Toward automated biochemotype annotation for large compound libraries

Summary Combinatorial chemistry allows scientists to probe large synthetically accessible chemical space. However, identifying the sub-space which is selectively associated with an interested biological target, is crucial to drug discovery and life sciences. This paper describes a process to automatically annotate biochemotypes of compounds in a library and thus to identify bioactivity related chemotypes (biochemotypes) from a large library of compounds. The process consists of two steps: (1) predicting all possible bioactivities for each compound in a library, and (2) deriving possible biochemotypes based on predictions. The Prediction of Activity Spectra for Substances program (PASS) was used in the first step. In second step, structural similarity and scaffold-hopping technologies are employed. These technologies are used to derive biochemotypes from bioactivity predictions and the corresponding annotated biochemotypes from MDL Drug Data Report (MDDR) database. About a one million (982,889) commercially available compound library (CACL) has been tested using this process. This paper demonstrates the feasibility of automatically annotating biochemotypes for large libraries of compounds. Nevertheless, some issues need to be considered in order to improve the process. First, the prediction accuracy of PASS program has no significant correlation with the number of compounds in a training set. Larger training sets do not necessarily increase the maximal error of prediction (MEP), nor do they increase the hit structural diversity. Smaller training sets do not necessarily decrease MEP, nor do they decrease the hit structural diversity. Second, the success of systematic bioactivity prediction relies on modeling, training data, and the definition of bioactivities (biochemotype ontology). Unfortunately, the biochemotype ontology was not well developed in the PASS program. Consequently, “ill-defined” bioactivities can reduce the quality of predictions. This paper suggests the ways in which the systematic bioactivities prediction program should be improved.     

The concept of constant emission yield in GDOES

This review paper describes the evolution of the quantification procedure for compositional depth profiling (CDP) in glow discharge optical emission spectrometry (GD-OES), based on the constant emission yield concept. The concept of emission yield (EY) is defined and ways of measuring it experimentally are discussed. The history of the development of quantitative CDP is reviewed, which shows that all of the different approaches depend on the assumption that the EY is essentially a matrix-independent quantity. Particular emphasis is placed on the dependence of the EY on the plasma parameters of current, voltage, power and pressure. In short, impedance changes (current voltage) can significantly affect the emission yield and should either be corrected mathematically or the impedance should be kept constant by pressure regulation in order to obtain reliable results from GDOES CDP. On the other hand, the effect of varying the pressure on the emission yield can be considered to be minor within the limits of practical operating conditions for most CDP applications. It is worth, however, bearing in mind that varying the discharge pressure has a significant effect on the plasma processes, and does affect the emission yield when these variations are large. The experimental results obtained for the emission yield are related to the results from theoretical model calculations published on the subject.     

Use of LIBS for rapid characterization of parchment

Parchment from different sources has been analyzed by laser-induced breakdown spectroscopy (LIBS) for determination of Ca, Na, K, Mg, Fe, Cu, and Mn. The LIBS results were compared with results from inductively coupled plasma spectroscopy (ICP) and good correlation was obtained. Rapid distinction between modern and historical samples was achieved by discriminant analysis of the LIBS data. Animal type recognition was also possible on the basis of Mg/Cu emission peak ratio and Mg depth profiling.     

Profiling of Piper betle Linn. cultivars by direct analysis in real time mass spectrometric technique

Piper betle Linn. is a traditional plant associated with the Asian and southeast Asian cultures. Its use is also recorded in folk medicines in these regions. Several of its medicinal properties have recently been proven. Phytochemical analysis showed the presence of mainly terpenes and phenols in betel leaves. These constituents vary in the different cultivars of Piper betle. In this paper we have attempted to profile eight locally available betel cultivars using the recently developed mass spectral ionization technique of direct analysis in real time (DART). Principal component analysis has also been employed to analyze the DART MS data of these betel cultivars. The results show that the cultivars of Piper betle could be differentiated using DART MS data.     

