超临界流体萃取仪器的研制

本文报道了以国产原配件为基础，成功地研制了分析规模的超临界流体萃取仪器、并对仪器性能进行了全面考察，仪器性能稳定，重现性良好（ＲＳＤ＜３．１％），定量线性关系可靠，可满足定量萃取的要求。     

Fredholm theory for pseudoholomorphic curves with brake symmetry

We study the pseudoholomorphic curves with brake symmetry in symplectization of a closed contact manifold. We introduce the pseudo-holomorphic curves with brake symmetry and the corresponding moduli space. Then we get the virtual dimension of the moduli space.     

Large deviation analysis of the single server queue

We establish the large deviation principle (LDP) for the virtual waiting time and queue length processes in the GI/GI/1 queue. The rate functions are found explicitly. As an application, we obtain the logarithmic asymptotics of the probabilities that the virtual waiting time and queue length exceed high levels at large times. Additional new results deal with the LDP for renewal processes and with the derivation of unconditional LDPs for conditional ones. Our approach applies in large deviations ideas and methods of weak convergence theory.This work was supported in part by AT&T Bell Labs.     

The matched queueing network PH/M/c→oPH/PH/1

We consider a matched queueing network PH/M/coPH/PH/1, where the output of the first subsystem PH/M/c is regarded as one of the inputs of the second subsystem and matched with another input of PH-renewal process, and they are served by a single server with PH-service-distribution. The stationary state probabilities, the distribution of the virtual waiting times in the two subsystems, and the distribution of the total virtual waiting time are derived.The work was supported by the Max-Planck-Gesellschaft, Germany, and the Chinese Academy ofSciences.     

便携式病害猪肉速测仪的研制与应用

基于健康与病害猪肉中过氧化物酶(POD)的活性不同的原理,研制出便携式的病害猪肉速测仪,用于病害猪肉的检验与鉴别,以评判猪肉的品质。仪器的工作系统由检测系统和软件系统两部分组成。该检测仪具有操作简便,检测快速,可进行现场检测等优点。在对市场猪肉的检测中,利用测定体系与POD的反应动力学曲线,可快速准确地完成病害猪肉的鉴别,健康猪肉和病害猪肉的符合率分别为100%和96%。     

一种新的库仑微水滴定仪的设计方法

在传统微库仑滴定仪原理的基础上，利用８７５１单片机和微机，采用对电解电流时间调制的方法以及测量精度为准则判断滴定终点，从而大大地提高了仪器的测量精度和重复性。     

In vitro and in silico study of Aloe vera leaf extract against human breast cancer

Abstract

Aloe vera leaf contains some bioactive compounds that have a strong binding affinity toward estrogen receptor as compared to standard drug tamoxifen. In this study, we have found that the IC₅₀ of Aloe vera leaf extract against breast cancer cell line (MCF-7) is 23?µg/mL which is much lower than the IC₅₀ (332?µg/mL) of Aloe vera leaf extract against non-cancerous cell line (NIH-3T3). We have also calculated the total concentration of phenolic acid (385.662?µg/mL), flavonoids (160.402?µg/mL) and alkaloids (276.754?µg/mL) in Aloe vera leaf extract. The free radical scavenging activity of Aloe vera leaf extract is 67% to 89% (at 50 to 300?µg/ml). Our virtual molecular docking study suggests that bioactive compounds like Aloe-emodin (?8.8?Kcal/mol), 7-hydroxy-2,5 dimethylchromone (?7.5?Kcal/mol), Beta-sitosterol (?7.3?Kcal/mol) etc. have a greater binding affinity toward estrogen alpha receptor as compared to standard drug Tamoxifen (?6.4?Kcal/mol).

     

Multidimensional separation of isomeric species of chlorinated hydrocarbons such as PCB,PCDD, and PCDF

A multidimensional GC-system containing two capillary columns of different polarities, operated within a double oven instrument, was used for the optimized separation of complex isomeric mixtures of various types of chlorinated aromatic compounds such as PCB, PCDD, or PCDF. Electron capture was applied parallel to flame ionization detection to obtain sensitive signals of the PCB or PCDD and the n-alkane standards required for identification by Kovats indices, respectively. Electron capture detection within a valvelessly operated MDGC system forced changes in the usual instrumental set-up, the live-switching coupling piece being located within the second oven of the double oven instrument. This oven is operated isothermally to ensure optimal and interference-free detection, for stable flow conditions within the coupling piece and for the determination of the isothermal retention indices (Kovats), which are much more suitable for identification by retention than the so-called “linear” indices.     

Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

ABSTRACT

Existing data on structures and biological activities are limited and distributed unevenly across distinct molecular targets and chemical compounds. The question arises if these data represent an unbiased sample of the general population of chemical-biological interactions. To answer this question, we analyzed ChEMBL data for 87,583 molecules tested against 919 protein targets using supervised and unsupervised approaches. Hierarchical clustering of the Murcko frameworks generated using Chemistry Development Toolkit showed that the available data form a big diffuse cloud without apparent structure. In contrast hereto, PASS-based classifiers allowed prediction whether the compound had been tested against the particular molecular target, despite whether it was active or not. Thus, one may conclude that the selection of chemical compounds for testing against specific targets is biased, probably due to the influence of prior knowledge. We assessed the possibility to improve (Q)SAR predictions using this fact: PASS prediction of the interaction with the particular target for compounds predicted as tested against the target has significantly higher accuracy than for those predicted as untested (average ROC AUC are about 0.87 and 0.75, respectively). Thus, considering the existing bias in the data of the training set may increase the performance of virtual screening.     

SARS-CoV protease inhibitors design using virtual screening method from natural products libraries

Two natural products databases, the marine natural products database (MNPD) and the traditional Chinese medicines database (TCMD), were used to find novel structures of potent SARS-CoV protease inhibitors through virtual screening. Before the procedure, the databases were filtered by Lipinski's ROF and Xu's extension rules. The results were analyzed by statistic methods to eliminate the bias in target-based database screening toward higher molecular weight compounds for enhancing the hit rate. Eighteen lead compounds were recommended by the screening procedure. They were useful for experimental scientists in prioritizing drug candidates and studying the interaction mechanism. The binding mechanism was also analyzed between the best screening compound and the SARS protein.