Biomedical subjects

Jian-Hui Jiang

Publications and source records attributed to Jian-Hui Jiang.

7 recordsLinked to original sources

PubMed2004

Chinese literature associated with diagnosis of Helicobacter pylori.

AIM: To synthetically analyze and probe into the diagnosis of H pylori infection, we followed the principles of evidence-based medicine. METHODS: A total of 22 papers of prevalence survey and case-control studies were selected for studying about diadynamic methods. Using meta-analysis, we analyzed the different diadynamic methods of H pylori in China. RESULTS: Through meta-analysis, among the five diadynamic methods, the accuracy of polymerase chain reaction (PCR) was the highest (98.47%) and PCR was the most sensitive method (Sp: 99.03%). CONCLUSION: Among the five diadynamic methods, the accuracy of PCR is the highest and PCR is the most sensitive method to diagnose the infection of H pylori.

Asian People↗

PubMed2003

Competitive interactions of adriamycin and ethidium bromide with DNA as studied by full rank parallel factor analysis of fluorescence three-way array data.

The competitive interactions of adriamycin (AMC) and a fluorescence probe of ethidium bromide (EB) with DNA have been studied by full rank parallel factor analysis (FRA-PARAFAC) of fluorescence excitation-emission three-way data array. The excitation and emission spectra as well as the equilibrium concentrations of co-existing species in different reaction mixtures can be directly obtained by the FRA-PARAFAC treatment. The concordance of the resolved excitation and emission spectra of AMC, EB and EB-DNA with the standard spectra of these species confirmed the reliability of the equilibrium concentrations of these components in the reaction mixtures studied. The results obtained are valuable for providing a deeper insight into the competitive interaction mechanism of AMC and EB with DNA. The conclusion was directly given out that the interaction of AMC with DNA is the intercalating model. The FRA-PARAFAC method as exemplified by the present study provides an useful approach for studying the interaction of clinical drugs with DNA in the presence of disturbance of drug assistants.

Algorithms↗

PubMed2003

Quantitative structure-activity relationships (QSAR): studies of inhibitors of tyrosine kinase.

A quantitative structure-activity relationship (QSAR) study of the 1-phenylbenzimidazoles as inhibitors of the platelet-derived growth factor receptor (PDGFR) was performed. Some new electronic parameters Q(o), Q(m) and Q(p) are suggested for characterizing the effect of substituents. Many other descriptors are also used which are selected by evolution algorithm (EA) using modified Cp as objective function proposed by the present authors. The descriptor Q(m) is shown to be an important variable to express effect of substituents. The variable selection shows that spatial descriptors are most important variables revealing important properties of the inhibitors. Electron-releasing substitutes at 5-position and the absence of bulky groups at 4,7-positions of the parent structure can enhance inhibitor activity. Principal component analysis is performed to classify this series of compounds.

Benzimidazoles↗

PubMed2003

An improved trilinear decomposition algorithm based on a Lagrange operator.

An improved trilinear decomposition algorithm based on a Lagrange operator (LO) is developed in this paper, which introduces a Lagrange operator and penalty terms in the loss function to improve the performance of the algorithm. Compared to the traditional parallel factor (PARAFAC) algorithm, the algorithm not only may converge much faster, but also overcome the sensibility to estimate the number of components. A set of simulated and measured excitation/emission fluorescence data were treated by both the proposed and traditional PARAFAC algorithm to compare their efficiencies. The analytical results obtained with real chemical system containing aspirin and its metabolic products show that the trilinear decomposition methodology is a promising tool to obtain spectral and composition information from mixtures without chemical separation.

Journal Article↗

PubMed2002

Variable selection by an evolution algorithm using modified Cp based on MLR and PLS modeling: QSAR studies of carcinogenicity of aromatic amines.

The variable selection in QSAR studies by MLR and PLS modeling has been performed using the evolution algorithm (EA). The Cp statistic has been modified and used as the objective function in the EA search for different combinations of molecular descriptors. For MLR modeling a few information-rich descriptors are selected for model formulation. In PLS modeling, the proposed procedure selects a relatively large number of information-containing descriptors, and a PLS model is formulated based on a few latent variables, which are linear combinations of the selected descriptors. The proposed procedures were used for the prediction of carcinogenicity of aromatic amines.

Algorithms↗

PubMed2002

Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data.

A new wavelength interval selection procedure, moving window partial least-squares regression (MWPLSR), is proposed for multicomponent spectral analysis. This procedure builds a series of PLS models in a window that moves over the whole spectral region and then locates useful spectral intervals in terms of the least complexity of PLS models reaching a desired error level. Based on a proposed theory demonstrating the necessity of wavelength selection, it is shown that MWPLSR provides a viable approach to eliminate the extra variability generated by non-composition-related factors such as the perturbations in experimental conditions and physical properties of samples. A salient advantage of MWPLSR is that the calibration model is very stable against the interference from non-composition-related factors. Moreover, the selection of spectral intervals in terms of the least model complexity enables the reduction of the size of a calibration sample set in calibration modeling. Two strategies are suggested for coupling the MWPLSR procedure with PLS for multicomponent spectral analysis: One is the inclusion of all selected intervals to develop a PLS calibration model, and the other is the combination of the PLS models built separately in each interval. The combination of multiple PLS models offers a novel potential tool for improving the performance of individual models. The proposed procedures are evaluated using two open-path Fourier transform infrared data sets and one near-infrared data set, each having different noise characteristics. The results reveal that the proposed procedures are very promising for vibrational spectroscopy-based multicomponent analyses and give much better prediction than the full-spectrum PLS modeling.

Journal Article↗

PubMed2002

A new redundant variable pruning approach--minor latent variable perturbation-PLS used for QSAR studies on anti-HIV drugs.

A new approach for eliminating the redundant variables in the multivariable data matrix encountered in QSAR studies, minor latent variable perturbation (MLVP)-PLS method has been proposed. In the latent variable (LV) space, the minor latent variables (LVs) with small covariances are mainly formulated by linear combinations of the redundant variables including information-deficient and highly correlative ones, while the major LVs with large covariances are mainly contributed by the informative variables. Deleting a minor LV, which is equivalent to a perturbation for LV space, could make the redundant variables not well be represented in LV subspace, leading to strong variation of their PLS regression coefficients. The informative variables could still be normally represented in LV subspace with the PLS regression coefficients remaining relatively stable. MLVP-PLS utilizes this fact to discriminate the informative and redundant variables. It gradually identifies and eliminates the redundant variables according to the relative variation of PLS regression coefficients after perturbations are given. The elimination process is terminated according to some proposed criteria. Applying the method to the quantitative structure-activity relationship (QSAR) studies on TIBO derivatives as potential anti-HIV drugs has demonstrated the feasibility and robustness of the proposed approach. A deeper insight into the effect of different structural parameters on the bio-activity of TIBO derivatives has been reached.

Anti-HIV Agents↗