Renal safety evaluation of aspirin plus edaravone in patients with ischaemic stroke: a retrospective cohort study.

Background And Objective: Aspirin combined with edaravone is more effective than aspirin or edaravone alone in the treatment of ischaemic stroke. Aspirin is defined as a nephrotoxic drug while the renal safety of edaravone is controversial. We aimed to evaluate whether edaravone will increase the nephrotoxicity of aspirin in patients with ischaemic stroke.

Safety and Efficacy of Low Molecular Weight Heparin for Thromboprophylaxis in the Elderly: A Network Meta-Analysis of Randomized Clinical Trials.

Given their changing pathophysiology, elderly patients carry a high risk of embolism and bleeding events; hence, use of appropriate anticoagulants is very important. Low molecular weight heparin (LMWH) is one of the most widely used anticoagulants although LMWHs differ in their anti-Xa, antithrombin, and anticoagulant activities. To date, no study has directly compared the safety and efficacy of different LMWHs in the elderly.

Validation of pre-operative risk scores of contrast-induced acute kidney injury in a Chinese cohort.

Background: Pre-operative risk scores are more valuable than post-procedure risk scores because of lacking effective treatment for contrast-induced acute kidney injury (CI-AKI). A number of pre-operative risk scores have been developed, but due to lack of effective external validation, most of them are also difficult to apply accurately in clinical practice. It is necessary to review and validate the published pre-operative risk scores for CI-AKI.

A new strategy to improve the predictive ability of the local lazy regression and its application to the QSAR study of melanin-concentrating hormone receptor 1 antagonists.

In the quantitative structure-activity relationship (QSAR) study, local lazy regression (LLR) can predict the activity of a query molecule by using the information of its local neighborhood without need to produce QSAR models a priori. When a prediction is required for a query compound, a set of local models including different number of nearest neighbors are identified. The leave-one-out cross-validation (LOO-CV) procedure is usually used to assess the prediction ability of each model, and the model giving the lowest LOO-CV error or highest LOO-CV correlation coefficient is chosen as the best model.

3D-QSAR studies on the inhibitors of AP-1 and NF-kappaB mediated transcriptional activation.

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 68 inhibitors of AP-1 and NF-kappaB mediated transcriptional activations. The CoMFA model produced statistically significant results with the cross-validated q(2) of 0.594 and the conventional correlation coefficient r(2) of 0.

Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56(Lck) inhibitors.

In this study, the quantitative structure-activity relationship (QSAR) of a series of 2-aminothiazole based Lck inhibitors was investigated. The key structural features responsible for the inhibition activities were discussed in detail. A population of 100 rigorously validated linear QSAR models were established based on the descriptors calculated in DRAGON program and selected by genetic algorithm (GA).

QSPR prediction of GC retention indices for nitrogen-containing polycyclic aromatic compounds from heuristically computed molecular descriptors.

Gas chromatographic retention indices of nitrogen-containing polycyclic aromatic compounds (N-PACs) have been predicted by quantitative structure-property relationship (QSPR) analysis based on heuristic method (HM) implemented in CODESSA. In order to indicate the influence of different molecular descriptors on retention indices and well understand the important structural factors affecting the experimental values, three multivariable linear models derived from three groups of different molecular descriptors were built. Moreover, each molecular descriptor in these models was discussed to well understand the relationship between molecular structures and their retention indices.

The prediction for gas chromatographic retention index of disulfides on stationary phases of different polarity.

Quantitative structure-retention relationship (QSRR) models for the gas chromatographic (GC) Kaváts indices of disulfides on four different polarity stationary phase have been developed. Semi-empirical quantum chemical method (AM1) implemented in hyperchem 4.0 was employed to calculate a set of molecular descriptors of 50 disulfides.

The prediction for gas chromatographic retention indices of saturated esters on stationary phases of different polarity.

A quantitative structure-retention relationship (QSRR) model has been developed for the gas chromatographic Kováts indices of 98 saturated esters on seven different polar stationary phases by multiple linear regression analysis (MLR). The seven stationary phases are: SE-30, OV-7, DC-710, OV-25, 100% phenyl, DC-230 and DC-530. Chemical descriptors were calculated from the molecular structures by PM3 of Hyperchem 4.

