Biomedical subjects
Publications and source records attributed to Biye Ren.
A novel poly(ferrocenylsilane) with a coumarin side group was synthesized. This photoreversible polymer exhibits interesting electrochemical activities, which change with photodimerization and photoscission reactions of the coumarin moieties.
Combination of adsorption by porous CaCO(3) microparticles and encapsulation by polyelectrolyte multilayers via the layer-by-layer (LbL) self-assembly was proposed for sustained drug release. Firstly, porous calcium carbonate microparticles with an average diameter of 5 microm were prepared for loading a model drug, ibuprofen (IBU). Adsorption of IBU into the pores was characterized by ultraviolet (UV), infrared (IR), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) experiment and X-ray diffraction (XRD). The adsorbed IBU amount Gamma was 45.1mg/g for one-time adsorption and increased with increasing adsorption times. Finally, multilayer films of protamine sulfate (PRO) and sodium poly(styrene sulfonate) (PSS) were formed on the IBU-loaded CaCO(3) microparticles by the layer-by-layer self-assembly. Amorphous IBU loaded in the pores of the CaCO(3) microparticles had a rapider release in the gastric fluid and a slower release in the intestinal fluid, compared with the bare IBU crystals. Polyelectrolyte multilayers assembled on the drug-loaded particles by the LbL reduced the release rate in both fluids. In this work, polymer/inorganic hybrid core-shell microcapsules were fabricated for controlled release of poorly water-soluble drugs. The porous inorganic particles are useful to load drugs in amorphous state and the polyelectrolyte multilayer films coated on the particle assuage the initial burst release.
A series of solid complexes, PEI-PFAO, made of poly(ethylenimine) (PEI) and perfluorooctanoic acid (PFOA) with different compositions were prepared through a "starving addition" method, where PFOA was fed into PEI solution at the molar ratio, phi(feed), of acid group to the amino group of PEI, never beyond unity. Wide-angle X-ray diffraction diagrams confirmed amorphous structure of these complexes. Small-angle X-ray scattering indicated two ordered mesomorphous structures of alpha and beta lamellar phases, with respective long periods of 2.29 and 1.15 nm in the complexes. By increasing the actual molar ratio, phi, of PFOA to the amino group of PEI, the complex structure was altered from alpha-phase dominant to beta-phase dominant. All complexes exhibited two thermal degradation processes induced by decomposition of the bound PFOA below 230 degrees C and PEI backbone at about 350 degrees C. The initiating degradation temperature, Tid, decreases with increasing phi due to the preferential degradation of the PFOA chain bound to the tertiary amino groups. The glass transition temperature, Tg, of the complex increases with phi up to the degradation of the complex of phi = 1. This increase in Tg with phi also supports an ordered alignment of the bound PFOA chains, which greatly restricts the PEI mobility. The solid surface tension, gammaS, and critical surface tension, gammac, of the complex are between 15.4 and 16.8 mN/m and between 13.5 and 15.4 mN/m, respectively. The latter is very close to or even smaller than gammac of PTFE (15 mN/m), suggesting the enrichment of CF2 and CF3 groups at the complex surfaces. The fact that the PEI-POFA complex combines high hydrophobicity with selective thermal degradation of bound fluorinated chains promises a potential of selective change and local functionalization of the surface in a well-controlled manner.
Multiple linear regression (MLR) analysis based on a combined use of the modified Xu index and the atom-type based AI indices is performed to construct quantitative structure-property models on several data sets of organic compounds including aliphatic aldehydes and/or ketones. For each of the physical properties (the normal boiling points, molar refractions, gas heat capacities at 25 degrees C, water solubility at 25 degrees C, and n-octanol/water partition coefficient at 25 degrees C), high quality QSPR models are obtained, particularly the decrease in the standard error is within the range of 23.6-75.9% relative to the linear models with the modified Xu index alone. For individual subsets containing only aldehydes or ketones, in the majority of cases the quality of the model can be further improved. The significant improvement verifies the efficiency of the present approach and also indicates the usefulness of these indices for application to a wide range of physical properties. The results indicate that the physical properties studied are dominated by molecular size but atom types have smaller influences, especially the oxygen atom seems to be most important due to intermolecular polar interactions. The final models are validated to be statistically reliable using the leave-one-out cross-validation and/or an external test set.
