基于集成类随机森林方法的神经胶质瘤特征基因选择的研究

神经胶质瘤(glioma)是一种严重的颅内肿瘤疾病,具有高复发率、高死亡率和低治愈率等特点。利用基因微阵列数据识别与神经胶质瘤相关的特征基因,对该疾病的临床诊断和生物医学研究将起到有益的参考和借鉴作用。作者针对神经胶质瘤数据,提出了一种集成类随机森林特征基因选择方法。首先应用有监督奇异值分解对数据进行降维并粗选出基因;其次应用类随机森林特征选择方法选出特征基因。实验结果显示,该方法对分类器的适应性强;对比其他方法,分类率优势明显;更重要的是,在选出的前50个特征基因中有39个基因与神经胶质瘤或肿瘤细胞生物过程存在着密切联系,证实该方法不仅保持了较高的分类率,而且保证了选择的特征基因具有很强的生物学关联意义,具有较高的可行性和实用性。     

Improving the objectivity of sustainability indices by a novel approach for combining contrasting effects: Happy Planet Index revisited

Measuring complex and rather intuitive qualities such as sustainability requires combining many different measures together. These measures often quantify contrasting effects. The resulting composite index then also depends not only on the component indices but also on the way that these have been combined together. An example of such a measure is the Happy Planet Index (HPI) that aggregates information on positive qualities like life-expectancy and human well-being with negative ones like ecological footprint to rank countries according to their sustainability. However, since component indices are often mutually correlated and feature quite different distributions of entities ranked, elaborate rules are used in the process of combination. As a result, the resulting composite index may look somewhat contrived and its rankings may depend heavily on subjective parameters in the combination process. We propose a geometrically motivated parameter-free method for combining indices with contrasting effects together. The method is independent of the number of contrasting indices to be combined and eliminates mutual correlation between component indices by using Singular Value Decomposition (SVD) analysis. As an example of its use, we revisit the Happy Planet Index and demonstrate the impact of adding new component indices to HPI on ranking nations by their sustainability.     

Analytical trapping: extraction of time-independent structures from time-dependent crystallographic data

All chemical and biological reactions involve atomic motion, embodied in dynamic structural changes. Identifying these changes is the goal of time-resolved crystallography. The "raw" output of a time-resolved macromolecular crystallography experiment is the time-dependent set of difference electron density maps that span the desired time range and display the time-dependent changes in density (and underlying structure) as the reaction progresses. The goal is to interpret such data in terms of a small number of crystallographically refinable, time-independent structures, each associated with a reaction intermediate; to establish the pathways and rate coefficients by which the intermediates interconvert; and thus to establish a chemical kinetic mechanism. We review briefly the various strategies that may be used to achieve this goal and concentrate on two promising advances: singular value decomposition and cluster analysis. The strategies are illustrated by using data on the photocycle of the bacterial blue light photoreceptor, photoactive yellow protein.     

基于EMD的河北省粮食产量波动的结构特征及其成因的分析

在分析河北省粮食产量变化的时间序列总体特征的基础之上,对河北粮食产量波动结构特征及其成因进行研究,旨在为指导河北省粮食安全生产提供科学的理论依据.综合运用EMD法、剩余法和方差分析法,对河北粮食产量波动结构特征及其成因进行研究.结果表明:在品种上,小麦和玉米两大主要粮食作物产量比重呈现递增趋势,两者之和达到了89.91%,其变动对粮食总产的变动起着举足轻重的作用;杂粮作物和稻谷所占比例较小,且呈逐年缩减趋势;小麦、玉米产量波动的方差贡献率分别为64.36%和31.72%,是河北省粮食总产波动的第一和第二主控作物;稻谷和杂粮作物由于其粮食产量基数较小对河北粮食总产波动的影响较小.在空间上,河北省粮食产量的波动值分布在0～0.35之间的地区比例约为90%,表明其强度主要处于中等水平;燕山太行山山前平原区和冀鲁豫低洼平原区粮食产量波动的方差贡献率分别为22.05%和17.82%,是河北省粮食总产波动的第一和第二主控区;辽吉西蒙东南冀北山地和后山坝上高原区的粮食产量波动对河北省粮食总产波动影响较小.研究表明综合运用EMD法、剩余法和方差分析法,对河北粮食产量波动结构特征及其成因进行研究是可行的.利用这种综合方法,提高了单独使用一种方法进行波动性分析的精度,为分析波动问题提供了新的科学的理论和方法.     

