基于知识的P2P网格资源发现研究*

针对当前网格资源管理系统扩展性差的问题,提出了具有分布式本体知识库的网格资源管理模型.新模型由分布的多个自治管理域组成;自治域之间通过DHT覆盖网连接.网格资源信息以本体知识库的形式管理:本地知识库管理域内网格知识;全局知识库则提供分布本体的语义映射以及知识的索引和定位.资源发现转换为本体知识库的实例检索推理,并且支持跨管理域的资源集发现.新模型极大地提高了网格资源管理系统的可扩展性.     

Differentiation of Cancer Stem Cells by Using Synthetic Small Molecules: Toward New Therapeutic Strategies against Therapy Resistance

Despite the existing arsenal of anti-cancer drugs, 10 million people die each year worldwide due to cancers; this highlights the need to discover new therapies based on innovative modes of action against these pathologies. Current chemotherapies are based on the use of cytotoxic agents, targeted drugs, monoclonal antibodies or immunotherapies that are able to reduce or stop the proliferation of cancer cells. However, tumor eradication is often hampered by the presence of resistant cells called cancer stem-like cells or cancer stem cells (CSCs). Several strategies have been proposed to specifically target CSCs such as the use of CSC-specific antibodies, small molecules able to target CSC signaling pathways or drugs able to induce CSC differentiation rendering them sensitive to classical chemotherapy. These latter compounds are the focus of the present review, which aims to report recent advances in anticancer-differentiation strategies. This therapeutic approach was shown to be particularly promising for eradicating tumors in which CSCs are the main reason for therapeutic failure. This general view of the chemistry and mechanism of action of compounds inducing the differentiation of CSCs could be particularly useful for a broad range of researchers working in the field of anticancer therapies as the combination of compounds that induce differentiation with classical chemotherapy could represent a successful approach for future therapeutic applications.     

Screening of Inhibitors Targeting Heat Shock Protein 47 Involved in the Development of Idiopathic Pulmonary Fibrosis

Heat shock protein 47 (HSP47), a collagen-specific molecular chaperone, is causally related to fibrotic diseases, including idiopathic pulmonary fibrosis. The identification of Compounds that interfere with the HSP47-collagen interaction is essential for the development of relevant therapeutics. Herein, we prepared human HSP47 as a soluble fusion protein expressed in E. coli and established an assay system for HSP47 inhibitor screening. We screened a natural and synthetic Compound library established at Nagasaki University. Among 1023 Compounds, 13 exhibited inhibitory activity against human HSP47, of which three inhibited its function in a dose-dependent manner. Epigallocatechin-3-O-gallate, one of these three Compounds, is a typical polyphenol Compound derived from tea leaves. Structurally related Compounds were synthesized and examined for their activity, revealing a hydroxyl group at A-ring position 5 as important for its activity. The present findings provide valuable insight for the development of natural product-derived therapeutics for fibrotic diseases, including idiopathic pulmonary fibrosis.     

Fragment-Based Drug Discovery for RNA Targets

Rapid development within the fields of both fragment-based drug discovery (FBDD) and medicinal targeting of RNA provides possibilities for combining technologies and methods in novel ways. This review provides an overview of fragment-based screening (FBS) against RNA targets, including a discussion of the most recently used screening and hit validation methods such as NMR spectroscopy, X-ray crystallography, and virtual screening methods. A discussion of fragment library design based on research from small-molecule RNA binders provides an overview on both the currently limited guidelines within RNA-targeting fragment library design, and future possibilities. Finally, future perspectives are provided on screening and hit validation methods not yet used in combination with both fragment screening and RNA targets.     

Peptides to Tackle Leishmaniasis: Current Status and Future Directions

Peptide-based drugs are an attractive class of therapeutic agents, recently recognized by the pharmaceutical industry. These molecules are currently being used in the development of innovative therapies for diverse health conditions, including tropical diseases such as leishmaniasis. Despite its socioeconomic influence on public health, leishmaniasis remains long-neglected and categorized as a poverty-related disease, with limited treatment options. Peptides with antileishmanial effects encountered to date are a structurally heterogeneous group, which can be found in different natural sources—amphibians, reptiles, insects, bacteria, marine organisms, mammals, plants, and others—or inspired by natural toxins or proteins. This review details the biochemical and structural characteristics of over one hundred peptides and their potential use as molecular frameworks for the design of antileishmanial drug leads. Additionally, we detail the main chemical modifications or substitutions of amino acid residues carried out in the peptide sequence, and their implications in the development of antileishmanial candidates for clinical trials. Our bibliographic research highlights that the action of leishmanicidal peptides has been evaluated mainly using in vitro assays, with a special emphasis on the promastigote stage. In light of these findings, and considering the advances in the successful application of peptides in leishmaniasis chemotherapy, possible approaches and future directions are discussed here.     

Dynamics of Bacterial Community Structure in the Rhizosphere and Root Nodule of Soybean: Impacts of Growth Stages and Varieties

Bacterial communities in rhizosphere and root nodules have significant contributions to the growth and productivity of the soybean (Glycine max (L.) Merr.). In this report, we analyzed the physiological properties and dynamics of bacterial community structure in rhizosphere and root nodules at different growth stages using BioLog EcoPlate and high-throughput sequencing technology, respectively. The BioLog assay found that the metabolic capability of rhizosphere is in increasing trend in the growth of soybeans as compared to the bulk soil. As a result of the Illumina sequencing analysis, the microbial community structure of rhizosphere and root nodules was found to be influenced by the variety and growth stage of the soybean. At the phylum level, Actinobacteria were the most abundant in rhizosphere at all growth stages, followed by Alphaproteobacteria and Acidobacteria, and the phylum Bacteroidetes showed the greatest change. But, in the root nodules Alphaproteobacteria were dominant. The results of the OTU analysis exhibited the dominance of Bradyrhizobium during the entire stage of growth, but the ratio of non-rhizobial bacteria showed an increasing trend as the soybean growth progressed. These findings revealed that bacterial community in the rhizosphere and root nodules changed according to both the variety and growth stages of soybean in the field.     

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.     

Characterization of New DNA Aptamers for Anti-HIV-1 Reverse Transcriptase

HIV-1 RT is a necessary enzyme for retroviral replication, which is the main target for antiviral therapy against AIDS. Effective anti-HIV-1 RT drugs are divided into two groups; nucleoside inhibitors (NRTI) and non-nucleoside inhibitors (NNRTI), which inhibit DNA polymerase. In this study, new DNA aptamers were isolated as anti-HIV-1 RT inhibitors. The selected DNA aptamer (WT62) presented with high affinity and inhibition against wild-type (WT) HIV-1 RT and gave a KD value of 75.10±0.29 nM and an IC₅₀ value of 84.81±8.54 nM. Moreover, WT62 decreased the DNA polymerase function of K103 N/Y181 C double mutant (KY) HIV-1 RT by around 80 %. Furthermore, the ITC results showed that this aptamer has small binding enthalpies with both WT and KY HIV-1 RTs through which the complex might form a hydrophobic interaction or noncovalent bonding. The NMR result also suggested that the WT62 aptamer could bind with both WT and KY mutant HIV-1 RTs at the connection domain.     

Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives.In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.     

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

We propose an efficient technique for improving the performance of automatic and cooperative compositions in unstructured Peer-to-Peer networks during service discovery. The technique exploits a probabilistic forwarding algorithm that uses different sources of knowledge, such as network density and service grouping, to reduce the amount of messages exchanged in the network. The technique, analysed in several network configurations by using a simulator to observe resolution time, recall and message overhead, presents good performance especially in dense and large-scale service networks.