基于荧光光谱的五维数据处理方法

石油是一种成分复杂的混合物,通过常规的检测方法很难对其进行定性识别。本文用汽、煤、柴油的混合物来模拟环境中的油类污染物。汽、煤、柴油在特定波长范围的激发下可以发出含有物质自身信息的荧光,根据朗伯-比尔定律可知荧光强度与物质浓度成正比,利用该性质对特定物质进行识别。通过FS920稳态荧光光谱仪对样本进行测量,将实验所得的三维数据拓展为五维数据,提出了一种将展开偏最小二乘耦合到残差四线性的五维数据处理方法,同时采用五维平行因子法和该算法分解数据,实现了对汽、煤油的定量分析,并恢复出了其激发和发射光谱。结果表明,展开偏最小二乘法的分析效果更好。     

基于线性多步法的GM(1,1)模型优化及应用

为提高灰色GM(1,1)模型的模拟效果和预测精度,采用线性多步法中四阶Adams显式公式和隐式公式来优化GM(1,1)模型,改进模型的参数辨识,讨论所建立优化模型的适用范围、模拟效果和预测精度,并与最小二乘作为参数辨识的传统GM(1,1)模型进行比较.实例表明,基于线性多步法所建立的GM(1,1)模型,可以有效地提高模型的预测精度和适用性.     

超高效液相色谱法测定虾青素

建立超高效液相色谱法快速检测虾青素的方法。采用UPLC BEH C_8色谱柱(50 mm×2.1 mm,1.7μm),考察了流动相、流量及柱温对虾青素样品分离的影响,确定了最佳色谱条件:等度洗脱,流动相为甲醇–水(体积比为75∶25),流量为0.5 mL/min,柱温为40℃,检测波长为475 nm。虾青素的质量浓度在0.2~10.0μg/mL范围内与其色谱峰面积呈良好的线性关系,线性相关系数r=0.998 8,检出限(S/N=3)为0.1μg/mL,定量限(S/N=10)为0.2μg/mL。测定结果的相对标准偏差为0.41%(n=6),加标回收率为105.8%~110.3%。该方法快速、简单、可靠、灵敏、重复性好,可用于虾青素有关样品的快速检测。     

Raman spectroscopic identification of single bacterial cells at different stages of their lifecycle

Early, rapid, and reliable bacterial identification is of great importance in natural environments and in medical situations. Numerous studies have shown that Raman spectroscopy can be used to differentiate between different bacteria under controlled laboratory conditions. However, individual bacteria within a population exhibit macromolecular and metabolic heterogeneity over their lifetime. Therefore it is important to be able to identify and classify specific bacteria at different time points of the growth cycle. In this study, four species of bacteria were used to explore the capability of confocal Raman spectroscopy as a tool for the identification of (and discrimination between) diverse bacterial species at various growth time points. The results show that bacterial cells from different growth time points (as well as from a random growth phase) can be discriminated among the four species using principal component analysis (PCA). The results also show that bacteria selected from different growth phases can be classified with the help of a prediction model based on principal component and linear discriminant analysis (PC-LDA). These findings demonstrate that Raman spectroscopy with the application of a PC-LDA model rooted in chemotaxonomic analysis has potential for rapid sensing of microbial cells in environmental and clinical studies.     

Expansion of a SNaPshot assay to a 55‐SNP multiplex: Assay enhancements,validation, and power in forensic science

A previously developed multiplex assay with 44 individual identification SNPs was expanded to a 55plex assay. Fifty‐four highly informative SNPs and an amelogenin sex marker were amplified in one PCR reaction and then detected with two SNaPshot reactions using CE. PCR primers for four loci, 28 single‐base extension primers, and the reaction conditions were altered to improve the robustness of the method. A detailed approach for allele calling was developed to guide analysis of the electropherogram. One hundred and eighty unrelated individuals and 100 father‐child‐mother trios of the Han population in Hebei, China were analyzed. No mutation was found in the SNP loci. The combined mean match probability and cumulative probability of exclusion were 1.327 × 10^?22 and 0.999932, respectively. Analysis of the 54 SNPs and 26 STRs (included in the AmpFLSTR Identifiler and Investigator HDplex kits) showed no significant linkage disequilibriums. Our research shows that the expanded SNP multiplex assay is an easily performed and valuable method to supplement STR analysis.     

In vivo metabolism study of (R)‐bambuterol in humans using ultra high performance liquid chromatography with tandem mass spectrometry

(R)‐Bambuterol, a selective β2‐adrenoceptor agonist, has been approved as a new drug for the treatment of asthma and chronic obstructive pulmonary disease by the China Food and Drug Administration and is currently under phase I clinical trials. In this study, a combined method based on ultra high performance liquid chromatography with triple quadrupole mass spectrometry and ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry was employed for the identification of the major metabolites of (R)‐bambuterol in human plasma and urine after an oral dose of 10 mg. The metabolites were separated by gradient elution program and different sample preparation methods were compared. Totally, 12 metabolites of (R)‐bambuterol were identified, including four metabolites in plasma and all 12 metabolites in urine. Among these, four metabolites are reported for the first time. The possible metabolic pathways of (R)‐bambuterol were subsequently proposed. The results indicated that (R)‐bambuterol was metabolized via hydrolysis, demethylation, oxygenation, glucuronidation, and sulfation pathways in vivo. This study revealed that this combined method was accurate and sensitive to identify the possible metabolites and to better understand the metabolism of (R)‐bambuterol in vivo.     

