Synthesis and Antiproliferative Activities of Novel Substituted 5‐Anilino‐α‐Glucofuranose Derivatives

In order to find novel antitumor candidate agents with high efficiency and low toxicity, 14 novel substituted 5‐anilino‐α‐glucofuranose derivatives have been designed, synthesized and evaluated for antiproliferative activities in vitro. Their structures were characterized by NMR (¹H and ¹³C) and HR‐MS, and configuration (R/S) at C(5) was identified by two‐dimensional ¹H,¹H‐NOESY‐NMR spectrum. Their antiproliferative activities against human tumor cells were investigated by MTT assay. The results demonstrated that most of the synthesized compounds had antiproliferative effects comparable to the reference drugs gefitinib and lapatinib. In particular, (5R)‐5‐O‐(3‐chloro‐4‐{[5‐(4‐fluorophenyl)thiophen‐2‐yl]methyl}anilino)‐5‐deoxy‐1,2‐O‐(1‐methylethylidene)‐α‐glucofuranose ( 9da ) showed the most potent antiproliferative effects against SW480, A431 and A549 cells, with IC₅₀ values of 8.57, 5.15 and 15.24 μm , respectively. This work suggested 5‐anilino‐α‐glucofuranose as an antitumor core structure that may open a new way to develop more potent anti‐cancer agents.     

Cyclic biphalin analogues with a novel linker lead to potent agonist activities at mu,delta, and kappa opioid receptors

In an effort to improve biphalin’s potency and efficacy at the µ-(MOR) and δ-opioid receptors (DOR), a series of cyclic biphalin analogues 1–5 with a cystamine or piperazine linker at the C-terminus were designed and synthesized by solution phase synthesis using Boc-chemistry. Interestingly, all of the analogues showed balanced opioid agonist activities at all opioid receptor subtypes due to enhanced κ-opioid receptor (KOR) activity. Our results indicate that C-terminal flexible linkers play an important role in KOR activity compared to that of the other cyclic biphalin analogues with a hydrazine linker. Among them, analogue 5 is a potent (Ki?=?0.27, 0.46, and 0.87?nM; EC₅₀?=?3.47, 1.45, and 13.5?nM at MOR, DOR, and KOR, respectively) opioid agonist with high efficacy. Based on the high potency and efficacy at the three opioid receptor subtypes, the ligand is expected to have a potential synergistic effect on relieving pain and further studies including in vivo tests are worthwhile.     

Benchmark Dose Profiles for Joint‐Action Quantal Data in Quantitative Risk Assessment

Summary Benchmark analysis is a widely used tool in public health risk analysis. Therein, estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a prespecified Benchmark Response (BMR) is well understood for the case of an adverse response to a single stimulus. For cases where two agents are studied in tandem, however, the benchmark approach is far less developed. This article demonstrates how the benchmark modeling paradigm can be expanded from the single‐dose setting to joint‐action, two‐agent studies. Focus is on response outcomes expressed as proportions. Extending the single‐exposure setting, representations of risk are based on a joint‐action dose–response model involving both agents. Based on such a model, the concept of a benchmark profile (BMP) – a two‐dimensional analog of the single‐dose BMD at which both agents achieve the specified BMR – is defined for use in quantitative risk characterization and assessment. The resulting, joint, low‐dose guidelines can improve public health planning and risk regulation when dealing with low‐level exposures to combinations of hazardous agents.     

