Discrimination of herbal medicines by molecular spectroscopy and chemical pattern recognition

The molecular spectroscopy (including near infrared diffuse reflection spectroscopy, Raman spectroscopy and infrared spectroscopy) with OPUS/Ident software was applied to clustering ginsengs according to species and processing methods. The results demonstrate that molecular spectroscopic analysis could provide a rapid, nondestructive and reliable method for identification of Chinese traditional medicine. It's found that the result of Raman spectroscopic analysis was the best one among these three methods. Comparing with traditional methods, which are laborious and time consuming, the molecular spectroscopic analysis is more effective.

Chinese herb medicines analyses by capillary electrophoresis with amperometric detection

Capillary electrophoresis (CE) with amperometric detection (AD) has been widely used in various fields of analytical science, especially in the pharmaceutical industry recently due to its high separation efficiency and low detection limit. The determination of active ingredients in Chinese herb medicines by CE-AD is of great importance in developing the researches on pharmacology of herbs, quantitative analysis and quality control. Analyses of the effective components in Chinese herb medicines and compound Chinese herb medicine by CE-AD are reviewed in this paper. In contrast with other analysis methods, the advantage of CE-AD is discussed. The development in analyses of traditional Chinese medicine (TCM) by CE-AD in future is mentioned.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

Mass spectrometric identification of multihydroxy phenolic compounds in Tibetan herbal medicines

A highly selective and accurate method based on derivatization with dansyl chloride coupled with liquid chromatography-mass spectrometry has been developed for identification of natural pharmacologically active phenolic compounds in extracts of Lomatogonium rotatum plants (Tibetan herbal medicine) obtained by solid-phase extraction. The number of hydroxyl groups on the dansylated phenols was estimated by LC-MS-MS analysis in positive-ion mode. Dansyl derivatization of the compounds introduced basic secondary nitrogen into the phenolic core structures and this was readily ionized when acidic HPLC mobile phases were used. MS fragmentation of the derivatives generated intense protonated molecular ions of m/z [MH](+) (phenol aglycones were transformed into the corresponding free phenols by cleavage of an aglycone bond). Collision-induced dissociation of the protonated molecule generated characteristic product ions of m/z 234 and 171 corresponding to the protonated 5-(dimethylamino)naphthalene sulfoxide and 5 -(dimethylamino) naphthalene moieties, respectively. Selected reaction monitoring based on the m/z [MH](+) to 234 and 171 transitions was highly specific for these phenolic compounds. Characteristic ions with m/z values of [MH - 234](+), [MH 2 x 234](+), and [MH - 3 x 234](+) were of great importance for estimation of the presence of multihydroxyl groups on the phenolic backbone.

Determination of 30 free fatty acids in two famous Tibetan medicines by HPLC with fluorescence detection and mass spectrometric identification

A simple and sensitive high-performance liquid chromatographic (HPLC) method with fluorescence detection and mass spectrometric identification has been developed for analysis of 30 long-chain and short-chain free Fatty acids (FFAs). The fatty acids were derivatized to their esters with 1-[2-(p-toluenesulfonate)ethyl]-2-phenylimidazole-[4,5-f]-9,10-phenanthrene (TSPP) in N,N-dimethylformamide (DMF) at 90 degrees C with anhydrous K2CO3 as catalyst. A mixture Of C-1-C-30 fatty acids was completely separated within 60 min by gradient elution on a reversed-phase C-8 column. Qualitative identification of the acids was performed by atmospheric-pressure chemical ionization mass spectrometry (APCI-MS) in positive-ion mode. The fluorescence excitation and emission wavelengths were 260 and 380 nm, respectively. Quantitative determination of the 30 acids in two Tibetan medicines Gentiana straminea and G. dahurica was performed. The results indicated that the medicines contained many FFAs. Linear correlation coefficients for the FFA derivatives were > 0.9991. Relative standard deviations (RSDs, n = 6) for the fatty acid derivatives were < 3%. Detection limits (at a signal-to-noise ratio of 3:1) were 3.1-38 fmol. When the fatty acid derivatives were determined in the two real samples results were satisfactory and the sensitivity and reproducibility of the method were good.

Affine Matching with Bounded Sensor Error: A Study of Geometric Hashing and Alignment

Affine transformations are often used in recognition systems, to approximate the effects of perspective projection. The underlying mathematics is for exact feature data, with no positional uncertainty. In practice, heuristics are added to handle uncertainty. We provide a precise analysis of affine point matching, obtaining an expression for the range of affine-invariant values consistent with bounded uncertainty. This analysis reveals that the range of affine-invariant values depends on the actual $x$-$y$-positions of the features, i.e. with uncertainty, affine representations are not invariant with respect to the Cartesian coordinate system. We analyze the effect of this on geometric hashing and alignment recognition methods.

