A self-contained polymeric cartridge for automated biological sample preparation

Sample preparation is one of the most crucial processes for nucleic acids based disease diagnosis. Several steps are required for nucleic acids extraction, impurity washes, and DNA/RNA elution. Careful sample preparation is vital to the obtaining of reliable diagnosis, especially with low copies of pathogens and cells. This paper describes a low-cost, disposable lab cartridge for automatic sample preparation, which is capable of handling flexible sample volumes of 10 μl to 1 ml. This plastic cartridge contains all the necessary reagents for pathogen and cell lysis, DNA/RNA extraction, impurity washes, DNA/RNA elution and waste processing in a completely sealed cartridge. The entire sample preparation processes are automatically conducted within the cartridge on a desktop unit using a pneumatic fluid manipulation approach. Reagents transportation is achieved with a combination of push and pull forces (with compressed air and vacuum, respectively), which are connected to the pneumatic inlets at the bottom of the cartridge. These pneumatic forces are regulated by pinch valve manifold and two pneumatic syringe pumps within the desktop unit. The performance of this pneumatic reagent delivery method was examined. We have demonstrated the capability of the on-cartridge RNA extraction and cancer-specific gene amplification from 10 copies of MCF-7 breast cancer cells. The on-cartridge DNA recovery efficiency was 54-63%, which was comparable to or better than the conventional manual approach using silica spin column. The lab cartridge would be suitable for integration with lab-chip real-time polymerase chain reaction devices in providing a portable system for decentralized disease diagnosis.     

萤火虫荧光素酶基困的反义RNA及其缺失片段阻抑基因表达的研究

利用离体转录载体ｐＳＰ１８、ｐＧＥＭ－３Ｚ和萤火虫荧光素酶基因（Ｌｕｃ）及其缺失片段构建了一组融合质粒。以这些质粒为模板，通过离体转录产生荧光素酶基因的ｍＲＮＡ，反义ＲＮＡ及大小和结构不同的反义ＲＮＡ缺失片段，再通过显微注射分别将其引入爪赡卵母细胞的细胞质。注射后的卵母细胞经一定时间培育，然后检测其翻译产物一荧光素酶的相对活性。结果表明，荧光素酶基因的表达受反义ＲＮＡ及其缺失片段的严重阻抑，表达抑制和反义ＲＮＡ之间存在明显的剂量效应。而且，基因表达的抑制程度主要的和反义ＲＮＡ片段的结构有关。     

A fast and simple assay to quantify bacterial leukotoxin activity

BackgroundMannheimia haemolytica is the primary bacterial pathogen in causing bovine respiratory disease with tremendous annual losses in the cattle industry. The leukotoxin from M. haemolytica is the predominant virulence factor. Several leukotoxin activity assays are available but not standardized regarding sample preparation and cell line. Furthermore, these assays suffer from a high standard error, a prolonged time consumption and often complex sample pretreatments, which is important from the bioprocess engineering point of view.ResultsWithin this study, an activity assay based on the continuous cell line BL3.1 combined with a commercial available adenosine triphosphate viability assay kit was established. The leukotoxin activity was found to be strongly dependent on the sample preparation. Furthermore, the interfering effect of lipopolysaccharides in the sample could be successfully suppressed by adding polymyxin B. We reached a maximum relative P95 value of 14%, which is more than seven times lower compared to current available assays as well as a time reduction up to 88%.ConclusionUltimately, the established leukotoxin activity assay is simple, fast and has a high reproducibility. Critical parameters regarding the sample preparation were characterized and optimized making complex sample purification superfluous.     

A distance-based weighting framework for boosting the performance of dynamic ensemble selection

Dynamic Ensemble Selection (DES) strategy is one of the most common and effective techniques in machine learning to deal with classification problems. DES systems aim to construct an ensemble consisting of the most appropriate classifiers selected from the candidate classifier pool according to the competence level of the individual classifier. Since several classifiers are selected, their combination becomes crucial. However, most of current DES approaches focus on the combination of the selected classifiers while ignoring the local information surrounding the query sample needed to be classified. In order to boost the performance of DES-based classification systems, we in this paper propose a dynamic weighting framework for the classifier fusion during obtaining the final output of an DES system. In particular, the proposed method first employs a DES approach to obtain a group of classifiers for a query sample. Then, the hypothesis vector of the selected ensemble is obtained based on the analysis of consensus. Finally, a distance-based weighting scheme is developed to adjust the hypothesis vector depending on the closeness of the query sample to each class. The proposed method is tested on 30 real-world datasets with six well-known DES approaches based on both homogeneous and heterogeneous ensemble. The obtained results, supported by proper statistical tests, show that our method outperforms, both in terms of accuracy and kappa measures, the original DES framework.     

