A GPU solvent–solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

During the past few years, graphics processing units (GPUs) have become extremely popular in the high performance computing community. In this study, we present an implementation of an acceleration engine for the solvent–solvent interaction evaluation of molecular dynamics simulations. By careful optimization of the algorithm speed‐ups up to a factor of 54 (single‐precision GPU vs. double‐precision CPU) could be achieved. The accuracy of the single‐precision GPU implementation is carefully investigated and does not influence structural, thermodynamic, and dynamic quantities. Therefore, the implementation enables users of the GROMOS software for biomolecular simulation to run the solvent–solvent interaction evaluation on a GPU, and thus, to speed‐up their simulations by a factor 6–9. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

同位素示踪技术定量分析肿瘤细胞中的代谢重编

肿瘤代谢在最近几年重新获得重视,讨论肿瘤代谢我们无法避开瓦伯格效应,尽管瓦伯格效应在20世纪20年代就提出来了。瓦伯格效应也称需氧糖酵解,是指在有氧的条件下癌细胞过量摄取葡萄糖,产生更多的乳酸。此外,癌细胞也可摄取其他物质,如谷氨酰胺、丝氨酸和甘氨酸等作为能量需求与营养来源。为了描述癌细胞中改变了的代谢通路,同位素标记示踪技术提供了一种新的全局观点,让我们更好地理解在癌基因或抑癌基因调控下的代谢切换。色谱与质谱联用是一种重要的分析工具,可定量检测带有同位素标记的代谢物,从而剖析肿瘤细胞中的生物化学反应。在本文中,我们总结了基于质谱的肿瘤代谢分析的研究概况并提出未来的研究方向。重点讨论碳-13标记与氘代标记的示踪技术分析中间代谢产物,包括还原型烟酰胺腺嘌呤二核苷酸磷酸(NADPH)。目前生物化学教科书中认为NADPH主要来源于磷酸戊糖途径。然而,氘代示踪技术分析表明,包括一碳代谢在内的其他代谢通路对产生NADPH也很重要。以上内容都在本文中进行了讨论。     

A microhap panel for kinship analysis through massively parallel sequencing technology

It is widely recognized that microhaps are powerful markers for different forensic purposes, mainly due to their advantages of both short tandem repeats and single nucleotide polymorphisms, including multiple alleles, low mutation rate, and absence of stutter peaks. In the present study, a panel of 60 microhap loci was developed and utilized in forensic kinship analysis as a preliminary study. Genotyping of microhap was performed by massively parallel sequencing and haplotypes were directly achieved from sequence reads of 73 samples from Chinese Han population. We observed that 49 out of 60 loci have effective number of alleles greater than 3.0 and 10 out of 60 have values above 4.0, with an average value of 3.5598. The heterozygosity values were in a range from 0.5840 to 0.8546 with an average of 0.7268 and the cumulative power of exclusion value of the 60 loci is equal to 1–4.78 × 10⁻¹⁸. Moreover, we demonstrated the applicability of this method by different relationship inference problems, including identification of single parent-offspring, full-sibling, and second-degree relative. The results indicated that the assembled microhap panel provided more power for relationship inference, than commonly used short tandem repeats or single nucleotide polymorphism system.     

New membraneless vaporization unit coupled with flow systems for analysis of ethanol

This work presents the development of a new design for a membraneless vaporization (MBL-VP) unit, called dual chamber MBL-VP for measurement of volatile compounds. With this unit, exact volumes of sample and reagent are introduced into their respective cone-shaped chambers from the base of the cones. Diffusion of volatile analyte then takes place. After an appropriate time interval, the acceptor solution is withdrawn from the chamber into the detector flow-cell, while the sample solution is withdrawn to waste. Unlike the previous MBL-VP design, problems with overflow of solutions are eliminated by precise control of the input volume to be less than the volume of the chamber. The developed flow system with the dual chamber MBL-VP unit was applied to the determination of the ethanol content of various liquid samples, using the oxidation reaction between potassium dichromate and the diffused ethanol. In addition, in order to accelerate the gas diffusion process, the donor chamber was aerated. As the result, relatively short analysis time of 144 s was achieved for ethanol content in the range of 5–50% (v/v). The proposed method was successfully validated against a gas chromatographic method for 17 alcoholic samples. Percentage recovery was in the range of 96–109%.     