Human serum albumin binding ibuprofen: A 3D description of the unfolding pathway in urea

Small angle X-ray scattering (SAXS) technique, supported by light scattering measurements and spectroscopic data (circular dichroism and fluorescence) allowed us to restore the 3D structure at low resolution of defatted human serum albumin (HSA) in interaction with ibuprofen. The data were carried out on a set of HSA solutions with urea concentrations between 0.00 and 9.00 M. The Singular Value Decomposition method, applied to the complete SAXS data set allowed us to distinguish three different states in solution. In particular a native conformation N (at 0.00 M urea), an intermediate I1 (at 6.05 M urea) and an unfolded structure U (at 9.00 M urea) were recognized. The low-resolution structures of these states were obtained by exploiting both ab initio and rigid body fitting methods. In particular, for the protein without denaturant, a conformation recently described (Leggio et al., PCCP, 2008, 10, 6741–6750), very similar to the crystallographic heart shape, with only a slight reciprocal movement of the three domains, was confirmed. The I1 structure was instead characterized by only a closed domain (domain III) and finally, the recovered structure of the U state revealed the characteristic feature of a completely open state. A direct comparison with the free HSA pointed out that the presence of the ibuprofen provokes a shift of the equilibrium towards higher urea concentrations without changing the unfolding sequence. The work represents a type of analysis which could be exploited in future investigations on proteins in solution, in the binding of drugs or endogenous compounds and in the pharmacokinetic properties as well as in the study of allosteric effects, cooperation or anticooperation mechanisms.     

Intractable Unphysiologically Low Adenylate Energy Charge Values in Synaptosome Fractions: An Explanatory Hypothesis Based on the Fraction''s Heterogeneity

Synaptosomes prepared and incubated in a variety of ways from rat cerebra exhibited intractable, unphysiologically low adenylate energy charge values (approximately 0.37-0.60), low total adenine nucleotide contents (approximately 8-10 nmol/mg protein), and much higher adenylate kinase apparent Keq values (approximately 3-8) as compared to intact brain tissue (values of approximately 0.90, 25 nmol/mg, and 0.74, respectively). Synaptosomes prepared from mouse, dog, and chicken cerebra had values essentially identical to those from rat. When incubated under oxygen in a physiological salt solution containing glucose, synaptosomes metabolized more glucose to lactic acid than to CO2, and the addition of 100 microM veratridine caused a two- to threefold stimulation of O2 uptake, lactate accumulation, and CO2 output. It is known that synaptosome fractions contain a substantial number (at least 30-45% by volume) of cytoplasm-containing particles devoid of mitochondria (henceforth termed "cytosolic particles"), and that approximately 80% of brain hexokinase is bound to the outer mitochondrial membrane. For the cytosolic particles, lacking oxidative phosphorylation, to maintain their "in vivo" ATP turnover would require about a 19-fold increase in the glycolytic rate, which is not possible due to limiting amounts of hexokinase, and thus these particles are postulated to be responsible for the high level of aerobic lactate accumulation and the intractable low energy charge values found in synaptosome fractions. The mitochondria-containing particles are postulated to have a normal energy charge, a submaximal glycolytic rate, and minimal lactate production, on the basis of the capacity of veratridine to stimulate synaptosomal O2 uptake and CO2 and lactate output. Calculations based on this "two populations of particles" hypothesis indicate that for synaptosome fractions in general, (1) the cytosolic particles contain approximately 35-64% of the total adenine nucleotides and maintain an energy charge of approximately 0.12; (2) the cytosolic particles and mitochondria-containing particles have adenylate kinase apparent Keq values of approximately 0.21-1.66 and 0.74, respectively, revealing that the higher apparent Keq values of the synaptosome fractions probably are not real departures from equilibrium: and (3) approximately 31-45% of synaptosome fraction protein is contained in debris, which, when taken into account, yields total adenine nucleotide contents in the cytosolic particles and mitochondria-containing particles of approximately 15-24 and approximately 11-19 nmol/mg of particle protein, respectively.     