Comparison of different methods for total RNA extraction from sclerotia of Rhizoctonia solani

BackgroundRhizoctonia solani (teleomorph: Thanatephorus cucumeris) is one of the most important pathogens of rice (Oryza sativa L.) that causes severe yield losses in all rice-growing regions. Sclerotia, formed from the aggregation of hyphae, are important structures in the life cycles of R. solani and contain a large quantity of polysaccharides, lipids, proteins and pigments. In order to extract high-quality total RNA from the sclerotia of R. solani, five methods, including E.Z.N.A.™ Fungal RNA Kit, sodium dodecyl sulfate (SDS)–sodium borate, SDS–polyvinylpyrrolidone (PVP), guanidinium thiocyanate (GTC) and modified Trizol, were compared in this study.ResultsThe electrophoresis results showed that it failed to extract total RNA from the sclerotia using modified Trizol method, whereas it could extract total RNA from the sclerotia using other four methods. Further experiments confirmed that the total RNA extracted using SDS–sodium borate, SDS–PVP and E.Z.N.A.™ Fungal RNA Kit methods could be used for RT-PCR of the specific amplification of GAPDH gene fragments, and that extracted using GTC method did not fulfill the requirement for above-mentioned RT-PCR experiment.ConclusionIt is concluded that SDS–sodium borate and SDS–PVP methods were the better ones for the extraction of high-quality total RNA that could be used for future gene cloning and expression studies, whereas E.Z.N.A.™ Fungal RNA Kit was not taken into consideration when deal with a large quantity of samples because it is expensive and relatively low yield.     

Binary and graded relevance in IR evaluations—Comparison of the effects on ranking of IR systems

In this study the rankings of IR systems based on binary and graded relevance in TREC 7 and 8 data are compared. Relevance of a sample TREC results is reassessed using a relevance scale with four levels: non-relevant, marginally relevant, fairly relevant, highly relevant. Twenty-one topics and 90 systems from TREC 7 and 20 topics and 121 systems from TREC 8 form the data. Binary precision, and cumulated gain, discounted cumulated gain and normalised discounted cumulated gain are the measures compared. Different weighting schemes for relevance levels are tested with cumulated gain measures. Kendall’s rank correlations are computed to determine to what extent the rankings produced by different measures are similar. Weighting schemes from binary to emphasising highly relevant documents form a continuum, where the measures correlate strongly in the binary end, and less in the heavily weighted end. The results show the different character of the measures.     

Hidden structure: Using network methods to map system architecture

In this paper, we describe an operational methodology for characterizing the architecture of complex technical systems and demonstrate its application to a large sample of software releases. Our methodology is based upon directed network graphs, which allows us to identify all of the direct and indirect linkages between the components in a system. We use this approach to define three fundamental architectural patterns, which we label core–periphery, multi-core, and hierarchical. Applying our methodology to a sample of 1286 software releases from 17 applications, we find that the majority of releases possess a “core–periphery” structure. This architecture is characterized by a single dominant cyclic group of components (the “Core”) that is large relative to the system as a whole as well as to other cyclic groups in the system. We show that the size of the Core varies widely, even for systems that perform the same function. These differences appear to be associated with different models of development – open, distributed organizations develop systems with smaller Cores, while closed, co-located organizations develop systems with larger Cores. Our findings establish some “stylized facts” about the fine-grained structure of large, real-world technical systems, serving as a point of departure for future empirical work.     

Construction of nanocarriers based on nucleic acids and their applications in nanobiology delivery systems

In recent years, nanocarriers based on nucleic acids have emerged as powerful and novel nanocarriers that are able to meet the demand for cancer-cell-specific targeting. Functional dynamics analysis revealed good biocompatibility, low toxicity and programmable structures, and their advantages include controllable size and modifiability. The development of novel hybrids has focused on the distinct roles of biosensing, drug and gene delivery, vaccine transport, photosensitization, counteracting drug resistance and functioning as carriers and logic gates. This review is divided into three parts: (i) DNA nanocarriers, (ii) RNA nanocarriers and (iii) DNA/RNA hybrid nanocarriers and their applications in nanobiology delivery systems. We also provide perspectives on possible future directions for growth in this field.     