Accelerated,untargeted metabolomics analysis of cutaneous T‐cell lymphoma reveals metabolic shifts in plasma and tumor adjacent skins of xenograft mice

Cutaneous T‐cell lymphoma (CTCL) is a heterogeneous group of skin‐homing T‐cell neoplasms. Clinical management is stage based but diagnosis and prognosis could be extremely challenging. The presented study aims to explore the metabolic profiling of CTCL by an accelerated untargeted metabolomics data analysis tool “Mummichog” to facilitate the discoveries of potential biomarkers for clinical early stage diagnosis, prognosis, and treatments in CTCL. Ultra high‐performance liquid chromatography–quadrupole time‐of‐flight–based untargeted metabolomics were conducted on the skin and plasma of CTCL mice. It showed that the metabolism of skin changed greatly versus control samples in the development of CTCL. Increased l ‐glutamate and decreased adenosine monophosphate were the most essential metabolic features of CTCL tumor and tumor adjacent skins. Unique metabolism changes in tumor adjacent non‐involved skin tissues (ANIT) occurred in the progress of carcinogenesis, including upregulated cytidine‐5′‐triphosphate, aberrant biosynthesis of prostaglandins, pyrimidine, mevalonate pathway, and tryptophan degradation. Sharply elevated 5‐phospho‐α‐d ‐ribose 1‐diphosphate (PRPP) marked the final state of tumor in CTCL. In the plasma, systematic shifts in corticosterone, sphingolipid, and ceramide metabolism were found. These uncovered aberrant metabolites and metabolic pathways suggested that the metabolic reprogramming of PRPP in tumor tissues may cause the disturbance of cytidine and uridine metabolic homeostasis in ANIT. Accumulative cytidine‐5′‐triphosphate in ANIT may exert positive feedback on the PRPP level and leads to CTCL further development. In addition, the accelerated data analysis tool “Mummichog” showed good practicability and can be widely used in high‐resolution liquid chromatography mass spectrometry–based untargeted metabolomics.     

Pseudomonas stutzeri 1317合成中长链聚羟基脂肪酸酯的组成分析模型

Pseudomonasstutzeri 1317可以在不同碳源上生长,合成不同共聚单体单元组成的中长链聚羟基脂肪酸酯(mclPHAs).本文在已知的代谢途径的基础上,提出了关于mclPHAs组成的数学模型,结果表明,mclPHAs的共聚单体单元组成主要取决于前体生成途径,以及该途径和聚合途径酶对不同碳原子数前体的选择性.实验结果与文献报道结果均验证了该模型.代谢控制分析的结果表明,碳数为8～10的前体的聚合效率最高.通过调制前体生成途径,可以有效调节PHA的单体单元组成.     

Parallelization and improvements of the generalized born model with a simple sWitching function for modern graphics processors

Two fundamental challenges of simulating biologically relevant systems are the rapid calculation of the energy of solvation and the trajectory length of a given simulation. The Generalized Born model with a Simple sWitching function (GBSW) addresses these issues by using an efficient approximation of Poisson–Boltzmann (PB) theory to calculate each solute atom's free energy of solvation, the gradient of this potential, and the subsequent forces of solvation without the need for explicit solvent molecules. This study presents a parallel refactoring of the original GBSW algorithm and its implementation on newly available, low cost graphics chips with thousands of processing cores. Depending on the system size and nonbonded force cutoffs, the new GBSW algorithm offers speed increases of between one and two orders of magnitude over previous implementations while maintaining similar levels of accuracy. We find that much of the algorithm scales linearly with an increase of system size, which makes this water model cost effective for solvating large systems. Additionally, we utilize our GPU‐accelerated GBSW model to fold the model system chignolin, and in doing so we demonstrate that these speed enhancements now make accessible folding studies of peptides and potentially small proteins. © 2016 Wiley Periodicals, Inc.     

Model-guided metabolic gene knockout of gnd for enhanced succinate production in Escherichia coli from glucose and glycerol substrates

The metabolic role of 6-phosphogluconate dehydrogenase (gnd) under anaerobic conditions with respect to succinate production in Escherichia coli remained largely unspecified. Herein we report what are to our knowledge the first metabolic gene knockout of gnd to have increased succinic acid production using both glucose and glycerol substrates in E. coli. Guided by a genome scale metabolic model, we engineered the E. coli host metabolism to enhance anaerobic production of succinic acid by deleting the gnd gene, considering its location in the boundary of oxidative and non-oxidative pentose phosphate pathway. This strategy induced either the activation of malic enzyme, causing up-regulation of phosphoenolpyruvate carboxylase (ppc) and down regulation of phosphoenolpyruvate carboxykinase (ppck) and/or prevents the decarboxylation of 6 phosphogluconate to increase the pool of glyceraldehyde-3-phosphate (GAP) that is required for the formation of phosphoenolpyruvate (PEP). This approach produced a mutant strain BMS2 with succinic acid production titers of 0.35 g l⁻¹ and 1.40 g l⁻¹ from glucose and glycerol substrates respectively. This work further clearly elucidates and informs other studies that the gnd gene, is a novel deletion target for increasing succinate production in E. coli under anaerobic condition using glucose and glycerol carbon sources. The knowledge gained in this study would help in E. coli and other microbial strains development for increasing succinate production and/or other industrial chemicals.     