Composite Subsidence Vulnerability Assessment Based on an Index Model and Index Decomposition Method

The threat of damage to buildings and other infrastructures resulting from land subsidence associated with groundwater pumping in urbanized areas is an ongoing problem requiring assessment. An important goal of subsidence vulnerability assessment is to construct a composite subsidence vulnerability index (SVI) that is represented by a set of indicators that focuses on four different thematic factors: physical, social, economic, and environmental vulnerability. These indicators are evaluated on the basis of indicator selection principles and then weighted by their contribution rate to the overall index. The weights reflect different measures assigned to the township-specific conditions. A complete and composite subsidence vulnerability assessment is developed in which future vulnerability management decision-making processes can be readily made. The vulnerability assessment includes not only the construction of the SVI, which involves selecting, assigning value to, weighting, and aggregating the vulnerability indicators, but also the presentation of the SVI decomposition. Research results demonstrate that a composite subsidence vulnerability assessment method can be made by first constructing and then decomposition-presenting the overall SVI. This allows for the relative comparison of subsidence vulnerability and the identification of the main vulnerable indicators; thus providing subsidence risk, which represents an important step toward vulnerability management of water resources.     

microRNA的实验和生物信息学开发方法

mircroRNA是一类约22nt的内源小分子RNA,普遍存在于真核生物体内,它通过与靶基因互补结合来调控基因表达,从而对生物体的生长、发育等起到重要的调节作用。随着生物学技术的不断发展,mircroRNA研究的越发深入,越来越多的mircroRNA被开发出来。本文结合了mircroRNA的生理特点,从RNA、DNA和生物信息学预测这3个方面归纳总结有关开发microRNA的方法,以及由此衍生出来的相关的研究方法。通过对这些研究方法的分类总结,不但为mircroRNA以后的研究工作奠定良好的基础,而且有利于新技术的研发。     

几丁糖乙醇含量测定的研究——顶空法

目的探讨简便实用的乙醇含量的测定方法。方法在企标基础上,改用恒温法进行测定,同时采用一定的顶空瓶保温措施降低温度散失。结果采用改进后的方法进行测定,其精密度达到分析要求操作简单实用。结论改进后的方法完全符合实际生产需要,对生产具有较好的指导意义。     

The multiple-minima problem in the conformational analysis of polypeptides. III. An Electrostatically Driven Monte Carlo Method: Tests on enkephalin

The three-dimensional conformation of Met-enkephalin, corresponding to the lowest minimum of the empirical potential energy function ECEPP/2 (empirical conformational energy program for peptides), has been determined using a new algorithm, viz. the Electrostatically Driven Monte Carlo Method. This methodology assumes that a polypeptide or protein molecule is driven toward the native structure by the combined action of electrostatic interactions and stochastic conformational changes associated with thermal movements. These features are included in the algorithm that produces a Monte Carlo search in the conformational hyperspace of the polypeptide, using electrostatic predictions and a random sampling technique to locate low-energy conformations. In addition, we have incorporated an alternative mechanism that allows the structure to escape from some conformational regions representing metastable local energy minima and even from regions of the conformational space with great stability. In 33 test calculations on Met-enkephalin, starting from arbitrary or completely random conformations, the structure corresponding to the global energy minimum was found inall the cases analyzed, with a relatively small search of the conformational space. Some of these starting conformations wereright orleft-handed -helices, characterized by good electrostatic interactions involving their backbone peptide dipoles; nevertheless, the procedure was able to convert such locally stable structures to the global-minimum conformation.On leave from the National University of San Luis, Faculty of Sciences and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Matemática Aplicada, San Luis, Ejército de los Andes 950, 5700 San Luis, Argentina.     