Comprehensive analysis of microRNA-mRNA co-expression in circadian rhythm

To investigate the potential role of microRNA (miRNA) in the regulation of circadian rhythm, we performed microarray-based expression profiling study of both miRNA and mRNA in mouse liver for 48 h at 4-hour intervals. Circadian miRNA-mRNA target pair is defined as the pair both elements of which show circadian expression patterns and the sequence-based target relationship of which can be predicted. Circadian initiators, Clock and Bmal1, showed inversely correlated circadian expression patterns against their corresponding miRNAs, miR-181d and miR-191, targeting them. In contrast, circadian suppressors, Per, Cry, CKIe and Rev-erba, exhibited positively correlated circadian expression patterns to their corresponding miRNAs. Genomic location analysis revealed that intronic region showed higher abundance of cyclic than non-cyclic miRNAs targeting circadian genes while other (i.e., 3''-UTR, exon and intergenic) regions showed no difference. It is suggested that miRNAs are involved in the regulation of peripheral circadian rhythm in mouse liver by modulating Clock:Bmal1 complex. Identifying specific miRNAs and their targets that are critically involved in circadian rhythm will provide a better understanding of the regulation of circadian-clock system.     

Parameter selection for peak alignment in chromatographic sample profiling: objective quality indicators and use of control samples

In chromatographic profiling applications, peak alignment is often essential as most chromatographic systems exhibit small peak shifts over time. When using currently available alignment algorithms, there are several parameters that determine the outcome of the alignment process. Selecting the optimum set of parameters, however, is not straightforward, and the quality of an alignment result is at least partly determined by subjective decisions. Here, we demonstrate a new strategy to objectively determine the quality of an alignment result. This strategy makes use of a set of control samples that are analysed both spiked and non-spiked. With this set, not only the system and the method can be checked but also the quality of the peak alignment can be evaluated. The developed strategy was tested on a representative metabolomics data set using three software packages, namely Markerlynx™, MZmine and MetAlign. The results indicate that the method was able to assess and define the quality of an alignment process without any subjective interference of the analyst, making the method a valuable contribution to the data handling process of chromatography-based metabolomics data.     

A solution to the 1D NMR alignment problem using an extended generalized fuzzy Hough transform and mode support

This paper approaches the problem of intersample peak correspondence in the context of later applying statistical data analysis techniques to 1D ¹H-nuclear magnetic resonance (NMR) data. Any data analysis methodology will fail to produce meaningful results if the analyzed data table is not synchronized, i.e., each analyzed variable frequency (Hz) does not originate from the same chemical source throughout the entire dataset. This is typically the case when dealing with NMR data from biological samples. In this paper, we present a new state of the art for solving this problem using the generalized fuzzy Hough transform (GFHT). This paper describes significant improvements since the method was introduced for NMR datasets of plasma in Csenki et al. (Anal Bioanal Chem 389:875-885, 15) and is now capable of synchronizing peaks from more complex datasets such as urine as well as plasma data. We present a novel way of globally modeling peak shifts using principal component analysis, a new algorithm for calculating the transform and an effective peak detection algorithm. The algorithm is applied to two real metabonomic ¹H-NMR datasets and the properties of the method are compared to bucketing. We implicitly prove that GFHT establishes the objectively true correspondence. Desirable features of the GFHT are: (1) intersample peak correspondence even if peaks change order on the frequency axis and (2) the method is symmetric with respect to the samples. Figure From chaos to order: heatmaps of a H-NMR spectral segment prior and post sorting on one peak position. Post sorting sample order reveals that peak positions exhibits distinctive patterns which are modeled by the GFHT to establish correspondence. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

高压射频等离子体增强化学气相沉积制备高效率硅薄膜电池的若干关键问题研究

报道了采用高压射频等离子体增强化学气相沉积(RF-PECVD) 制备高效率单结微晶硅电池和非晶硅/微晶硅叠层电池时几个关键问题的研究结果, 主要包括: 1)器件质量级本征微晶硅材料工艺窗口的确定及其结构和光电性能表征; 2)孵化层的形成机理以及减小孵化层的有效方法; 3)氢稀释调制技术对本征层晶化率分布及其对提高电池性能的作用; 4)高电导、高晶化率的微晶硅p型窗口层材料的获得, 及其对减小微晶硅电池p/i界面孵化层厚度和提高电池性能的作用等. 在解决上述问题的基础上, 采用高压RF-PECVD制备的单结微晶硅电池效率达8.16%, 非晶硅/微晶硅叠层电池效率11.61%.