Biomedical subjects

Ru-Qin Yu

Publications and source records attributed to Ru-Qin Yu.

61 records · Page 4Linked to original sources

PubMed2002

[Simultaneous determination of isomers of dihydroxybenzene using alternating trilinear decomposition algorithm combined with reversed-phase high performance liquid chromatography/diode array detection].

Alternating trilinear decomposition (ATLD) algorithm is a promising method for second-order calibration, which is based on an alternating least-squares principle to overcome some shortcomings of the traditional parallel factor analysis (PARAFAC) algorithms, such as the sensitivity to the estimated component numbers and slow convergence. It utilizes an iterative procedure involving Moore-Penrose generalized inverse computations based on singular value decomposition and can be applied to the simultaneous determination of several organic components even in the presence of unknown interfering components. The overlapped chromatogram and spectra system of dihydroxybenzenes were resolved by ATLD combined with reversed-phase high performance liquid chromatography (RP-HPLC)/ diode array detection (DAD). The elution time was set from 1.086 min to 1.399 min with an interval of 1/150 min and the ultraviolet wavelength from 268 nm to 298 nm with an interval of 1 nm. The resolved results were in agreement with the actual results excellently. Catechol (CAT), resorcinol (RES) and hydroquinone (HYD) in aqueous solution were determined simultaneously, whose recoveries were (100.1 +/- 1.0)%, (99.4 +/- 1.4)% and (100.5 +/- 1.7)%, respectively. The results showed this experiment can be easily performed without resorting to time-consuming and complicated procedures and quantified accurately. It successfully solved the resolving problem caused by chromatogram and spectra overlapping in the presence of interfering components. It also revealed the ATLD algorithm can be efficiently applied to solve the second-order calibration problem in HPLC-DAD.

English Abstract↗

PubMed2001

Covalently immobilized aminonaphthalimide as fluorescent carrier for the preparation of optical sensors.

By replacing the hydrogen of the 4-amino group of a 4-amino-1,8-naphthalimide derivative with an N-acryloxyethyl group, the fluorophore has been covalently immobilized on an optical sensor surface by UV photopolymerization. The optical sensor obtained can be used for the determination of picric acid. The linear range and detection limit of the sensor are 9.80x10(-7)-1.96x10(-4) mol L(-1) and 7.1x10(-7) mol L(-1), respectively. Leaching of the fluorophore from the membrane is effectively prevented by covalent immobilization, resulting in a sensor with a relatively long lifetime. The response time of the sensor is short, and the reproducibility and reversibility are good. The sensor has been used for the indirect determination of the chloroquine content of pharmaceutical tablets.

Journal Article↗

PubMedDate not supplied

Optimized partition of minimum spanning tree for piecewise modeling by particle swarm algorithm. QSAR studies of antagonism of angiotensin II antagonists.

In quantitative structure-activity relationship (QSAR) modeling, when compounds in a training set exhibit a significant structural distinction between each other, in particular when chemicals of biological interest interacting on the receptor involve a different mechanism, it might be difficult to construct a single linear model for the whole population of compounds of interest with desired residuals. Developing a piecewise linear local model can be effective to circumvent the aforementioned problem. In this paper, piecewise modeling by the particle swarm optimization (PMPSO) approach is applied to QSAR study. The minimum spanning tree is used for clustering all compounds in the training set to form a tree, and the modified discrete PSO is applied to divide the tree to find satisfactory piecewise linear models. A new objective function is formulated for searching the appropriate piecewise linear models. The proposed PMPSO algorithm was used to predict the antagonism of angiotensin II. The results demonstrated that PMPSO is useful for improvement of the performance of regression models.

Algorithms↗

PubMedDate not supplied

Modified ant colony optimization algorithm for variable selection in QSAR modeling: QSAR studies of cyclooxygenase inhibitors.

A new version of an ant colony optimization (ACO) algorithm has been proposed. A modified ACO algorithm is proposed to select variables in QSAR modeling and to predict inhibiting action of some diarylimidazole derivatives on cyclooxygenase (COX) enzyme. As a comparison to this method, the evolution algorithm (EA) was also tested. Experimental results have demonstrated that the modified ACO is a useful tool for variable selection that needs few parameters to be adjusted and converges quickly toward the optimal position.

Algorithms↗

PubMedDate not supplied

Piecewise hypersphere modeling by particle swarm optimization in QSAR studies of bioactivities of chemical compounds.

As the structural diversity in a quantitative structure-activity relationship (QSAR) model increases, constructing a good model becomes increasingly difficult, and simply performing variable selection might not be sufficient to improve the model quality to make it practically usable. To combat this difficulty, an approach based on piecewise hypersphere modeling by particle swarm optimization (PHMPSO) is developed in this paper. It treats the linear models describing the sought-for subsets as hyperspheres which have different radii in the data space. According to the attribute of each hypersphere, all compounds in the training set are allocated to hyperspheres to construct submodels, and particle swarm optimization (PSO) is applied to search the optimal hyperspheres for finding satisfactory piecewise linear models. A new objective function is formulated to determine the appropriate piecewise models. The performance is assessed using three QSAR data sets. Experimental results have shown the good performance of this technique in improving the QSAR modeling.

Angiotensin II↗

PubMedDate not supplied

Optimized block-wise variable combination by particle swarm optimization for partial least squares modeling in quantitative structure-activity relationship studies.

The use of numerous descriptors that are indicative of molecular structure is becoming common in quantitative structure-activity relationship (QSAR) studies. As all of the descriptors might carry more or less molecular information, it seems more advisable to investigate the possible variable combination rather than variable selection. In this paper, an optimized block-wise variable combination (OBVC) by particle swarm optimization based on partial least squares modeling has been proposed for variable combination. An F statistic is also introduced to determine the dimensionality of the PLS model. The performance is assessed using two QSAR data sets. Experimental results have shown the good performance of this technique compared to those obtained by stepwise regression.

Amines↗

PubMedDate not supplied

Adaptive configuring of radial basis function network by hybrid particle swarm algorithm for QSAR studies of organic compounds.

The configuring of a radial basis function network (RBFN) consists of selecting the network parameters (centers and widths in RBF units and weights between the hidden and output layers) and network architecture. The issues of suboptimum and overfitting, however, often occur in RBFN configuring. This paper presented a hybrid particle swarm optimization (HPSO) algorithm to simultaneously search the optimal network structure and parameters involved in the RBFN (HPSORBFN) with an ellipsoidal Gaussian function as a basis function. The continuous version of PSO was used for parameter training, while the modified discrete PSO was employed to determine the appropriate network topology. The proposed HPSORBFN algorithm was applied to modeling the inhibitory activities of substituted bis[(acridine-4-carboxamide)propyl]methylamines to murine P388 leukemia cells and the bioactivities of COX-2 inhibitors. The results were compared with those obtained from RBFNs with the parameters optimized by continuous PSO and by conventionally RBFN training the algorithm for a fixed network topology, indicating that the HPSO was competent for RBFN configuring in that it converged quickly toward the optimal solution and avoided overfitting.

Algorithms↗