Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression.

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Recipe for uncovering the bioactive components in herbal medicine.

Using whole chromatographic profiles and measurements of total bioactivity as input, a quantitative pattern-activity relationship (QPAR) approach is proposed as a general method for providing two pieces of crucial information about complex bioactive mixtures available: (i) a model for predicting total bioactivity from the chromatographic fingerprint and (ii) the features in the chromatographic profile responsible for the bioactivity. While the first piece of information is already available through existing approaches, the second one results from our ability to remove dominant features in the chromatographic fingerprints which mask the components specifically related to pharmacological activity. Our targeted approach makes information about bioactivity available at the molecular level and provides possibilities for assessment of herbal medicine (HM) possible beyond just authentication and total bioactivity. As an example, the antioxidant property of the HM Radix Puerariae lobatae is measured through its reducing power toward a ferric ion complex. A partial least-squares (PLS) model is created to predict the antioxidant activity from the chromatographic fingerprint. Using the antioxidant activity as a target, the most discriminatory projection in the multivariate space spanned by the chromatographic profiles is revealed. From this target-projected component, the chromatographic regions most strongly connected to antioxidant activity are identified using the so-called selectivity ratio (SR) plot. The results are validated by prediction of samples not included in the modeling step.

Analytical comparison of different parts of Radix Angelicae Sinensis by gas chromatography coupled with mass spectrometry.

The three parts of Radix Angelicae Sinensis (Danggui) were reported to have different therapeutic effects. In order to investigate their chemical compositions of different parts of Danggui, gas chromatography-mass spectrometry (GC-MS) combined with chemometrics data analysis was applied to provide a more detailed study. Subwindow factor analysis (SFA) and a modified augmented evolving window orthogonal projection (AEWOP) method were used to resolve the batch GC-MS data sets from the Danggui samples. Then, t-test, Wilcoxon rank sum test, and principal component analysis (PCA) were applied to carry out the comparison job. The results indicate which components are found to have significant differences among the three parts. These findings may be helpful for further research of the pharmacological activities of Danggui.

Pretreatments of chromatographic fingerprints for quality control of herbal medicines.

Pretreatments of chromatographic fingerprints are important for quality control of herbal medicines and they include data correction and data transformation. The data correction can reduce the variations of experimental procedures, and data transformation can put different weights on the different parts of the fingerprints. In this paper, a new target peak alignment (TPA) procedure has been proposed to correct the retention time shifts, multiplicative scattering correction (MSC) has been introduced for response correction. Then the similarity of the fingerprints with mean and median fingerprints is used to evaluate the quality of herbal medicines (HMs). Furthermore, different data transformation methods with kernel principal component analysis (PCA) have been applied to the data and their effects were discussed. The proposed approaches have been demonstrated by the essential oils data set of a herbal medicine, named Houttuynia cordata (HC), containing samples from different geographic origins. The experimental results indicate that the proposed approaches may be helpful in the quality control of herbal medicines by fingerprints.

Sequential uniform designs for fingerprints development of Ginkgo biloba extracts by capillary electrophoresis.

A sequential procedure for the method of development of fingerprints based on a uniform design approach has been described in this paper. The sequential uniform design is used to reach the global optimum for a separation. The procedure is illustrated through developing the fingerprint of a Ginkgo biloba extract by capillary electrophoresis (CE) with diode array detection (DAD). The local overlap index (LOVI) is proposed as a criterion to evaluate the separation quality of two-dimensional hyphenated data in the optimization process. The successful application of the described techniques, including a sequential procedure, the CE-DAD hyphenated method and the LOVI criterion, shows their practicality in the fingerprint development of herbal medicines. However, some critical remarks on their use can also be made.

Identification of essential components of Houttuynia cordata by gas chromatography/mass spectrometry and the integrated chemometric approach.

Starting with Biller-Biemann's work [J.E. Biller, K. Biemann, Anal. Lett. 7 (1974) 515], various kinds of approaches have been proposed to extract GC/MS data to obtain pure components responses. In this paper, an integrated chemometric approach is proposed, which combine four sequential steps, data pretreatment, component perception, resolution and component identification, and then the proposed approach is manipulated to analyze the essential oils of a herbal medicine named Houttuynia cordata (HC). On the basis of the selective information obtained from both chromatograms and mass spectra, the proposed integrated chemometric approach can resolve the two-way GC/MS responses matrix into pure chromatograms and mass spectra without any model assumption on the peak shape. The resolution results obtained from HC samples demonstrate the performance of the proposed approach and indicate that it may be a promising one for analyzing complex chromatograms.

Comparing chemical fingerprints of herbal medicines using modified window target-testing factor analysis.