The novel vertex degree v(m) for heteroatom in molecular graph is derived on the basis of the valence connectivity delta(v) of Kier-Hall. The newly proposed atom-type Al indices and previously proposed Xu index, are further modified for compounds with heteroatoms by replacing the vertex-degree of heteroatom by the proposed v(m). The multiple linear regression using the modified Xu index and Al indices can provide high-quality QSPR models for the normal boiling points (BP), molar volumes (MV), molar refractions (MR), and molecular total surface areas (TSA) of alcohols with up to 17 non-hydrogen atoms. The results imply that these physical properties may be expressed as a linear combination of the individual indices related to molecular size and atom-types. For each of the four properties, the correlation coefficient r is greater than 0.996 and particularly the decrease in the standard error is within the range of 61 83% compared with the simple linear models based on the modified Xu index, and the standard errors are 3.814, 0.939, 0.187, and 3.348 for BP, MV, MR, and TSA, respectively. The final models correspond to a fit error of 2.33, 0.70, 0.53, and 0.95% for BP, MV, MR, and TSA, respectively. The more general leave-n-out method is used to do the cross-validation. The cross-validation demonstrates the outstanding predictive power of the final models. The contributions of individual indices are used to illustrate the role of the molecular size and individual groups in molecules. The results indicate that physical properties of alcohols are dominated by the molecular size. On the other hand, although the hydrogen-bonding interactions caused by the -OH group play an important role in determining the normal BPs, the branching seems to be a more important factor influencing the MVs, MRs, and TSAs than the hydrogen-bonding interaction. The contribution of individual atom type or group to properties is not a constant and depends on its structural environment in a molecule.
Atom-type AI topological indices derived from the topological distance sums and vertex degree further are used to describe different structural environment of each atom-type in a molecule. The multiple linear regression based on combined use of the proposed Xu index and AI indices is performed to develop high quality QSPR models for describing six physical properties (the normal boiling points, heats of vaporization, molar volumes, molar refractions, van der Waals' constants, and Pitzer's acentric factors) of alkanes with up to nine carbon atoms. For each of six properties, the correlation coefficient r of the final models is larger than 0.995 and particularly the decrease in the standard error (s) is within the range of 45-86% as compared with the simple linear models with Xu index alone. The agreement between calculated and experimental data is quite good. The results indicate the potential of these indices for application to a wide range of physical properties. The role of each of the molecular size and individual groups in the molecules are illustrated by analyzing the relative or fraction contributions of individual indices. The results indicate that the six physical properties of alkanes are dominated by molecular size while AI indices have smaller influence dependent on the studied properties. Moreover, the studies demonstrate that each atomic group contributes an indefinite value to properties dependent on its structural environment in a molecule or other groups present. The cross-validation using the more general leave-n-out method demonstrates the final models to be highly statistically reliable.
Novel atomic level AI topological indexes based on the adjacency matrix and distance matrix of a graph is used to code the structural environment of each atomic type in a molecule. These AI indexes, along with Xu index, are successfully extended to compounds with heteroatoms in terms of novel vertex degree v(m), which is derived from the valence connectivity delta(v) of Kier-Hall to resolve the differentiation of heteroatoms in molecular graphs. The multiple linear regression (MLR) is used to develop the structure-property/activity models based on the modified Xu and AI indices. The efficiency of these indices is verified by high quality QSPR/QSAR models obtained for several representative physical properties and biological activities of several data sets of alcohols with a wide range of non-hydrogen atoms. The results indicate that the physical properties studied are dominated by molecular size, but other atomic types or groups have small influences dependent on the studied properties. Among all atomic types, -OH groups seem to be most important due to hydrogen-bonding interactions. On the contrary, -OH groups play a dominant role in biological activities studied, although molecular size is also an important factor. These results indicate that both Xu and AI indices are useful model parameters for QSPR/QSAR analysis of complex compounds.
Multiple linear regression (MLR) analysis is used to construct the structure-boiling point models for 71 sulfur-containing organic compounds in terms of the Xu index and atomic level AI indices. The potential of these descriptors is further verified by three high quality QSPR models obtained for two subsets of compounds and a combined set of all compounds. For these subsets, containing respectively 45 sulfides and 26 thiols, the best three-parameter models are obtained, and the best four-variable model is obtained for the whole data set of 71 compounds. The correlation coefficients r are larger than 0.997 in all three final models. The standard errors s are 3.14, 2.48, and 3.48 degrees C for the sulfide subset, the thiol subset, and the whole data set, respectively. Furthermore, the results indicate that the boiling points are dominated by the molecular size, but some atomic types in a molecule are important due to interactions between atomic groups of the molecules. Both the molecular size and atomic types related to different fundamental interactions provide the separate contributions to boiling points. Finally, the three final models are further validated to be statistically significant and reliable by the leave-one-out cross-validation method.
Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.