Quorum Sensing Is a Language of Chemical Signals and Plays an Ecological Role in Algal-Bacterial Interactions

Algae are ubiquitous in the marine environment, and the ways in which they interact with bacteria are of particular interest in the field of marine ecology. The interactions between primary producers and bacteria impact the physiology of both partners, alter the chemistry of their environment, and shape microbial diversity. Although algal-bacterial interactions are well known and studied, information regarding the chemical-ecological role of this relationship remains limited, particularly with respect to quorum sensing (QS), which is a system of stimuli and response correlated to population density. In the microbial biosphere, QS is pivotal in driving community structure and regulating behavioral ecology, including biofilm formation, virulence, antibiotic resistance, swarming motility, and secondary metabolite production. Many marine habitats, such as the phycosphere, harbor diverse populations of microorganisms and various signal languages (such as QS-based autoinducers). QS-mediated interactions widely influence algal-bacterial symbiotic relationships, which in turn determine community organization, population structure, and ecosystem functioning. Understanding infochemicals-mediated ecological processes may shed light on the symbiotic interactions between algae host and associated microbes. In this review, we summarize current achievements about how QS modulates microbial behavior, affects symbiotic relationships, and regulates phytoplankton chemical-ecological processes. Additionally, we present an overview of QS-modulated co-evolutionary relationships between algae and bacterioplankton, and consider the potential applications and future perspectives of QS.     

Difference of pine ectomycorrhizal biomass in relation to forest conditions

In this study, two plots in a secondary and another two in planted Pinus densiflora stands were exposed to different forest treatments, and the ectomycorrhizal (EM) biomass and its ergosterol content was measured for a year. The unmanaged plot in the secondary stand had greater EM biomass than those in any other plots. Whereas understory cutting had less effect on EM biomass, litter and humus removal decreased pine EM biomass and its ergosterol content, suggesting that such forest treatment alters EM biomass and its structure.     

Early root growth plasticity in seedlings of three Mediterranean woody species

Using a 141 F₂ population generated from maize inbred B64 × teosinte Zea nicaraguensis cross, quantitative trait loci (QTLs) controlling aerenchyma formation in roots under non-flooding drained soil conditions were identified. Seedlings of Z. nicaraguensis formed clear aerenchyma in the cortex of adventitious roots in non-flooding conditions, whereas the maize inbred line B64 did not. In the F₂ population, the capacity to develop aerenchyma exhibited wide and continuous variation, suggesting the trait was controlled by multiple genes. A linkage map was developed using 85 SSR markers, covering 1,224 cM across all ten chromosomes. Composite interval mapping analysis revealed that four QTLs for aerenchyma formation under non-flooding conditions were located to two regions of chromosome 1 (identified as Qaer1.02-3 and Qaer1.07), chromosome 5 (Qaer5.09) and chromosome 8 (Qaer8.06-7), and these explained 46.5% of the total phenotypic variance. The multiple interval mapping approach identified additional QTLs on chromosomes 1 (Qaer1.01) and 5 (Qaer5.01). Using these results, it may be possible to use SSR markers linked to aerenchyma formation in a marker assisted selection approach to introduce aerenchyma formation in drained soil conditions into maize for the eventual development of flooding tolerant maize hybrids.     

An empirical EEG analysis in brain death diagnosis for adults

Electroencephalogram (EEG) is often used in the confirmatory test for brain death diagnosis in clinical practice. Because EEG recording and monitoring is relatively safe for the patients in deep coma, it is believed to be valuable for either reducing the risk of brain death diagnosis (while comparing other tests such as the apnea) or preventing mistaken diagnosis. The objective of this paper is to study several statistical methods for quantitative EEG analysis in order to help bedside or ambulatory monitoring or diagnosis. We apply signal processing and quantitative statistical analysis for the EEG recordings of 32 adult patients. For EEG signal processing, independent component analysis (ICA) was applied to separate the independent source components, followed by Fourier and time-frequency analysis. For quantitative EEG analysis, we apply several statistical complexity measures to the EEG signals and evaluate the differences between two groups of patients: the subjects in deep coma, and the subjects who were categorized as brain death. We report statistically significant differences of quantitative statistics with real-life EEG recordings in such a clinical study, and we also present interpretation and discussions on the preliminary experimental results.