Prediction of gas chromatographic retention indices by the use of radial basis function neural networks.

A new method for the prediction of retention indices for a diverse set of compounds from their physicochemical parameters has been proposed. The two used input parameters for representing molecular properties are boiling point and molar volume. Models relating relationships between physicochemical parameters and retention indices of compounds are constructed by means of radial basis function neural networks.

Highly sensitive analysis of substituted aniline compounds in water samples by using oxidized multiwalled carbon nanotubes as an in-tube solid-phase microextraction medium.

An automated on-line method for the determination of the substituted aniline compounds was developed using in-tube solid-phase microextraction coupling to high-performance liquid chromatography (HPLC). In this work, oxidized multiwalled carbon nanotubes (MWCNTs-COOH) coated on the outer surface of the fused-silica tube and inserted in the polyether ether ketone (PEEK) tubing, which was fixed directly on the six-port injection valve to substitute for the sample loop. The extraction procedure was performed by a constant flow pump frequently driving the sample solution through the PEEK tubing and the analytes were adsorbed onto MWCNTs-COOH materials when the six-port valve set to load position.

A chemometric strategy for optimization of solid-phase microextraction: determination of bisphenol A and 4-nonylphenol with HPLC.

A sensitive method for the analysis of bisphenol A and 4-nonylphenol is developed by means of the optimization of solid-phase microextraction using Uniform Experimental Design methodology followed by high-performance liquid chromatographic analysis with fluorescence detection. The optimal extraction conditions are determined based on the relationship between parameters and the peak area. The curve calibration plots are linear (r2>or=0.

Selective solid-phase extraction using molecular imprinted polymer for the analysis of diethylstilbestrol.

A simple imprinted amino-functionalized silica gel material was synthesized by combining a surface molecular imprinting technique with a sol-gel process for solid-phase extraction-high performance liquid chromatography (SPE-HPLC) determination of diethylstilbestrol (DES). Activated silica gel was used as the supporter and non-imprinted silica sorbent was synthesized without the addition of DES using the same procedure as that of DES-imprinted silica sorbent. Compared with non-imprinted polymer particles, the prepared DES-imprinted silica sorbent showed high adsorption capacity, significant selectivity, good site accessibility and fast binding kinetics for DES.

QSAR study of malonyl-CoA decarboxylase inhibitors using GA-MLR and a new strategy of consensus modeling.

Quantitative structure-activity relationship (QSAR) of a series of structural diverse malonyl-CoA decarboxylase (MCD) inhibitors have been investigated by using the predictive single model as well as the consensus analysis based on a new strategy proposed by us. Self-organizing map (SOM) neural network was employed to divide the whole data set into representative training set and test set. Then a multiple linear regressions (MLR) model population was built based on the theoretical molecular descriptors selected by Genetic Algorithm using the training set.

Elimination of matrix effects in the determination of bisphenol A in milk by solid-phase microextraction-high-performance liquid chromatography.

Solid-phase microextraction coupled to high-performance liquid chromatography (SPME-HPLC) with fluorescence detection was employed to determine bisphenol A (BPA) in milk samples. The potential influence of the milk matrix on the determination of BPA by SPME-HPLC were investigated. Optimal conditions to eliminate any matrix effects were as follows: milk samples were deproteinized with trichloroacetic acid, diluted 20-fold with BPA-free Ultrapure water, dissolved in methanol, the precipitated protein was filtered out, rinsed with methanol and evaporated to remove the methanol.

Wettability switching between high hydrophilicity at low pH and high hydrophobicity at high pH on surface based on pH-responsive polymer.

Surfaces obtained by modifying poly(N,N'-dimethylaminoethyl methacrylate) (PDMAEMA) on rough silicon substrates are highly hydrophilic at low pH and highly hydrophobic at high pH; such surfaces effectively supplement the research on the wettability of solid surfaces based on the pH-responsive polymers.

Prediction of retention times for a large set of pesticides or toxicants based on support vector machine and the heuristic method.

Quantitative structure-retention relationship (QSRR) studies were performed for predicting the retention times (RTs) of 110 kinds of pesticides or toxicants. Chemical descriptors were calculated from the molecular structure of the compounds alone. The QSRR models were built using the heuristic method (HM) and support vector machine (SVM), respectively.

