Penalized estimation of sparse concentration matrices based on prior knowledge with applications to placenta elemental data

Identifying patterns of association or dependency among high-dimensional biological datasets with sparse precision matrices remains a challenge. In this paper, we introduce a weighted sparse Gaussian graphical model that can incorporate prior knowledge to infer the structure of the network of trace element concentrations, including essential elements as well as toxic metals and metaloids measured in the human placentas. We present the weighted L1 penalized regularization procedure for estimating the sparse precision matrix in the setting of Gaussian graphical models. First, we use simulation models to demonstrate that the proposed method yields a better estimate of the precision matrix than the procedures that fail to account for the prior knowledge of the network structure. Then, we apply this method to estimate sparse element concentration matrices of placental biopsies from the New Hampshire Birth Cohort Study. The chemical architecture for elements is complex; thus, the method proposed herein was applied to infer the dependency structures of the elements using prior knowledge of their biological roles.     

A New Advance in Preparation of Mo-S(O) Clusters

ＡＮｅｗＡｄｖａｎｃｅｉｎＰｒｅｐａｒａｔｉｏｎｏｆＭｏ－Ｓ（Ｏ）Ｃｌｕｓｔｅｒｓ￥ＹａｏＹｕａｎ－Ｇｅｎ；ＷｕＬｉｎｇ；ＺｈｕＹｏｎｇ－Ｂａｏ；ＬｕＳｈａｏ－Ｆａｎｇ；（ＦｕｊｔａｎＩｎｓｔｉｔｕｔｅｏｆＲｅｓｅａｒｃｈｏｎｔｈｅＳｔｒｕｃｔｕｒｅ...     

对211例类风湿关节炎患者微量元素的测定

用同位素激发Ｘ射线荧光分析对２１１例类风湿关节炎患者发中１０种常量及微量元素测定，以探索类风湿关节病与微量元素之间的关系．结果表明：全部女性患者发锌含量明显降低，除３０～３９岁及５０～５９岁年龄组Ｐ＜０．０５外，其余各组均Ｐ＜０．０１。而２０～２９岁男性组患者发锌含量也低，Ｐ＜０．０１。男女患者各组发锶含量较对照组均低，且有明显差异（除男性２０～２９岁组及５０￣５９岁组Ｐ＜０．０５，其余各组均ｐ＜０．０１）。提示类风湿关节病患者发中锌、锶含量较正常人低。因此，如临床上补充锌和锶元素，可能是有效治疗类风湿关节病的新途径．     

Prediction of Rheological Properties of Multi-Component Dispersions by Using Artificial Neural Networks

This article shows the ability of artificial neural network (ANN) technology for predicting the correlation between rheological properties of multi-component food model systems and their chemical compositions. Multi-component food model systems were made of whey protein isolate (WPI) (2, 4 wt%), Iranian tragacanth gum (TG) (Astragalus gossypinus) (0.5, 1 wt%) and oleic acid (5, 10% v/v). The input parameters of the neural networks (NN) were these chemical compositions, namely WPI and TG concentrations, and oleic acid volume fractions. The output parameters of the NN models were rheological properties of multi-component food model systems (flow and consistency indices, viscosity, loss and storage moduli). Results showed that, ANN with training algorithm of back propagation (BP) was the best one for the creation of nonlinear mapping between input and output parameters. The best topology was 3-10-5. The ANN model predicted the rheological properties of multi-component food model systems with average RMSE 4.529 and average MAE 3.018. These results show that the ANN can potentially be used to estimate rheological parameters of multi-component food model systems from chemical composition. This development may have significant potential to improve product quality control and reduce time and costs by minimizing the rheological experiments.     

Prediction of gaseous emissions from industrial stacks using an artificial intelligence method

A novel technique based on artificial intelligence methods able to predict pollutant emission concentrations from industrial stacks is presented. This procedure combines regression and classification problems into a unified technique, named minimax decision procedure. The core of this procedure is based on the minimax probability machine regression model. Using experimental databases, the trend of pollutant emissions and the level of pollution for one industrial thermal power station stack were presented. Based on this unified technique, numerical experiments provided the estimates of concentrations of CO, NO_x, NO, and SO₂ confirming the predictive power of this procedure. Presented at the 33rd International Conference of the Slovak Society of Chemical Engineering, Tatranské Matliare, 22–26 May 2006.     