Perceptron ensemble of graph-based positive-unlabeled learning for disease gene identification

Identification of disease genes, using computational methods, is an important issue in biomedical and bioinformatics research. According to observations that diseases with the same or similar phenotype have the same biological characteristics, researchers have tried to identify genes by using machine learning tools. In recent attempts, some semi-supervised learning methods, called positive-unlabeled learning, is used for disease gene identification. In this paper, we present a Perceptron ensemble of graph-based positive-unlabeled learning (PEGPUL) on three types of biological attributes: gene ontologies, protein domains and protein-protein interaction networks. In our method, a reliable set of positive and negative genes are extracted using co-training schema. Then, the similarity graph of genes is built using metric learning by concentrating on multi-rank-walk method to perform inference from labeled genes. At last, a Perceptron ensemble is learned from three weighted classifiers: multilevel support vector machine, k-nearest neighbor and decision tree. The main contributions of this paper are: (i) incorporating the statistical properties of gene data through choosing proper metrics, (ii) statistical evaluation of biological features, and (iii) noise robustness characteristic of PEGPUL via using multilevel schema. In order to assess PEGPUL, we have applied it on 12950 disease genes with 949 positive genes from six class of diseases and 12001 unlabeled genes. Compared with some popular disease gene identification methods, the experimental results show that PEGPUL has reasonable performance.     

The effect of initiators and oxidants on the morphology of poly [(±)‐2‐(sec‐butyl) aniline] a chiral bulky substituted polyaniline derivative

The nano and micro sphere synthesis of chiral bulky substituted polyaniline from monomer (±)‐2‐sec‐butylaniline in bulk and template‐free method (rapid mixing) was done successfully using ammonium peroxydisulfate (APS) and FeCl₃·6H₂O as oxidants. The effect of initiators such as p‐phenylendiamine and 1,4‐benzenediamine, temperature and concentration of monomer on morphology is demonstrated by scanning electron microscopy (SEM) images. The nano and micro sphere morphology was obtained using initiators. Smallest particles were achieved when 1,4‐benzenediamine was used as initiator in the presence of FeCl₃·6H₂O as oxidant. By increasing the concentration of monomer more uniform spheres were obtained. Characterization was made via FT‐IR, UV–Vis, ¹H and ¹³C‐NMR spectroscopy. Elemental analysis and electrical conductivity of products are also presented. All analysis data are in good agreement with nigraniline oxidation state of polyaniline. Copyright © 2015 John Wiley & Sons, Ltd.     

Identification of transformation products from β‐blocking agents formed in wetland microcosms using LC‐Q‐ToF

Identification of degradation products from trace organic compounds, which may retain the biological activity of the parent compound, is an important step in understanding the long‐term effects of these compounds on the environment. Constructed wetlands have been successfully utilized to remove contaminants from wastewater effluent, including pharmacologically active compounds. However, relatively little is known about the transformation products formed during wetland treatment. In this study, three different wetland microcosm treatments were used to determine the biotransformation products of the β‐adrenoreceptor antagonists atenolol, metoprolol and propranolol. LC/ESI‐Q‐ToF run in the MS^E and MS/MS modes was used to identify and characterize the degradation products through the accurate masses of precursor and product ions. The results were compared with those of a reference standard when available. Several compounds not previously described as biotransformation products produced in wetlands were identified, including propranolol‐O‐sulfate, 1‐naphthol and the human metabolite N‐deaminated metoprolol. Transformation pathways were significantly affected by microcosm conditions and differed between compounds, despite the compounds' structural similarities. Altogether, a diverse range of transformation products in wetland microcosms were identified and elucidated using high resolving MS. This work shows that transformation products are not always easily predicted, nor formed via the same pathways even for structurally similar compounds. Copyright © 2016 John Wiley & Sons, Ltd.     

Non‐target environmental analysis by liquid chromatography/high‐resolution mass spectrometry with a product ion and neutral loss database

Despite the increasing detection of emerging substances in the environment, the identity of most are left unknown due to the lack of efficient identification methods. We developed a non‐target analysis method for identifying unknown substances in the environment by liquid chromatography/high‐resolution mass spectrometry (LC/HRMS) with a product ion and neutral loss database (PNDB). The present analysis describes an elucidation method with elemental compositions of the molecules, product ions, and corresponding neutral losses of the unknown substance: (1) with the molecular formula, possible molecular structures are retrieved from two chemical structure databases (PubChem and ChemSpider); then (2) with the elemental compositions of product ions and neutral losses, possible partial structures are retrieved from the PNDB; and finally, (3) molecular structures that match the possible partial structures are listed in order of number of hits. A molecular structure with a higher number of hits is more similar to the structure of the analyzed substance. The performance of the non‐target method was evaluated by simulated analysis of 150 LC/HRMS spectra registered in MassBank. First, all substances of the same mass data (41/41) and 68% (39/57) of the mass data of the same substances not registered in the PNDB were elucidated. It was demonstrated that 14% (7/52) and 31% (16/52) of the substances with no mass spectral data registered in the PNDB were obtained at the first and within the fifth place, respectively. Owing to the fact that 10 of the total hits occurred in product ions and neutral losses, almost 50% of the substances evaluated with this method were placed at the top 4 positions in the similarity ranking. Importantly, the proposed method is effective for analyzing mass spectral data that has not been registered in the PNDB and thus is expected to be used for a variety of non‐target analyses.