傅里叶变换近红外光谱法测定大麦中蛋白质、淀粉和赖氨酸含量

采用傅里叶变换近红外光谱法测定大麦中蛋白质、淀粉、赖氨酸的含量，并用光谱影响值法(leverage)对异常值进行判断和处理。蛋白质、淀粉和赖氨酸含量近红外光谱分析模型的测定系数R。分别为0．985、0．973和0．978；检验集的化学值与模型预测值的相关系数r分别为0．9853、0．9644和0．9172，分析模型的预测相对标准偏差RSD分别为4．0％、2．4％和5．4％，该结果可替代经典分析方法，满足农产品快速分析的需要。     

Lecithin/propanol-based microemulsions used as media for a cholesterol oxidase-catalyzed reaction

Reverse micelles, Winsor III and IV systems were examined as reaction media for the enzymatic conversion of cholesterol to cholestenone by cholesterol oxidase at 298.2 K. The micelles and the microemulsions, stabilized by soybean lecithin and ethanol or 1-propanol as cosolvent, were characterized with respect to phase behavior and distribution of 1-propanol between the phases of the Winsor III systems. The used oils were dodecane, tetradecane, and hexadecane. The Winsor IV systems and the surfactant-rich phase in the Winsor III systems exhibit bicontinuous structures. The reaction yield for the enzymatic conversion performed in a Winsor IV system was much higher than in a Winsor III system or in reverse micelles.     

Group contributions to the thermodynamic properties of non-ionic organic solutes in dilute aqueous solution

The thermodynamic properties G _h ^o,H _h ^o, and C _p,h ^oassociated with the transfer of non-ionic organic compounds from gas to dilute aqueous solution and the limiting partial molar properties C _p ^o ,2 and V₂ ² of these compounds in water are described through a simple scheme of group contributions. A distinction is made between groups made only of carbon and hydrogen, and functional groups i.e. groups containing at least one atom different from carbon and hydrogen. Each group is assigned a contribution, for each property, through a least squares procedure which utilizes only molecules containing at most one functional group. Finally, for compounds containing more than one functional group, correction parameters are evaluated as the differences between the experimental values and those calculated by means of the group contributions. The different behavior of hydrophilic compared with hydrophobic groups is discussed for the various properties. A rationale for the correction parameters, i.e. for the effects of the interactions among hydrophilic groups on the thermodynamic properties, is attempted.     

An <Emphasis Type="BoldItalic">in silico</Emphasis> approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

Summary P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure–activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 ± 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.     

Unraveling the mystery of efficacy in Chinese medicine formula: New approaches and technologies for research on pharmacodynamic substances

Traditional Chinese medicine (TCM) is the key to unlock treasures of Chinese civilization. TCM and its compound play a beneficial role in medical activities to cure diseases, especially in major public health events such as novel coronavirus epidemics across the globe. The chemical composition in Chinese medicine formula is complex and diverse, but their effective substances resemble “mystery boxes”. Revealing their active ingredients and their mechanisms of action has become focal point and difficulty of research for herbalists. Although the existing research methods are numerous and constantly updated iteratively, there is remain a lack of prospective reviews. Hence, this paper provides a comprehensive account of existing new approaches and technologies based on previous studies with an in vitro to in vivo perspective. In addition, the bottlenecks of studies on Chinese medicine formula effective substances are also revealed. Especially, we look ahead to new perspectives, technologies and applications for its future development. This work reviews based on new perspectives to open horizons for the future research. Consequently, herbal compounding pharmaceutical substances study should carry on the essence of TCM while pursuing innovations in the field.     

Computation of suboptimal randomized strategies for steering the random motion of a point under partial observation

Consider the random motion in the plane of a pointM, whose velocityv=(v ₁,v ₂) is perturbed by an ²-valued Gaussian white noise. Only noisy nonlinear observations taken on the point location (state) are available toM. The velocityv is of the formv(y)= _u (u ₁,u ₂) _y (du), wherey denotes the value of the observed signal,U is the range of the velocity, and, for eachy, _y is a probability measure on (U). Using the available observations, the pointM wishes to steer itself into a given target set by choosing a randomized strategy ={ _y :y ²}. Sufficient conditions on weak optimal randomized strategies are derived. An algorithm for computing weak suboptimal randomized strategies is suggested, and the strategies are computed for a variety of cases.This work was partially supported by a grant from Control Data.     

Thermodynamic evaluation of a partial charge model assumptionfor the dissolved silica system

The Partial Charge Model was developed to predict the hydroxylation, polymerization, and precipitation of ions. The purpose of this study is to evaluate the Partial Charge Model for describing the polymerization of silica in aqueous solutions. The Partial Charge Model predicts the stability of ions and complexes based on the assumption that the stable species will have the same electronegativity as the mean electronegativity of the solution. The silica system was chosen for model validation because of the rare availability of self-consistent thermodynamic data on many dissolved but polymerized silicate anions, including both linear and cyclical species. The electronegativity of each species was calculated using the Partial Charge Model and the results were plotted against the stability constants for the ions. The silicate anions segregated into groups on the plot based on the number of charges per silicon atom in the polymer. Plots of the log of the stability constant versus the change in electronegativity produced a linear relationship for the silica polymers containing one negative charge per silicon atom, which resulted in an r ² of 0.9978. Thus, the Partial Charge Model successfully describes the thermodynamics of silica polymerization in aqueous solution for species that are sufficiently alike, but was not accurate for all silica species.     

Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR

Comparative molecular similarity indices analysis (CoMSIA), a three-dimensional quantitative structure activity relationship (3D QSAR) paradigm, was used to examine the correlations between the calculated physicochemical properties and the in vitro activities (3'-processing and 3'-strand transfer inhibition) of a series of human immunodeficiency virus type 1 (HIV-1) integrase inhibitors. The training set consisted of 34 molecules from five structurally diverse classes: salicylpyrazolinones, dioxepinones, coumarins, quinones, and benzoic hydrazides. The data set was aligned using extrema of molecular electrostatic potentials (MEPs). The predictive ability of the resultant model was evaluated using a test set comprised of 7 molecules belonging to a different structural class of thiazepinediones. A CoMSIA model using an MEP-based alignment showed considerable internal as well external predictive ability (r2(cv) = 0.821, r2(pred) = 0.608 for 3'-processing; and r2(cv) = 0.759, r2(pred.) = 0.660 for 3'-strand transfer).     

Multivariate calibration techniques applied to the spectrophotometric analysis of one-to-four component systems

The UV spectrophotometric analysis of a multicomponent mixture containing paracetamol, caffeine, tripelenamine and salicylamide by using multivariate calibration methods, such as principal component regression (PCR) and partial least-squares regression (PLS), was described. The calibration set was based on 47 reference samples, consisting of quaternary, ternary, binary and single-component mixtures, with the aim to develop models able to predict the concentrations of unknown samples containing as many as one-to-four components. The calibration models were optimized by an appropriate selection of the number of factors as well as wavelength ranges to be used for building up the data matrix and excluding any information about the interfering excipients included in pharmaceutics. The PCR and PLS models were compared and their predictive performance was inferred by a successful application to the assays of synthetic mixtures and pharmaceutical formulations.