Recent Advances in the Identification of Replication Origins Based on the Z-curve Method

Precise DNA replication is critical for the maintenance of genetic integrity in all organisms. In all three domains of life, DNA replication starts at a specialized locus, termed as the replication origin, oriC or ORI, and its identification is vital to understanding the complex replication process. In bacteria and eukaryotes, replication initiates from single and multiple origins, respectively, while archaea can adopt either of the two modes. The Z-curve method has been successfully used to identify replication origins in genomes of various species, including multiple oriCs in some archaea. Based on the Z-curve method and comparative genomics analysis, we have developed a web-based system, Ori-Finder, for finding oriCs in bacterial genomes with high accuracy. Predicted oriC regions in bacterial genomes are organized into an online database, DoriC. Recently, archaeal oriC regions identified by both in vivo and in silico methods have also been included in the database. Here, we summarize the recent advances of in silico prediction of oriCs in bacterial and archaeal genomes using the Z-curve based method.     

等位基因多态性群体遗传结构的多元非线性分析方法

长期以来,对于多维基因多态性数据的多元统计分析,如计算遗传距离时昕用的聚类分析、分析群体遗传结构时所用的主成分分析、因子分析和典型相关分析等,一直应用为无约束条件数据而设计的经典多元线性分析方法,并没有注意基因多态性数据的“闭合效应”所带来的问题。从分析基因多态性数据的分布和结构特征入手,文中指出了基因多态性分布具有“闭合数据”的特点,分析了由于“闭合效应”的影响,经典多元线性方法用于群体遗传结构分析昕面临的困难。根据成分数据统计分析的理论和方法,提出了基因多态性群体遗传结构的多元非线性分析基本方法。并以主成分分析为例,通过实例比较和分析了经典线性主成分分析和“对数比”非线性主成分分析的结果,证明“对数比”非线性主成分分析方法是研究基因多态性群体遗传结构的良好方法,具有特异、灵敏等优点,其结果符合群体遗传学规律。     

Fungal microbiota dynamics as a postmortem investigation tool: focus on Aspergillus,Penicillium and Candida species

Aims: To investigate the presence of fungi during three human decomposition stages: bloated, putrefaction and skeletonization. Methods and Results: The samples were gathered in the city of Fortaleza, Ceará, Brazil, from the public morgue and cemeteries. The material was submitted to conventional mycological procedures by direct examination and macro/micro morphological and biochemical analyses. The main fungi isolated were Aspergillus spp., Penicillium spp. and Candida spp. in the bloated stage (n = 34 cadavers) and in the putrefaction stage (n = 6 cadavers), while in the skeletonization stage (n = 20 cadavers), the main fungi were Aspergillus spp., Penicillium spp. and Mucor sp. Conclusions: Aspergillus, Penicillium and Candida species were associated with decomposed human cadavers. Significance and Impact of the Study: These findings enable tracing out the profile of fungal communities of human cadavers for the first time. However, much more research will be necessary to develop this new segment of mycology and to enable its routine use in forensic science.     

A New Method of Regression of Time-series Based on a Mathematical Connection Between Path and Compartmental Analyses

In the regression analysis of time-series the error terms may be serially correlated with the results. In this case the possibility arises that the expectations and adjustment processes are themselves mis-specifications of the correct behavioural relationships. In this paper an analogy is pointed out between the compartmental-analysis and the path analysis by the author. It will be argued that the time-series of the standardized partial regression coefficients (path coefficients or beta weights) computed from the cross-sectional data, have to be analysed instead of applying ordinary least squares directly to the timeseries. An application of the new method is briefly discussed.     