The Alignment of Objects With Smooth Surfaces: Error Analysis of the Curvature Method

The recognition of objects with smooth bounding surfaces from their contour images is considerably more complicated than that of objects with sharp edges, since in the former case the set of object points that generates the silhouette contours changes from one view to another. The "curvature method", developed by Basri and Ullman [1988], provides a method to approximate the appearance of such objects from different viewpoints. In this paper we analyze the curvature method. We apply the method to ellipsoidal objects and compute analytically the error obtained for different rotations of the objects. The error depends on the exact shape of the ellipsoid (namely, the relative lengths of its axes), and it increases a sthe ellipsoid becomes "deep" (elongated in the Z-direction). We show that the errors are usually small, and that, in general, a small number of models is required to predict the appearance of an ellipsoid from all possible views. Finally, we show experimentally that the curvature method applies as well to objects with hyperbolic surface patches.

On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions

In this paper, we bound the generalization error of a class of Radial Basis Function networks, for certain well defined function learning tasks, in terms of the number of parameters and number of examples. We show that the total generalization error is partly due to the insufficient representational capacity of the network (because of its finite size) and partly due to insufficient information about the target function (because of finite number of samples). We make several observations about generalization error which are valid irrespective of the approximation scheme. Our result also sheds light on ways to choose an appropriate network architecture for a particular problem.

Error Detection and Recovery for Robot Motion Planning with Uncertainty

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions.

Screening and analysis of bioactive compounds with biofingerprinting chromatogram analysis of traditional Chinese medicines targeting DNA by microdialysis/HPLC

Biofingerprinting chromatogram, analysis, which is defined as the comparison of fingerprinting chromatograms of the extract of traditional Chinese medicines (TCMs) before and after the interaction with biological systems (DNA, protein. cell. etc.), was proposed for screening and analysis of the multiple bioactive compounds in TCMs. A method of microdialysis sampling combined with high performance liquid chromatography (HPLC) was applied to the study of DNA-binding property for the extracts of TCMs. Seven compounds were found to bind to calf thymus DNA (ct-DNA) from the TCMs of Coptis chinensis Franch (Coptis), but only three ones from Phellodendron amurense Rupr. (Phellodendron) and none from Sophoraflavescens Ait. (Sophora) to bind to ct-DNA. respectively. Three of them were identified as berberine, palmatine and jatrorrhizine and their association constants (K) to ct-DNA were determined by microdialysis/HPLC. Competitive binding behaviors of them to ct-DNA were also investigated. © 2005 Elsevier B.V. All rights reserved.

Improved performance of comprehensive two-dimensional HPLC separation of traditional Chinese medicines by using a silica monolithic column and normalization of peak heights

Performance of comprehensive two-dimensional liquid chromatography system is greatly improved than we reported previously by using a silica monolithic column as for the second dimensional separation. Due to the increase of the elution speed on the second dimensional monolithic column, the first dimensional column efficiency and analysis rate can be greatly improved as comparing with conventionally second dimensional column. The developed system was applied to analysis of methanol extraction of two umbelliferae herbs Ligusticum chuanxiong Hort. and Angelica sinensis (Oliv.) Diels by using CN column as for the first dimensional separation and a silica monolithic ODS column for the second dimensional separation, and the obtained three-dimensional chromatograms were treated by normalization of peak heights with the value of the highest peak or setting a certain value using a software written in-house. It was observed that much more peaks for low-abundant components in TCM extract can clearly be detected here than we reported before, due to the large difference for the amount of components in TCMs' extract. With the above improvements in separation performance and data treatment, totally about 120 components in methanol extraction of Rhizoma chuanxiong and 100 in A. sinensis were separated with UV detection within 130 min. This result meant that both the number of peaks detected increase twice but the analysis time decease twice if comparing with the previously reported result. (c) 2005 Published by Elsevier B.V.

Separation of compounds interacting with liposome membrane in combined prescription of traditional Chinese medicines with immobilized liposome chromatography

Immobilized liposome chromatography (ILC), the stationary phase of which has been regarded as a mimic biomembranes system was used to separate and analyze compounds interacting with liposome membrane in Danggui Buxue decoction, a combined prescription of traditional Chinese medicines (CPTCMs), and its compositions Radix Astragli and Radix Angelica Sinensis. More than 10 main peaks in the extract of Danggui Buxue decoction were resolved on the ILC column, suggesting that more than 10 components in the prescription have significant retention on ILC column. Ligustilide, astragaloside, TV and formononetin, three main bioactive ingredients in Danggui Buxue decoction, were found to have relatively significant, while ferulic acid, another bioactive ingredient in the prescription, relatively weak retention on ILC column. Effects of the eluent pH and amount of immobilized phosphatidylcholine (PC) on separation of interactional compounds in the extract of Danggui Buxue decoction were also investigated. It was found that these two factors strongly affected the retention of some interactional compounds. In addition, the fractions partitioned with different solvents from water extract of this combined prescription were evaluated with this ILC column system. (c) 2005 Elsevier B.V. All rights reserved.

The effect of the product cost factor on error handling in industrial robots

N.W. Hardy and M.H. Lee. The effect of the product cost factor on error handling in industrial robots. In Maria Gini, editor, Detecting and Resolving Errors in Manufacturing Systems. Papers from the 1994 AAAI Spring Symposium Series, pages 59-64, Menlo Park, CA, March 1994. The AAAI Press. Technical Report SS-94-04, ISBN 0-929280-60-1.