A novel fusion approach based on induced ordered weighted averaging operators for chemometric data analysis

This paper proposes a novel approach for the estimation of spectroscopic data by combining the predictions of an ensemble of estimators using the induced ordered weighted averaging (IOWA) fusion operators. For ensemble generation, we use Gaussian process regression (GPR) and extreme learning machine (ELM) estimators associated with different kernels. To render the model selection issue of ELM as efficiently as in the GPR Bayesian estimation method, we develop an automatic solution based on the powerful differential evolution (DE) algorithm. During the fusion process, the IOWA operator needs two things: (1) an order‐inducing value; and (2) a way to determine its weights. For the order‐inducing value, we propose to use the residual of each estimated output value. Because we cannot compute the true residual, we explore the idea of estimating the residuals themselves by associating to each estimator of the ensemble a second estimator of the same kind called a residual estimator. To learn the weights associated with these nonlinear operators, the proposed method relies on the concept of prioritized aggregation, where we generate the weights directly from the estimated residuals. Experimental results obtained on three real spectroscopic datasets confirm the interesting capabilities of the proposed IOWA fusion method. Copyright © 2013 John Wiley & Sons, Ltd.     

A robust regression approach for spectrophotometric signal analysis

The effectiveness of a regression method strongly depends on the characteristics of the considered regression problem. As a consequence, this makes it difficult to choose a priori the most appropriate algorithm for a given dataset. This issue is faced in this work through a novel regression approach based on the fusion of an ensemble of different regressors. In order to implement the proposed robust multiple system (RMS), four different fusion strategies are explored. In this context, we propose a novel fusion strategy named selection‐based strategy (SBS) that provides as output the estimate obtained by the regression algorithm (included in the ensemble) characterized by the highest expected accuracy in the region of the feature space associated with the considered model. The SBS is based not on a direct combination of the estimates yielded by all the regressors but on a selection mechanism that identifies the expected best available estimate. For such purpose, it exploits the accuracies of the regressors included in the ensemble in different portions of the input feature space. The experimental assessment of the RMS was carried out on three different datasets: a wine, an orange juice, and an apple datasets. The obtained experimental results suggest that, in general, the fusion of an ensemble of different regression algorithms leads to a regression process that is more robust and sometimes also more accurate than traditional regression methods. In particular, the proposed SBS method represents an effective solution to carry out the fusion process. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling of synergistic solvent extraction of Zr(IV) / HCl / TOA+Cyanex 921 system using statistical analysis and neural network

Multi-linear regression analysis (MLR), radial basis function (RBF) and multilayer perceptron (MLP) of artificial neural network (ANN) with five inputs (temperature, concentrations of HCl, TOA, Cyanex 921, Zr (IV) and percentage of extraction (%E)) as only output were employed for the construction of models. It was observed that ANN (RBF and MLP) performed better as compared to the MLR model. Based on the models proposed, the extraction of Zr(IV) could be predicted under variable experimental conditions of concentrations of HCl, TOA (Tri-n-octylamine), Cyanex 921 (Tri-n-octyl phosphineoxide), Zr(IV) and temperature. The nonlinear and complex relation between the percentage of extraction and operating variables have been determined using two and three layered feed forward neural network with back-propagation of error learning algorithm. Uncertainties in data have been determined in terms of statistical parameters such as root mean-squared error and R-squared values to check the efficiency of the model for prediction.     

蛋白质组质谱分析中基于串并联支持向量机的肽段色谱保留时间预测方法

基于质谱的大规模蛋白质鉴定中,在线液相色谱分离发挥了重要作用。色谱保留时间(retention time,RT)是肽段鉴定和定量的重要信息。由于整个色谱分析运行时间中,流动相中的有机相采用了非线性浓度曲线以及样品中肽段之间的相互影响等因素,基于肽段序列的RT预测还存在精度不高、模型推广性能差等问题。本文提出了一种基于串并联支持向量机(serial and parallel support vector machine,SP-SVM)的RT预测方法,能够表征洗脱过程中有机相浓度的非线性变化和肽段之间的相互影响,显著提高了肽段保留时间预测的精度。利用复杂样本数据集验证结果表明,预测RT和实验RT之间的决定系数达到了0.95,超过95%的鉴定肽段的RT预测误差范围小于总运行时间的20%,超过70%的鉴定肽段的RT预测误差范围小于总运行时间的10%。本文提出的模型的性能达到了目前已知的最好水平。     