Modeling of Actual Eukaryotic Control Gene Subnetworks Based on the Method of Generalized Threshold Models

Mathematical and computational means are developed that take into consideration the specifics of control processes at the molecular level and allow one to obtain both qualitative and quantitative patterns of gene network dynamics. Using the method of generalized threshold models, models are constructed for the Arabidopsis thalianaflower morphogenesis control subsystem and gene subnetwork controlling the Drosophila melanogasterearly ontogeny. The dynamics of these systems are investigated: kinetic curves are computed for molecular components (RNA, proteins), possible modes of functioning and steady states of the nets are revealed and biologically interpreted. The models are shown to be adequate to the real processes. The effectiveness of the generalized threshold model method is evaluated in the analysis of the actual eukaryotic gene networks.     

Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features

OBJECTIVES: To analyze the distant metastasis possibility based on computed tomography (CT) radiomic features in patients with lung cancer. METHODS: This was a retrospective analysis of 348 patients with lung cancer enrolled between 2014 and February 2015. A feature set containing clinical features and 485 radiomic features was extracted from the pretherapy CT images. Feature selection via concave minimization (FSV) was used to select effective features. A support vector machine (SVM) was used to evaluate the predictive ability of each feature. RESULTS: Four radiomic features and three clinical features were obtained by FSV feature selection. Classification accuracy by the proposed SVM with SGD method was 71.02%, and the area under the curve was 72.84% with only the radiomic features extracted from CT. After the addition of clinical features, 89.09% can be achieved. CONCLUSION: The radiomic features of the pretherapy CT images may be used as predictors of distant metastasis. And it also can be used in combination with the patient's gender and tumor T and N phase information to diagnose the possibility of distant metastasis in lung cancer.     

Physiological Daily Inhalation Rates for Free-Living Individuals Aged 2.6 Months to 96 Years Based on Doubly Labeled Water Measurements: Comparison with Time-Activity-Ventilation and Metabolic Energy Conversion Estimates

In the first part of this article, a critical review of traditional approaches used to estimate daily inhalation rates as a function of age for health risk assessment purposes shows that such rates are not totally reliable due to various biases introduced by both quantitative and qualitative deficiencies regarding certain input parameters. In the second part, the magnitude of under- and overestimations of published inhalation rates derived from each approach is described by a comparison with new sets of physiological daily inhalation rates and distribution percentile values based on total daily energy expenditures (TDEEs) measured by the doubly labeled water (DLW) method. TDEEs are derived from the analysis of deuterium (²H) and heavy oxygen-18 (¹⁸O) in urine samples by gas-isotope-ratio mass spectrometry during an aggregate period of over 20,000 days for unrestrained free-living normal-weight individuals aged 2.6 months to 96 years (n = 1252). Regarding physiological values based on DLW measurements, opposite tendencies have been observed between two sets of estimates using time-activity patterns both biased by conservative input data assumptions during sleep and light activities: most estimates based on the time-activity-ventilation approach are overestimated, whereas most of those using metabolic equivalent approach are underestimated. Erroneous food intakes have clearly lead to underestimated rates when used in daily food-energy intake (EFD) and Parameter A approaches. With the latter approach, overestimated basal metabolic rates (BMRs) used in EFD/BMR ratios contribute to the underestimation of inhalation values. Few mean daily inhalation rates and Monte Carlo simulation percentiles based on traditional approaches (57 out of 253) are close to physiological values within a gap of ± 5% or less. Aggregate errors in all estimates (in m³/day and m³/kg-day) vary from -52 to +126%. The most accurate daily inhalation rates are those based on DLW measurements with an error of about ± 5%, as calculated in previous studies for free-living males and females aged 1 month to 96 years and pregnant and lactating adolescents and women aged 11 to 55 years during real-life situations in their normal surroundings.