Analysis of free amino acids in islets of Langerhans by high-performance liquid chromatography using pre-column derivatization with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole.

A simple high-performance liquid chromatographic method with pre-column derivatization and fluorescence detection was developed and used for the analysis of free amino acids in islets of Langerhans; 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl) served as pre-column derivatization reagent. Islets of Langerhans were separated from the pancreas of normal and obese rats, treated with pre-cooling methanol-water (80:20, v/v), and ultrasonicated to fragmentize the islets and effect deproteination. Several parameters influencing the derivatization reaction and chromatographic separation were optimized.

Microemulsion electrokinetic chromatography for the separation of arctiin and arctigenin in Fructus Arctii and its herbal preparations.

A microemulsion electrokinetic chromatography method was used to separate arctiin and arctigenin in Fructus Arctii and its herbal preparations. The separation of arctiin and arctigenin was performed using a 1-butanol-SDS-ethyl acetate-water microemulsion in 10mM sodium tetraborate buffer. The analytes were baseline-resolved within 4 min.

Classification study of skin sensitizers based on support vector machine and linear discriminant analysis.

The support vector machine (SVM), recently developed from machine learning community, was used to develop a nonlinear binary classification model of skin sensitization for a diverse set of 131 organic compounds. Six descriptors were selected by stepwise forward discriminant analysis (LDA) from a diverse set of molecular descriptors calculated from molecular structures alone. These six descriptors could reflect the mechanic relevance to skin sensitization and were used as inputs of the SVM model.

Oxidized multiwalled carbon nanotubes as a novel solid-phase microextraction fiber for determination of phenols in aqueous samples.

A simple and environmentally friendly method for determination of seven phenols using solid-phase microextraction (SPME) coupled to high-performance liquid chromatography (HPLC) has been developed. Several materials were used as stationary phase of SPME fibers and an oxidized multiwalled carbon nanotubes material was found to be effective in carrying out simultaneous extraction of phenols in aqueous samples. Compared with the widely used commercially available SPME fibers, this proposed fiber had much lower cost, longer lifetime (over 150 times), shorter analysis time (30 min of extraction and 3 min of desorption time) and comparable or superior extraction efficiency for the investigated analytes.

Determination of tetrandrine and fangchinoline in plasma samples using hollow fiber liquid-phase microextraction combined with high-performance liquid chromatography.

Tetrandrine (TET) and fangchinoline (FAN) are basic and highly hydrophobic drugs with logP>5.7. In this work, a simple, inexpensive and efficient liquid-phase microextraction (LPME) technology combined with high-performance liquid chromatography (HPLC) was developed for the simultaneous analysis of tetrandrine and fangchinoline in plasma samples.

[Quantitative relationship between gas chromatographic retention time and structural parameters of alkylphenols].

Alkylphenols are a group of permanent pollutants in the environment and could adversely disturb the human endocrine system. It is therefore important to effectively separate and measure the alkylphenols. To guide the chromatographic analysis of these compounds in practice, the development of quantitative relationship between the molecular structure and the retention time of alkylphenols becomes necessary.

QSPR prediction of n-octanol/water partition coefficient for polychlorinated biphenyls.

The logarithmic n-octanol/water partition coefficient (logK(ow)) is a very important property which concerns water-solubility, bioconcentration factor, toxicity and soil absorption coefficient of organic compounds. Quantitative structure-property relationship (QSPR) model for logK(ow) of 133 polychlorinated biphenyls (PCBs) is analyzed using heuristic method (HM) implemented in CODESSA. In order to indicate the influence of different molecular descriptors on logK(ow) values and well understand the important structural factors affecting the experimental values, three multivariable linear models derived from three groups of different molecular descriptors were built.

Small organic molecular imprinted materials: their preparation and application.

Molecular imprinting is a technique for preparing polymeric materials that are capable of recognizing and binding the desired molecular target with a high affinity and selectivity. The materials can be applied to a wide range of target molecules, even those for which no natural binder exists or whose antibodies are difficult to raise. The imprinting of small organic molecules (e.