A study of large-volume on-column injection GC-ECD for the ultratrace analysis of organochlorine pesticides in water

In this work, a large-volume on-column injection method for the analysis of 21 organochlorine pesticides, including HCH isomers, DDT derivatives and cyclodiene derivatives, was optimized. The solvent selected to carry out the study was ethyl acetate and the injection volume was 100 μl. Some factors were introduced in a Plackett-Burman design to determine their influence in the vaporization efficiency. The significant factors were then studied by a univariate procedure and sorted according to their importance on the response. The effect of the injection conditions on the peak resolution was also noted. The conditions selected according to sensitivity and resolution were: initial oven temperature 75 °C, injection speed 20 μl s⁻¹, solvent vapor exit (SVE) valve closure time 60 s, initial pressure 100 kPa and isothermal oven time 1 min. Analytical characteristics expressed in terms of precision, linear range, and limit of detection have been determined and compared with those obtained by splitless injection. The degradation of endrin and p,p′-DDT thermolabile pesticides was evaluated for both injection techniques. Finally the developed method was successfully applied to the ultratrace analysis of pesticides in natural waters. With this purpose a micro liquid-liquid extraction method using 2 ml of ethyl acetate to extract 10 ml of water sample was proposed. Recoveries between 69 and 107% were obtained with a very good precision (0.2-1.3%) for the studied pesticides, except for p,p′-DDD. Detection limits between 0.3 and 25 ng l⁻¹, which fulfill the limits established by the new water directive 2008/105/EC, were achieved. The MLLE method was compared with the SPE method by the analysis of some water samples using both procedures, and good concordance was obtained.     

A TriPPPro-Nucleotide Reporter with Optimized Cell-Permeable Dyes for Metabolic Labeling of Cellular and Viral DNA in Living Cells

The metabolic labeling of nucleic acids in living cells is highly desirable to track the dynamics of nucleic acid metabolism in real-time and has the potential to provide novel insights into cellular biology as well as pathogen-host interactions. Catalyst-free inverse electron demand Diels–Alder reactions (iEDDA) with nucleosides carrying highly reactive moieties such as axial 2-trans-cyclooctene (2TCOa) would be an ideal tool to allow intracellular labeling of DNA. However, cellular kinase phosphorylation of the modified nucleosides is needed after cellular uptake as triphosphates are not membrane permeable. Unfortunately, the narrow substrate window of most endogenous kinases limits the use of highly reactive moieties. Here, we apply our TriPPPro (triphosphate pronucleotide) approach to directly deliver a highly reactive 2TCOa-modified 2′-deoxycytidine triphosphate reporter into living cells. We show that this nucleoside triphosphate is metabolically incorporated into de novo synthesized cellular and viral DNA and can be labeled with highly reactive and cell-permeable fluorescent dye-tetrazine conjugates via iEDDA to visualize DNA in living cells directly. Thus, we present the first comprehensive method for live-cell imaging of cellular and viral nucleic acids using a two-step labeling approach.     

A thallium(I) tetranuclear cubic cage unit in an interpenetrated supramolecular polymer: A new precursor for the preparation of Tl2O3 nanostructures

A new thallium(I) supramolecular polymer, [Tl₄(μ₃-4-BN)₄]_n (1) [9-HBN = 4-hydroxy benzonitrile], with a disordered cubic cage structural unit has been synthesized and characterized. The single-crystal X-ray data of compound 1 shows one type of Tl^I ion in the tetranuclear cubic cage structure with a coordination number of three. In addition to two intra cage thallophilic interactions in 1, each thallium(I) atom has a weak Tl?N secondary interaction with the nitrile group of the 4-BN⁻ ligand. Finally the Tl-ions attain the O₃Tl?NTl₂ coordination sphere with a stereo-chemically ‘active’ electron lone pair on the metal. The self assembly between the benzonitrile groups of one cubic cage structure with an adjacent one with a Tl?N short contact, by π-π stacking and weak hydrogen bonding interactions, results in the formation of a new interpenetrating thallium(I) supramolecular polymer. The thermal stability of 1 was studied by thermo gravimetric (TG) and differential thermal analyses (DTA). Nanostructures of thallium(III) oxide were prepared from a calcination process of compound 1 fine powder at 743 K. These nanostructures were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM).     