~(160)Tb同位素示踪研究稀土元素铽在雏鸡体内的分布和转运

160Tb－EDTA注入美国海兰鸡种蛋，孵出雏鸡，解剖取21种组织、器官．用γ能谱测定160Tb．证明160Tb-EDTA能透过种蛋胎膜进入雏鸡各组织和器官中。     

107例高龄老人头发锰铜锌铬微量元素含量的探讨

对１０７例７０～８０岁高龄老人作头发８种微量元素含量测定，测定结果以Ｍｎ，Ｃｕ，Ｚｎ，Ｃｒ与长寿地区广西巴马县老人作比较，结果表明本组是低Ｍｎ、高Ｃｕ、低Ｚｎ、高Ｃｒ，差异极为显著（Ｐ＜０．００１），符合非长寿地区低Ｍｎ的现状．本组与４５～５９岁，６０～６９岁二个年龄组比较，本组为高Ｍｎ、低Ｃｕ、低Ｚｎ、高Ｃｒ，差异均显著（Ｐ＜０．０５），表明本组微量元素组合优于７０岁前老人．从本组男、女微量元素比较，女性表现为高Ｍｎ、高Ｓｒ、高Ｃａ、低Ｃｒ、低Ｃｕ，说明老年女性在抗衰防衰方面优于老年男性．     

Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs

The treatment of complex diseases by using multiple drugs has become popular. However, drug-drug interactions (DDI) may give rise to the risk of unanticipated adverse effects and even unknown toxicity. Therefore, for polypharmacy safety it is crucial to identify DDIs and explore their underlying mechanisms. The detection of DDI in the wet lab is expensive and time-consuming, due to the need for experimental research over a large volume of drug combinations. Although many computational methods have been developed to predict DDIs, most of these are incapable of predicting potential DDIs between drugs within the DDI network and new drugs from outside the DDI network. In addition, they are not designed to explore the underlying mechanisms of DDIs and lack interpretative capacity. Thus, here we propose a novel method of GNN-DDI to predict potential DDIs by constructing a five-layer graph attention network to identify k-hops low-dimensional feature representations for each drug from its chemical molecular graph, concatenating all identified features of each drug pair, and inputting them into a MLP predictor to obtain the final DDI prediction score. The experimental results demonstrate that our GNN-DDI is suitable for each of two DDI predicting scenarios, namely the potential DDIs among known drugs in the DDI network and those between drugs within the DDI network and new drugs from outside DDI network. The case study indicates that our method can explore the specific drug substructures that lead to the potential DDIs, which helps to improve interpretability and discover the underlying interaction mechanisms of drug pairs.     

Trace element determination using static high-sensitivity inductively coupled plasma optical emission spectrometry (SHIP-OES)

A low-flow air-cooled inductively coupled plasma (ICP) design for optical emission spectrometry (OES) with axial plasma viewing is described and an evaluation of its analytical capabilities in trace element determinations is presented. Main advantage is a total argon consumption of 0.6 L min⁻¹ in contrast to 15 L min⁻¹ using conventional ICP sources.The torch was evaluated in trace element determinations and studied in direct comparison with a conventional torch under the same conditions with the same OES system, ultrasonic nebulization (USN) and single-element optimization. A variety of parameters (x-y-position of the torch, rf power, external air cooling, gas flow rates and USN operation parameters) was optimized to achieve limits of detection (LOD) which are competitive to those of a conventional plasma source.Ionic to atomic line intensity ratios for magnesium were studied at different radio frequency (rf) power conditions and different sample carrier gas flows to characterize the robustness of the excitation source. A linear dynamic range of three to five orders of magnitude was determined under compromise conditions in multi-element mode. The accuracy of the system was investigated by the determination of Co, Cr, Mn, Zn in two certified reference materials (CRM): CRM 075c (Copper with added impurities), and CRM 281 (Trace elements in rye grass). With standard addition values of 2.44 ± 0.04 and 3.19 ± 0.21 μg g⁻¹ for Co and Mn in the CRM 075c and 2.32 ± 0.09, 81.8 ± 0.4, 32.2 ± 3.9 for Cr, Mn and Zn, respectively, were determined in the samples and found to be in good agreement with the reported values; recovery rates in the 98-108% range were obtained. No influence on the analysis by the matrix load in the sample was observed.     

Determination of trace amounts of sodium and lithium in zirconium dioxide (ZrO2) using liquid electrode plasma optical emission spectrometry