Accuracy-diversity optimization in personalized recommender system via trajectory reinforcement based bacterial colony optimization

Personalized recommender systems have been extensively studied in human-centered intelligent systems. Existing recommendation techniques have achieved comparable performance in predictive accuracy; however, the trade-off between recommendation accuracy and diversity poses new challenges, as diversification may lead to accuracy loss, whereas it can solve the over-fitting problem and enhance the user experience. In this study, we propose a heuristic optimization-based recommendation model that jointly optimizes accuracy and diversity performance by obtaining a set of optimized solutions. To establish the best accuracy-diversity balance, a novel trajectory-reinforcement-based bacterial colony optimization algorithm was developed. The improved bacterial colony optimization algorithm was comprehensively evaluated by comparing it with eight popular and state-of-the-art algorithms on ten benchmark testing problems with different degrees of complexity. Furthermore, an optimization-based recommendation model was applied to a real-world recommendation dataset. The results demonstrate that the improved bacterial colony optimization algorithm achieves the best overall performance for benchmark problems in terms of convergence and diversity. In the real-world recommendation task, the proposed approach improved the diversity performance by 1.62% to 8.62% while maintaining superior (1.88% to 40.32%) accuracy performance. Additionally, the proposed personalized recommendation model can provide a set of nondominated solutions instead of a single solution to accommodate the ever-changing preferences of users and service providers. Therefore, this work demonstrates the excellence of an optimization-based recommendation approach for solving the accuracy-diversity trade-off.     

Escherichia coli lipopolysaccharide administration alters antioxidant profile during hypercholesterolemia

Pathogens, especially Gram-negative bacteria or bacterial endotoxin, along with other classical factors, may be involved in inflammatory response within the aortic endothelium during the progression of cardiovascular disease. Studies have shown that bacterial endotoxin activates various inflammatory processes in the body. Our study aims to establish a correlation between endotoxemia and vascular expression of antioxidant enzymes. Swiss albino mice (4 weeks old) were fed a high fat diet for 24 weeks and then were administered Escherichia coli endotoxin intraperitonealy, for 4 weeks. Tissue antioxidant enzymes, serum levels of IL-6 and TNF alpha were measured from the mice. We report that i.p. administration of endotoxin to hyperlipidemic mice resulted in elevation of superoxide dismutase and catalase enzymes, which was paralleled by a systemic reduction of serum cholesterol and LDL expression. Myeloperoxidase levels were also found to be elevated in aortic tissue, while an increase was also observed in the serum cytokine levels.     

High-throughput study of alpha-synuclein expression in yeast using microfluidics for control of local cellular microenvironment

Microfluidics is an emerging technology which allows the miniaturization, integration, and automation of fluid handling processes. Microfluidic systems offer low sample consumption, significantly reduced processing time, and the prospect of massive parallelization. A microfluidic platform was developed for the control of the soluble cellular microenvironment of Saccharomyces cerevisiae cells, which enabled high-throughput monitoring of the controlled expression of alpha-synuclein (aSyn), a protein involved in Parkinson's disease. Y-shaped structures were fabricated using particle desorption mass spectrometry-based soft-lithography techniques to generate biomolecular gradients along a microchannel. Cell traps integrated along the microchannel allowed the positioning and monitoring of cells in precise locations, where different, well-controlled chemical environments were established. S. cerevisiae cells genetically engineered to encode the fusion protein aSyn-GFP (green fluorescent protein) under the control of GAL1, a galactose inducible promoter, were loaded in the microfluidic structure. A galactose concentration gradient was established in the channel and a time-dependent aSyn-GFP expression was obtained as a function of the positioning of cells along the galactose gradient. Our results demonstrate the applicability of this microfluidic platform to the spatiotemporal control of cellular microenvironment and open a range of possibilities for the study of cellular processes based on single-cell analysis.     

发展基因沉默技术,控制作物土传真菌病害

作物土传真菌病害是当前农业所面临的最重要问题之一,由于防治困难,正日趋成为限制我国农业生产可持续发展的重要因素。基因沉默(或RNA沉默,RNAi)是广泛存在于真核生物中,基于同源序列调控基因表达的一条重要途径,而由此发展起来的基因沉默技术,作为一种新防治策略被广泛地应用于防控植物有害生物的研究中。文章综合介绍了作物土传真菌病害的发生与防治现状、RNA沉默及其在植物有害生物防控应用的最新研究进展,客观分析了基因沉默技术在防治作物土传真菌病害的巨大潜力和亟需解决的主要问题,阐述了研发基因沉默技术对可持续控制作物土传真菌病害的重要性及其巨大应用前景。     

类耗散系统的特性

介绍由保面积映像不连续、不可逆耦合构成的 类耗散系统",并以两个系统为例介绍类耗散系统的主要性质。这样的系统中会出现规则或混沌的,能把外部的迭代吸引过来的 类吸引子",但迭代一旦到达类吸引子,又会展示典型的保守性运动。这类系统中可能出现 类V形阵发 ",在适当的参数改变时,还可以展示从典型的保守系统向近似于耗散系统的连续转变。更多的特异性质还有待于继续研究     

The convergence of Moore's/Mooers' law's

A four-stage hypothesis of information systems development is presented. The stages derive from the application of Moore's Law—that the number of elements that can be integrated onto a chip is doubling roughly every year—the expression of the very rapid exponential rate of growth of information systems technology, and the application of Mooers' Law—that an information system will only be used when it is more trouble not to use it than it is to use it—the quintessential expression of the importance of human factors. It is argued that we are now roughly halfway along this developmental process, about to make the transition from Stage II to Stage 111, and that from that conclusion we can make some useful projections for and about the future.     