A post-modification approach to independent compo-nent analysis for resolution of overlapping GC/MS signals: from independent components to chemical components

Independent component analysis (ICA) has demonstrated its power to extract mass spectra from over-lapping GC/MS signal. However, there is still a problem that mass spectra with negative peaks at some m/z will be obtained in the resolved results when there are overlapping peaks in the mass spectra of a mixture. Based on a detail theoretical analysis of the preconditions for ICA and the non-negative property of GC/MS signals, a post-modification based on chemical knowledge (PMBK) strategy is pro-posed to solve this problem. By both simulated and experimental GC/MS signals, it was proved that the PMBK strategy can improve the resolution effectively.     

Ultra-sensitive fully automated immunoassay for detection of propanil in aqueous samples: steps of progress toward sub-nanogram per liter detection

The widely-used pesticide propanil is a selective post-emergent general-use acetanilide herbicide registered for control of broadleaf and grass weeds in rice, small grain, and turf. Because broad application and quite heavy use of this herbicide lead to contaminated sites and, consequently, contaminated water, immunoanalytical methods with very low limits of detection (LOD) and low limits of quantification (LOQ) are becoming increasingly important for environmental analysis and, especially, for monitoring drinking-water quality. Environmental monitoring of pesticides, hormones, endocrine-disrupting chemicals, and antibiotics in aqueous samples (e.g. surface, ground, waste, or drinking water) with quite difficult matrices places large demands on chemical analysis. Biosensors have suitable characteristics such as efficiency in enabling very fast, sensitive, and cost-effective detection. Here we describe the steps of progress toward sub-nanogram per liter detection of propanil with a fully automated immunoassay. In contrast with common analytical methods such as GC–MS or HPLC–MS the biosensor used requires no sample pre-treatment and pre-concentration. The basis of our sensitive assay is an antibody with a high affinity constant toward propanil. During the optimization process, we compared different surface modifications (four different immobilized derivatives) and reduced the amount of antibody per sample. In fact, optimization of the assay resulted in an LOD of 0.6 ng L^–1 and an LOQ of 4.5 ng L^–1 without any sample pre-treatment and without pre-concentration. These results for propanil with the RIANA instrument, and its improved sensitivity for detection of a single pesticide at the low nanogram per liter range, show that biosensors can compete with common analytical methods in the field of water analysis.     

A novel microfluidic capture and monitoring method for assessing physiological damage of C. elegans under microgravity

Spatial microgravity is a significant factor affecting and causing physiological changes of organisms in space environment. On‐site assessment of the damage associated to microgravity is very important for future long‐term space exploration of mankind. In this paper, a new microfluidic device for analyzing the damage of microgravity on Caenorhabditis elegans (C. elegans) has been developed. This device is mainly composed of a microfluidic chip, a dual imaging module, and an imaging acquisition and processing module, which are integrated into a compact system. The microfluidic chip is designed as a platform for monitoring C. elegans, which is captured in an imaging region through a suction structure in the microfluidic chip. A dual imaging module is designed to obtain the images of bright field and fluorescence of C. elegans. The behaviors of C. elegans are analyzed based on the dual‐mode imaging of bright field and fluorescence to assess the degree of damage due to microgravity. A comparative study using a commercial microscope is also conducted to demonstrate the unique advantage of the developed system under the simulated microgravity. The results show that the developed system can evaluate the damage of C. elegans under microgravity accurately and conveniently. Furthermore, this device has compact size and weight, easy operation, and low‐cost, which could be highly advantageous for on‐site evaluation of the damage to microorganisms under microgravity in a space station.     

A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with ¹¹Β, ¹²C, ¹⁴Ν, ¹⁶Ο, ²⁰Νe, ⁴⁰Αr, ²⁸Si and ⁵⁶Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.     

加速溶剂萃取-凝胶渗透色谱净化-气相色谱快速分析动物源性食品中残留的多种有机磷农药

建立了动物源性食品猪肉、牛肉、鸡肉及鱼肉中36种有机磷农药残留的快速分析方法。以乙腈作为溶剂,对试样采用加速溶剂萃取仪萃取,自动凝胶渗透色谱仪净化预处理,N-丙基乙二胺(PSA)填料再净化,毛细管气相色谱法分离,火焰光度检测器(磷型)检测,内标法定量。该方法分离效果良好,重现性好,灵敏度、精密度高,杂质干扰少。36种有机磷农药的检测限(LOD)为0.0012 mg/kg(乙拌磷)～0.014 mg/kg(吡唑硫磷),定量限(LOQ)为0.004 mg/kg(乙拌磷)～0.047 mg/kg(吡唑硫磷)。当试样中有机磷农药的添加浓度分别为0.05,0.1,0.2 mg/kg时,回收率为58.2%～106.3%。方法的最低检测限和添加回收率均符合农药残留分析的要求。