This paper describes a quantitative measurement of trace elements (Na, Li) in high purity zirconium dioxide powder using liquid electrode plasma optical emission spectrometry (LEP-OES). Conventionally, for such type of measurements, inductively coupled plasma optical emission spectrometry (ICP-OES) is frequently employed. The detection limits of elements in zirconium by ICP-OES are degraded due to the spectra interference between the trace elements and zirconium of the matrix, because zirconium is a line rich element in spectra obtained by ICP-OES. LEP-OES is an elemental analysis method developed by the authors. The measurement principle is simple, as follows. Sample solution is put into a narrow channel on a small cuvette and voltage pulse is applied from both ends of the channel. At the center of the channel which is made narrower, the voltage and current are concentrated there, and plasma is generated. From the emission of the plasma, the quantitative analysis of the elements in the solution is achieved. The LEP-OES has the property that the emission of zirconium is relatively weak, so that highly sensitive measurement of trace elements in zirconium matrix can be conducted without interference. Sample solution is prepared by dissolving high purity zirconium dioxide powder and trace amounts of Na or Li with sulfuric acid. The voltage dependence and the pulse width dependence of optical emission spectra are also investigated. With increase of the voltage or the pulse width, the ratio of emission intensities of Na to those of hydrogen increases. This suggests that the ratio of sensitivity of two elements is variable, that means the element selectivity is controllable to some extent by the measurement conditions in LEP-OES. In the case of Na and H, the ratio can be controlled from 7.4 to 21.6%. Finally, the detection limits (3S.D.) of the trace elements, Na and Li, in 4000 μg g⁻¹ zirconium dioxide aqueous solution are found to be 0.02 and 0.133 μg g⁻¹, respectively. These values correspond to 5 μg g⁻¹ for Na, 33.25 μg g⁻¹ for Li in original high purity zirconium dioxide powder. The correlation coefficient of calibration curve was 0.995 for Na, 0.985 for Li. Those are comparable to the literature values of detection limits using ICP-OES.     

生物质固体成型燃料热值和碳元素预测模型的建立

建立生物质固体成型燃料热值和碳元素预测模型。利用秸秆类生物质固体成型燃料的测试数据,以工业分析中的水分、灰分、挥发分和固定碳含量指标为4个自变量,分别以低位热值、高位热值和碳元素分析为因变量,通过多元线性回归模型(MLR)方法建立多元线性回归预测模型。内部检验和外部检验说明3组模型在应用域范围内均具有理想的预测能力,拟合效果良好,其中高位热值预测模型的R^2和R^2_(prep)分别为0.900和0.730,与已有研究相比,相对残差范围减小为–2.59%~2.26%,可为工业用途的生物质固体成型燃料的热值和碳元素分析快速做出反映。     

Temperature‐programmed reduction of silver(I) oxide using a titania‐supported silver catalyst under a H2 atmosphere

Reduction kinetics of silver(I) oxide using a titania‐supported silver catalyst was analyzed using temperature‐programmed reduction (TPR) with hydrogen as a reducing gas. Ag₂O reduction to Ag was observed in all samples as a single reduction step occurring at two reduction peaks. Observation of these reduction peaks indicates the existence of different lattice oxygen species, that is, surface and bulk, which are, respectively, attributed to surficial and pore‐deposited Ag₂O aggregates. The powdered samples exhibited high reducibility with average final oxidation states ranging from 0 to +0.18. The apparent activation energies for Ag₂O reduction to Ag metal were 73.35 and 81.71 kJ/mol for surficial and pore‐deposited Ag₂O aggregates, respectively. In this study, a unimolecular decay model was reported to accurately describe the reduction mechanism of Ag/TiO₂ catalysts. Hence, this would also infer that the catalyst reduction is rate‐limited by the nucleation of Ag metal instead of the topochemical reaction and the diffusion of hydrogen and oxygen molecules.     

硫醇保护金团簇的实验和理论研究现状

硫醇保护的金团簇(Au_m(SR)_n,m和n为Au和SR的数目)由于其特殊的光学、电学性质以及特别的物理/化学性质,在纳米催化、生物医学和光学设备中具有潜在的应用价值。Au₁₀₂(SR)₅₄和Au₂₅(SR)₁₈^-团簇单晶结构的确定是Au_m(SR)_n团簇合成的两大突破,它们的结构揭示了Au_m(SR)_n团簇中Au-S键新的成键特征和新的原子堆积方式。本文总结了Au_m(SR)_n团簇实验合成单晶结构的研究成果,概述了有谱图无单晶结构的Au_m(SR)_n团簇的实验进展,介绍了密度泛函理论预测Au_m(SR)_n团簇的研究概况,并结合本课题组的研究课题归纳了解释团簇稳定性和化学成键方式的超原子复合物模型,超原子网络模型和超级共价键模型及其应用。最后,对Au_m(SR)_n团簇的研究趋势进行了展望。     

七星剑花、肇芡的微量元素研究

七星剑花和肇芡是广东肇庆产的著名地道中药，本文首次报道两者的金属微量元素的测定方法及测定结果。并发现七星剑花钙的含量比其他微量元素高3个数量级，提示其水煮液及作为汤料有高级天然补钙剂的作用。     

麻甘合剂治疗小儿呼吸道感染

采用经验协方制成的麻甘合剂治疗小儿呼吸道感染，取得了较好的疗效。     

Preconcentration of Cd(II) and Cu(II) ions by coprecipitation without any carrier element in some food and water samples

