in sub-Saharan Africa. A neutrophil mediated mechanism, the antibody dependent respiratory burst (ADRB), was recently shown to correlate with protection from clinical malaria. Human neutrophils constitutively express Fc gamma receptor-FcγRIIA and FcγRIIIB by which they interact with immunoglobulin (Ig) G (IgG)-subclass antibodies. Polymorphisms in exon 4 of FCGR2A and exon 3 of FCGR3B genes encoding FcγRIIA and FcγRIIIB respectively have been described to alter the affinities of both receptors for IgG. Here, associations between specific polymorphisms, encoding FcγRIIA p.H166R and FcγRIIIB-NA1/NA2/SH variants with clinical malaria were investigated in a longitudinal malaria cohort study. FcγRIIA-p.166H/R was genotyped by gene specific polymerase chain reaction followed by allele specific restriction enzyme digestion. FCGR3B-exon 3 was sequenced in 585 children, aged 1 to 12 years living in a malaria endemic region of Ghana. Multivariate logistic regression analysis found no association between FcγRIIA-166H/R polymorphism and clinical malaria. The A-allele of FCGR3B-c.233C>A (rs5030738) was significantly associated with protection from clinical malaria under two out of three genetic models (additive: p = 0.0061; recessive: p = 0.097; dominant: p = 0.0076) of inheritance. The FcγRIIIB-SH allotype (CTGAAA) containing the 233A-allele (in bold) was associated with protection from malaria (p = 0.049). The FcγRIIIB-NA2*03 allotype (CTGCGA), a variant of the classical FcγRIIIB-NA2 (CTGCAA) was associated with susceptibility to clinical malaria (p = 0.0092). The present study is the first to report an association between a variant of FcγRIIIB-NA2 and susceptibility to clinical malaria and provides justification for further functional characterization of variants of the classical FcγRIIIB allotypes. This would be crucial to the improvement of neutrophil mediated functional assays such as the ADRB assay aimed at assessing the functionality of antibodies induced by candidate malaria vaccines.     

A case-control study estimating accident risk for alcohol, medicines and illegal drugs

Background

The aim of the present study was to assess the risk of having a traffic accident after using alcohol, single drugs, or a combination, and to determine the concentrations at which this risk is significantly increased.

Methods

A population-based case-control study was carried out, collecting whole blood samples of both cases and controls, in which a number of drugs were detected. The risk of having an accident when under the influence of drugs was estimated using logistic regression adjusting for gender, age and time period of accident (cases)/sampling (controls). The main outcome measures were odds ratio (OR) for accident risk associated with single and multiple drug use. In total, 337 cases (negative: 176; positive: 161) and 2726 controls (negative: 2425; positive: 301) were included in the study.

Results

Main findings were that 1) alcohol in general (all the concentrations together) caused an elevated crash risk; 2) cannabis in general also caused an increase in accident risk; at a cut-off of 2 ng/mL THC the risk of having an accident was four times the risk associated with the lowest THC concentrations; 3) when ranking the adjusted OR from lowest to highest risk, alcohol alone or in combination with other drugs was related to a very elevated crash risk, with the highest risk for stimulants combined with sedatives.

Conclusion

The study demonstrated a concentration-dependent crash risk for THC positive drivers. Alcohol and alcohol-drug combinations are by far the most prevalent substances in drivers and subsequently pose the largest risk in traffic, both in terms of risk and scope.