Improved configuration space sampling: Langevin dynamics with alternative mobility

We present a new and efficient method for determining optimal configurations of a large number (N) of interacting particles. We use a coarse-grained stochastic Langevin equation in the overdamped limit to describe the dynamics of this system and replace the standard mobility by an effective space dependent inverse Hessian correlation matrix. Due to the analogy of the drift term in the Langevin equation and the update scheme in Newton's method, we expect accelerated dynamics or improved convergence in the convex part of the potential energy surface Phi. The stochastic noise term, however, is not only essential for proper thermodynamic sampling but also allows the system to access transition states in the concave parts of Phi. We employ a Broyden-Fletcher-Goldfarb-Shannon method for updating the local mobility matrix. Quantitative analysis for one and two dimensional systems shows that the new method is indeed more efficient than standard methods with constant effective friction. Due to the construction, our effective mobility adapts high values/low friction in configurations which are less optimal and low values/high friction in configurations that are more optimal.     

Model selection of a switching mechanism for financial time series

The threshold autoregressive model with generalized autoregressive conditionally heteroskedastic (GARCH) specification is a popular nonlinear model that captures the well‐known asymmetric phenomena in financial market data. The switching mechanisms of hysteretic autoregressive GARCH models are different from threshold autoregressive model with GARCH as regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. This paper conducts a Bayesian model comparison among competing models by designing an adaptive Markov chain Monte Carlo sampling scheme. We illustrate the performance of three kinds of criteria by comparing models with fat‐tailed and/or skewed errors: deviance information criteria, Bayesian predictive information, and an asymptotic version of Bayesian predictive information. A simulation study highlights the properties of the three Bayesian criteria and the accuracy as well as their favorable performance as model selection tools. We demonstrate the proposed method in an empirical study of 12 international stock markets, providing evidence to strongly support for both models with skew fat‐tailed innovations. Copyright © 2016 John Wiley & Sons, Ltd.     

Gold nanoparticles bridging infra-red spectroscopy and laser desorption/ionization mass spectrometry for direct analysis of over-the-counter drug and botanical medicines

With a coating of gold nanoparticles (AuNPs), over-the-counter (OTC) drugs and Chinese herbal medicine granules in KBr pellets could be analyzed by Fourier Transform Infra-red (FT-IR) spectroscopy and Surface-assisted Laser Desorption/Ionization mass spectrometry (SALDI-MS). FT-IR spectroscopy allows fast detection of major active ingredient (e.g., acetaminophen) in OTC drugs in KBr pellets. Upon coating a thin layer of AuNPs on the KBr pellet, minor active ingredients (e.g., noscapine and loratadine) in OTC drugs, which were not revealed by FT-IR, could be detected unambiguously using AuNPs-assisted LDI-MS. Moreover, phytochemical markers of Coptidis Rhizoma (i.e. berberine, palmatine and coptisine) could be quantified in the concentrated Chinese medicine (CCM) granules by the SALDI-MS using standard addition method. The quantitative results matched with those determined by high-performance liquid chromatography with ultraviolet detection. Being strongly absorbing in UV yet transparent to IR, AuNPs successfully bridged FT-IR and SALDI-MS for direct analysis of active ingredients in the same solid sample. FT-IR allowed the fast analysis of major active ingredient in drugs, while SALDI-MS allowed the detection of minor active ingredient in the presence of excipient, and also quantitation of phytochemicals in herbal granules.     

A new anti-inflammatory β-carboline alkaloid from the hairy-root cultures of Eurycoma longifolia

One new β-carboline alkaloid 7-methoxy-(9H-β-carbolin-1-il)-(E)-1-propenoic acid (1) together with 9-methoxycanthin-6-one (2) and 9-hydroxycanthin-6-one (3) were isolated from the hairy-root cultures of Eurycoma longifolia. The effects of these compounds on lipopolysaccharide (LPS)-induced nitric oxide (NO) production in RAW264.7 cells were investigated. Compound 1 strongly inhibited the production of NO while 2 and 3 having weak or inactive effect. Consistently, compound 1 decreased the expression of cyclooxygenase-2 and inducible nitric oxide synthase.     

Analysis of berberine and total alkaloid content in cortex phellodendri by near infrared spectroscopy (NIRS) compared with high-performance liquid chromatography coupled with ultra-visible spectrometric detection

This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of Cortex Phellodendri (CP), Cortex Phellodendri Chinensis (PCS) and Cortex Phellodendri Amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all Cortex Phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R = 0.996 for the berberine and R = 0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.     

Detection of antinuclear antibodies by a colloidal gold modified optical fiber: comparison with ELISA

A fiberoptic evanescent-wave sensor has been developed for the measurement of antinuclear antibodies in sera from patients and healthy individuals. The sensor was constructed on the basis of modification of the unclad portion of an optical fiber with self-assembled gold colloids, where the colloidal gold surface was further functionalized with extractable nuclear antigens. Results show that detection of antinuclear antibodies by this sensor agrees quantitatively with the clinically accepted enzyme-linked immunosorbent assay (ELISA) method. This sensing platform has the following advantages: label-free and real-time detection capability, simple to construct and use, highly sensitive, and does not require a secondary antibody. The sensitivity of this platform is at least an order of magnitude higher than that of the ELISA method and thus may lead to a new direction in recognition of immune response. Biomolecular binding of antinuclear antibodies (ANA) with extractable nuclear antigens (ENA)-functionalized gold nanoparticles results in a change of surface plasmon absorption. When light propagates in an optical fiber by multiple total internal reflection, such a change in signal can be significantly enhanced.     

The effect of protein structural conformation on nanoparticle molecular imprinting of ribonuclease A using miniemulsion polymerization

One of the major difficulties faced in the molecular imprinting of proteins is the inherently fragile and flexible nature of the protein template which makes it incompatible with most polymerization systems. Miniemulsion polymerization is a possible approach for preparing molecularly imprinted nanoparticles, and in this study, the method of initiation, the high-shear homogenization, and the surfactant used for the polymerization reaction had been considered as possible factors that can denature the template protein, ribonuclease A (RNase A). The conformation of the protein in a miniemulsion was studied using circular dichroism (CD). It was found that redox initiation was more suitable for protein imprinting and that the addition of poly(vinyl alcohol) (PVA) as a co-surfactant had proved to be effective in preserving the template protein structural integrity. On the basis of the results of the study, polymeric nanoparticles imprinted with RNase A were prepared via miniemulsion polymerization using methyl methacrylate (MMA) and ethylene glycol dimethacrylate (EGDMA) as the functional and cross-linker monomers, respectively, with the conditions of the polymerization system optimized to best preserve the integrity of the protein template. In the subsequent investigation for the recognition properties of the prepared nanoparticles through batch and competitive rebinding tests, the imprinted nanoparticles prepared through the conventional (nonoptimized) miniemulsion polymerization lacked the target specificity as displayed by those prepared under the optimized conditions. This illustrated the importance of protein structural integrity in protein imprinting.     

HELP法在中草药分析中的应用研究-冬虫夏草的化学成分测定

基于直观推导式演进特征投影（ＨＥＬＰ）法,对冬虫夏草子座和虫体分别进行了多组分同时定性定量测定．结果表明,ＨＥＬＰ法能减少样本提取分离的步骤,降低色谱分离条件的要求,提高检测准确度．联用色谱检测与化学计量学解析法相结合将为复杂中草药分析提供一种全新手段