蚕豆主要数量性状的遗传主成份和数量分类

对50个蚕豆品种的7个数量性状进行了遗传主成份分析, 初步提出了评选蚕豆品种的遗传主成份标准,并筛选出18个综合性状优良的亲本品种。测定了50个蚕豆品种的遗传距离, 根据遗传距离大小,将50个蚕豆品种聚类为2群、 3类、9组。分类结果指出,蚕豆品种的遗传距离大小与地理差异有些似有一定关系,但在总体上,二者间无必然联系。 Abastract:Analysis of major Genetic component analysis was performed for 7 quantitative characters of 50 faba bean lines and according to the analysis,18 lines were selected as parents.The 50 lines were classified into 2 subpopulations,3 types and 9 groups according to their genetic distance.The results showed that there was seemly a correlation between geographical distribution and genetic distance,nevertheless most lines within the same cluster were close in genetic distance but far in geographic sites.     

Dissecting the molecular mechanism of drosophila odorant receptors through activity modeling and comparative analysis

To gain insight into the molecular mechanism of odorant receptors (ORs) in Drosophila species, we developed a Quantitative Structure Activity Relationship (QSAR) model that predicts experimentally measured electrophysiological activities between 24 D. melanogaster ORs and 108 odorants. Although the model is limited by the tested odorants,analyzing the model allowed dissection of specific topological and chemical properties necessary for an odorant to elicit excitatory or inhibitory receptor response. Linear odorants with five to eight nonhydrogen atoms at the main chain and hydrogen‐bond acceptor and/or hydrogen‐bond donor at its ends were found to stimulate strong excitatory response. A comparative sequence analysis of 90 ORs in 15 orthologous groups identified 15 putative specificity‐determining residues (SDRs) and 15 globally conserved residues that we postulate as functionally key residues. Mapping to a model of secondary structure resulted in 14 out of 30 key residues locating to the transmembrane (TM) domains. Twelve residues, including six SDRs and six conserved residues, are located at the extracellular halves of the TM domains. Combining the evidence from the QSAR modeling and the comparative sequence analysis, we hypothesize that the Drosophila ORs accept odorants into a binding pocket located on the extracellular halves of its TM domains. The QSAR modeling suggests that the binding pocket is around 15 Å in depth and about 6 Å in width. Twelve mainly polar or charged key residues, both SDRs and conserved, are located inthis pocket and postulated to distinguish docked odorants via primarily geometry fitting and hydrogen‐bond interaction. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Use of the additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley

The additive main effects and multiplicative interaction (AMMI) model has emerged as a powerful analytical tool for genotype x environment studies. The objective of the present study was to assess its value in quantitative trait locus (QTL) mapping. This was done through the analysis of a large two-way table of genotype-by-environment data of barley (Hordeum vulgare L.) grain yields, where the genotypes constituted a genetic population suitable for mapping studies. Grain yield data of 150 doubled haploid lines derived from the Steptoe x Morex cross, and the two parental lines, were taken by the North American Barley Genome Mapping Project (NABGMP) at 16 environments throughout the barley production areas of the USA and Canada. Four regions of the genome were responsible for most of the differential genotypic expression across environments. They accounted for approximately 50% of the genotypic main effect and 30% of the genotype x environment interaction (GE) sums of squares. The magnitude and sign of AMMI scores for genotypes and sites facilitate inferences about specific interactions. The parallel use of classification (cluster analysis of environments) and ordination (principal component analysis of GE matrix) techniques allowed most of the variation present in the genotype x environment matrix to be summarized in just a few dimensions, specifically four QTLs showing differential adaptation to four clusters of environments. Thus, AMMI genotypic scores, when the genotypes constituted a population suitable for QTL mapping, could provide an adequate way of resolving the magnitude and nature of QTL x environment interactions.Ignacio Romagosa was on sabbatical leave from the University of Lleida and the Institut de Recerca i Tecnologia Agroalimentàries, Lleida, Spain, when this study was conducted