Microfluidic enrichment of small proteins from complex biological mixture on nanoporous silica chip

The growing field of miniaturized diagnostics is hindered by a lack of pre-analysis treatments that are capable of processing small sample volumes for the detection of low concentration analytes in a high-throughput manner. This letter presents a novel, highly efficient method for the extraction of low-molecular weight (LMW) proteins from biological fluids, represented by a mixture of standard proteins, using integrated microfluidic systems. We bound a polydimethylsiloxane layer patterned with a microfluidic channel onto a well-defined nanoporous silica substrate. Using rapid, pressure-driven fractionation steps, this system utilizes the size-exclusion properties of the silica nanopores to remove high molecular weight proteins while simultaneously isolating and enriching LMW proteins present in the biological sample. The introduction of the microfluidic component offers important advantages such as high reproducibility, a simple user interface, controlled environment, the ability to process small sample volumes, and precise quantification. This solution streamlines high-throughput proteomics research on many fronts and may find broad acceptance and application in clinical diagnostics and point of care detection.     

Flexible sample selection strategies for transfer learning in ranking

Ranking is a central component in information retrieval systems; as such, many machine learning methods for building rankers have been developed in recent years. An open problem is transfer learning, i.e. how labeled training data from one domain/market can be used to build rankers for another. We propose a flexible transfer learning strategy based on sample selection. Source domain training samples are selected if the functional relationship between features and labels do not deviate much from that of the target domain. This is achieved through a novel application of recent advances from density ratio estimation. The approach is flexible, scalable, and modular. It allows many existing supervised rankers to be adapted to the transfer learning setting. Results on two datasets (Yahoo’s Learning to Rank Challenge and Microsoft’s LETOR data) show that the proposed method gives robust improvements.     

Expression,purification and biological effect of a novel single chain Fv antibody and protamine fusion protein for the targeted delivery of siRNAs to FGFR3 positive cancer cells

BackgroundGain-of-function of fibroblast growth factor receptor 3 (FGFR3) is involved in the pathogenesis of many tumors. More and more studies have focused on the potential usage of therapeutic single-chain Fv (ScFv) antibodies against FGFR3. RNA interference (RNAi) has been considered as a promising therapeutic method against cancer. A tool which can deliver small interference RNAs (siRNAs) into FGFR3 positive cancer cells is very promising for anti-tumor therapy.ResultsIn this study, a novel fusion protein R3P, which consists of FGFR3-ScFv and protamine, was generated in Escherichia coli by inclusion body expression strategy and Ni-NTA chromatography. Its yield reached 10 mg per liter of bacterial culture and its purity was shown to be higher than 95%. 1 μg of R3P could efficiently bind to about 2.5 pmol siRNAs and deliver siRNAs into FGFR3 positive RT112 and K562 cells. Annexin V staining results showed that R3P can deliver the amplified breast cancer 1 (AIB1) siRNAs to induce RT112 cell apoptosis.ConclusionThese results indicated that R3P was a promising carrier tool to deliver siRNAs into FGFR3 positive cancer cells and to exert anti-tumor effect.     

Using surface plasmon resonance imaging to study bacterial biofilms

This paper describes the use of Surface Plasmon Resonance imaging (SPRi) as an emerging technique to study bacterial physiology in real-time without labels. The overwhelming majority of bacteria on earth exist in large multicellular communities known as biofilms. Biofilms are especially problematic because they facilitate the survival of pathogens, leading to chronic and recurring infections as well as costly industrial complications. Monitoring biofilm accumulation and removal is therefore critical in these and other applications. SPRi uniquely provides label-free, high-resolution images of biomass coverage on large channel surfaces up to 1 cm² in real time, which allow quantitative assessment of biofilm dynamics. The rapid imaging capabilities of this technique are particularly relevant for multicellular bacterial studies, as these cells can swim several body lengths per second and divide multiple times per hour. We present here the first application of SPRi to image Escherichia coli and Pseudomonas aeruginosa cells moving, attaching, and forming biofilms across a large surface. This is also the first time that biofilm removal has been visualized with SPRi, which has important implications for monitoring the biofouling and regeneration of fluidic systems. Initial images of the removal process show that the biofilm releases from the surface as a wave along the direction of the fluid flow.