A "chromatographic fingerprint" of a herbal medicine is essentially its chromatographic spectrum: a characteristic representation of its chemical components, some of which are pharmacologically active. Since a wide variety of factors, such as the geographical location, the harvest season, and the part used can influence the chemical constituents (and therefore the pharmacological activity) of any particular herbal medicine and its products, these fingerprints provide a way to compare and contrast the compositions of different variants of the same herbal medicine. In particular, it is possible to ascertain whether particular components present in one herbal fingerprint are also present in another fingerprint. In this work we use a novel method-modified window target-testing factor analysis (MWTTFA), based on the use of target factor analysis (TFA), fixed-size moving window evolving factor analysis (FSMWEFA) and a Gaussian shape correction to the chromatographic profiles-to achieve this end. To demostrate the strategy, the fingerprints of samples from garlics produced in different geographical locations were compared, as well as the fingerprints of samples taken from above-ground and below-ground parts of Houttuynia cordata Thunb. The results from these comparisons clearly show that four chemical components present in Hunan common edible garlic are absent in Xingping base garlic, while seven components are present in Xingping base garlic but absent in Hunan common edible garlic. Also, eleven components are present in the sample from the above-ground part of Houttuynia cordata Thunb but not in the sample from the below-ground part, while seven components are present in the sample from the below-ground part of Houttuynia cordata Thunb that are not present in the sample from the above-ground part. These interesting conclusions should be very useful for future pharmacological and clinical research into these herbal medicines, and the novel MWTTFA technique can also be used for quality control purposes.

Comparison of the volatile constituents of Artemisia capillaris from different locations by gas chromatography-mass spectrometry and projection method.

The volatile chemical constituents of Artemisia capillaries (an important traditional Chinese medicine) were determined by gas chromatography-mass spectrometry (GC-MS) and sub-window factor analysis (SFA). Seventy-five components were separated and 43 of them were qualitatively and quantitatively determined, which represented about 89.03% of the total content. This profile was then used to identify and assess the consistency of the herb by using an orthogonal projection method. Four different sources of A. capillaries were analyzed and compared with each other. Among the components determined, there were 51 components coexisting in all samples although the relative peak areas of a few showed variations. It is the first time to apply orthogonal projection method to the comparison of different samples, and it reduces the burden of qualitative analysis as well as the subjectivity. The results showed a fair consistency in their GC-MS fingerprint. A. capillaris was distinguished from Artemisia sacrorum L., a possible substitute in traditional Chinese medicine by comparing the fingerprints with each other.

Spectral correlative chromatography and its application to analysis of chromatographic fingerprints of herbal medicines.

A signal-processing method known as spectral correlative chromatography (SCC) for two-dimensional data obtained from hyphenated chromatography is developed and applied to chemical chromatographic fingerprint data sets of herbal medicine under specific experimental conditions. The method can judge the presence or absence of a spectral correlative peak among the spectrochromatograms. A local least squares regression model (LLS) is constructed in a piecewise manner to correct the shifts of retention time of some peaks of interest in the chromatograms of various test samples. The results compare favorably with those obtained by a two-point calibrated algorithm. It is shown that performing SCC and LLS on the piecewise clusters of various chromatographic fingerprints is more helpful in practice in revealing their common nature and for characterizing the chemical constituents. This approach holds great potential for facilitating quality control of herbal medicines.

Analyzing of the volatile chemical constituents in Artemisia capillaris herba by GC-MS and correlative chemometric resolution methods.

The volatile chemical constituents in traditional Chinese medicine (TCM), Artemisia capillaris herba, were determined by gas chromatography-mass spectrometry (GC-MS). The acquired two-dimensional data were resolved by correlative chemometric resolution methods. The noise in the raw data is pretreated by roughness penalty smoothing method. With the data denoised, heteroscedastic noise and signal-to-noise ratio were decreased apparently, which was favorable to the determination of component number. The selective range can be extracted from rankmap obtained by fixed size moving window evolving factor analysis (FSMWEFA) conveniently. The overlapped chromatographic peaks were resolved into pure chromatograms and pure spectra with evolving window orthogonal projection (EWOP). The purity of the resolved pure spectra were improved furthermore with the heteroscedastic noise decreased through roughness penalty smoothing method, although the basic structure of the raw data changes little. Qualitative analysis was performed by similarity search in NIST147 and Willey library. Pure chromatograms are in favor of quantitative analysis, which was obtained by total volume integration. Forty-two of seventy-five separated constituents in essential oil, accounting for 89.03% of the total content, were identified. The result proves the combined approaches to be powerful for the analysis of complex herbal samples.

Determination of the volatile chemical constituents of Notoptergium incium by gas chromatography-mass spectrometry and iterative or non-iterative chemometrics resolution methods.

The qualitative and quantitative determination of the chemical constitutes in traditional Chinese medicine (TCM) is an important task, which builds the foundation of the theory of pharmacological activity. The hyphenated chromatography instruments combined with the related chemometric methods provide powerful tools for the resolution of such complex systems. The familiar chemometrics methods can be roughly divided into two different kinds, the iterative one such as orthogonal projection approach (OPA) and non-iterative one representing by evolving window orthogonal projection (EWOP). One can use different kinds of methods according to overlapping condition, and then the measured data matrix can be resolved into pure concentration profiles and mass spectra of the chemical components with relative high efficiency and acceptable accuracy. One kind of TCM, named Notoptergium incium (NI) was analyzed by gas chromatography-mass spectrometry (GC-MS) and resolved by above chemometric approach. Experiment results show the efficiency and convenience of the proposed approach. 65 of the 98 separated constituents in essential oil, accounting for 92.13%, were identified by mass spectroscopy (MS).