A simple, rapid, sensitive and environmentally friendly separation and preconcentration procedure, based on the carrier element free coprecipitation (CEFC) of Cu(II) and Cd(II) ions by using an organic coprecipitant, 2-{[4-(4-fluorophenyl)-5-sulphanyl-4H-1,2,4-triazol-3-yl]methyl}-4-{[(4-fluorophenyl) methylene]amino}-5-(4-methylphenyl)-2,4-dihydro-3H-1,2,4-triazol-3-one (MEFMAT) was developed. The analyte ions were determined by flame atomic absorption spectrometric (FAAS) determinations. The optimum conditions for the coprecipitation process were investigated on several commonly tested experimental parameters such as pH of the solution, amount of MEFMAT, sample volume, standing time, centrifugation rate and time. The influences of some anions, cations and transition metals on the recoveries of analyte ions were also investigated, and no considerable interference was observed. The preconcentration factor was found to be 50. The detection limits for Cu(II) and Cd(II) ions based on the three times the standard deviation of the blanks (N:10) were found to be 1.49 and 0.45 μg L^{− 1}, respectively. The relative standard deviations were found to be lower than 3.5% for both analyte ions. The method was validated by analyzing two certified reference materials (CRM-TMDW-500 Drinking Water and CRM-SA-C Sandy Soil C) and spike tests. The procedure was successfully applied to sea water and stream water as liquid samples and tobacco, hazelnut and black tea as solid samples.     

Naked-eye detection of trace arsenic(V) in aqueous media using molybdenum-loaded chelating resin having beta-hydroxypropyl-di(beta-hydroxyethyl)amino moiety

A naked-eye detection method for a trace amount of arsenic in aqueous samples has been newly developed. The proposed method is based on the formation of a hetero poly acid in a chelating resin phase. Molybdenum loaded on a chelating resin having β-hydroxypropyl-di(β-hydroxyethyl) amino moiety reacts with arsenic(V) to form the hetero poly acid, which makes the resin beads greenish blue in the presence of a reducing agent under acidic conditions. It was also found that the intensity of the color of the resin depends on the concentration of arsenic(V) in the sample solutions. Since the development of the color occurs in 20 min by heating of the mixture at 40 °C, this system can provide a simple, rapid and low-cost detection method of a trace amount of arsenic(V) in an aqueous media. The detection limit of this method is 1 × 10⁻⁶ mol dm⁻³. A longer preconcentration time with the same resin gave the higher sensitivity of 1 × 10⁻⁷ mol dm⁻³ that is comparable with that of the instrumental analysis. The present method comprises both the concentration and detection step with the same solid material, and hence it gives higher sensitivity and easier handling than the ordinary colorimetric methods using a liquid medium.     

Prediction of the reduction potential of tris(2,2′‐bipyridinyl)iron(III/II) derivatives

The reduction potentials of a tris(2,2′‐bipyridinyl)iron (III/II) and iron(III/II) couples complexed with 2,2′‐bipyridinyl derivatives in acetonitrile are predicted using density functional theory. The calculation protocol proposed by Kim et al. (Kim, J. Park, Y. S. Lee, J. Comput. Chem. 2013, 34, 2233) showing reliable performance for the reduction potential is used. The four kinds of the functional groups, a methoxy group, a methyl group, a chlorine atom, and a cyanide group, are substituted at the ligands to examine the electronic effect on the reduction potential. Electron donating/withdrawing effect is analyzed by comparing the reduction potential having different substituents at the same position. The influence of the geometrical strain on the reduction potential is investigated. The good correlation between the experimental results and the calculated results is obtained. Not only the general trend, but also the detailed phenomena are correctly reproduced. The maximum deviation from the experimental value is 0.083 V for the methyl substitution at the position 4. The mean absolute error for the seven couples is 0.047 V. The difference of the reduction potential between the chlorine atom substituted at the positions 4 and 5, 0.1 V, is well described. The difference between the CN and the Cl substitution of 0.318 and 0.228 V for the position 4 and 5 is correctly obtained as 0.325 and 0.213 V, respectively. The simple linear relation between the lowest unoccupied molecular orbital (LUMO) energy of the Fe(III) complexes in solution and the calculated reduction potentials is obtained with the R² of 0.977. © 2014 Wiley Periodicals, Inc.     

Chelation-controlled reduction: an enantioselective synthesis of (−)-tarchonanthuslactone

The total synthesis of tarchonanthuslactone (1) has been achieved by two different routes. In the first approach, LiAlH₄-LiI reduction and RCM protocols, and in the second approach, Wacker oxidation and LiAlH₄-LiI reduction were used as key steps.