AFM Studies of Monolayers of Hydrophobically-modified Poly(Propylene Imine) Dendrimers

A series of hydrophobically-modified dendrimers were prepared by using the second generation poly(propylene imine) dendrimer and fatty acid chlorides. The modified dendrimers were characterized by 1H and 13C NMR spectra. The dendrimers were also studied by Langmuir technique and AFM. Surface pressure-area isotherms and atomic force microscopy (AFM) measurements showed that the C12-fatty acid modified amphiphilic dendrimers formed stable monolayers of smooth and homogenous surface with roughness < 0.5 nm. High resolution AFM images showed a tetragonal motif with spacing of between 0.4 and 0.5 nm, indicating crystalline two dimensional packing of the alkyl chains on a mica surface. The C18-fatty acid modified dendrimers formed relatively stable films and showed island structures at surface pressure of 10 mN/m, and the monolayers were collapsed at surface pressure of 25 mN/m.Chemistry Departmen

The effect of Cu content on corrosion, wear and tribocorrosion resistance of Ti-Mo-Cu alloy for load-bearing bone implants

In this study, the effects of Cu content on wear, corrosion, and tribocorrosion resistance of Ti-10Mo-xCu alloy were investigated. Results revealed that hardness of Ti-10Mo-xCu alloy increased from 355.1 ± 15.2 HV to 390.8 ± 17.6 HV by increasing Cu content from 0 % to 5 %, much higher than CP Ti (106.6 ± 15.1 HV) and comparable to Ti64 (389.7 ± 13.9 HV). With a higher Cu content, wear and tribocorrosion resistance of Ti-10Mo-xCu alloys were enhanced, and corrosion resistance showed an initial increase with a subsequent decrease. Wear mechanisms under pure mechanical wear and tribocorrosion conditions of Ti-10Mo-xCu alloys were a combination of delamination, abrasion and adhesion wear

Design and performance evaluation of additively manufactured composite lattice structures of commercially pure Ti (CP-Ti)

Ti alloys with lattice structures are garnering more and more attention in the field of bone repair or regeneration due to their superior structural, mechanical, and biological properties. In this study, six types of composite lattice structures with different strut radius that consist of simple cubic (structure A), body-centered cubic (structure B), and edge-centered cubic (structure C) unit cells are designed. The designed structures are firstly simulated and analysed by the finite element (FE) method. Commercially pure Ti (CP–Ti) lattice structures with optimized unit cells and strut radius are then fabricated by selective laser melting (SLM), and the dimensions, microtopography, and mechanical properties are characterised. The results show that among the six types of composite lattice structures, combined BA, CA, and CB structures exhibit smaller maximum von-Mises stress, indicating that these structures have higher strength. Based on the fitting curves of stress/specific surface area versus strut radius, the optimized strut radius of BA, CA, and CB structures is 0.28, 0.23, and 0.30 mm respectively. Their corresponding compressive yield strength and compressive modulus are 42.28, 30.11, and 176.96 MPa, and 4.13, 2.16, and 7.84 GPa, respectively. The CP-Ti with CB unit structure presents a similar strength and compressive modulus to the cortical bone, which makes it a potential candidate for subchondral bone restorations

A targeted metabolomic protocol for short-chain fatty acids and branched-chain amino acids

Research in obesity and metabolic disorders that involve intestinal microbiota demands reliable methods for the precise measurement of the short-chain fatty acids (SCFAs) and branched-chain amino acids (BCAAs) concentration. Here, we report a rapid method of simultaneously determining SCFAs and BCAAs in biological samples using propyl chloroformate (PCF) derivatization followed by gas chromatography mass spectrometry (GC-MS) analysis. A one-step derivatization using 100 µL of PCF in a reaction system of water, propanol, and pyridine (v/v/v = 8:3:2) at pH 8 provided the optimal derivatization efficiency. The best extraction efficiency of the derivatized products was achieved by a two-step extraction with hexane. The method exhibited good derivatization efficiency and recovery for a wide range of concentrations with a low limit of detection for each compound. The relative standard deviations (RSDs) of all targeted compounds showed good intra- and inter-day (within 7 days) precision (< 10%), and good stability (< 20%) within 4 days at room temperature (23–25 °C), or 7 days when stored at −20 °C. We applied our method to measure SCFA and BCAA levels in fecal samples from rats administrated with different diet. Both univariate and multivariate statistics analysis of the concentrations of these target metabolites could differentiate three groups with ethanol intervention and different oils in diet. This method was also successfully employed to determine SCFA and BCAA in the feces, plasma and urine from normal humans, providing important baseline information of the concentrations of these metabolites. This novel metabolic profile study has great potential for translational research

Aggregation of a hydrophobically modified poly(propylene imine) dendrimer

The poly(propylene imine) dendrimer DAB-dendr- (NH2)8 was hydrophobically modified with dodecanoyl end groups. The modified dendrimer was deposited onto mica by adsorption from solution and observed by atomic force microscopy. With the decrease of adsorption time, the modified dendrimer varied from continuous film to scattered islands. For the adsorption time of 20s the dendrimer formed a sub-monolayer thin film that contained many fractal aggregates of fractal dimension 1.80 that were > 1 μm in diameter and no more than 0.8nm thick. After 5 months at 1#1 , the initial fractal aggregates transformed into disks and other less-branched shapes with average heights of the domains of 0.6nm and 0.4nm, respectively. Formation of the fractal aggregates is explained by diffusion-limited aggregation. The slow reorganization of dendrimer molecules in the fractal aggregates occurs at a temperature well above the Tg of the dendrimer

EEG feature selection method based on maximum information coefficient and quantum particle swarm

Abstract To reduce the dimensionality of EEG features and improve classification accuracy, we propose an improved hybrid feature selection method for EEG feature selection. First, MIC is used to remove irrelevant features and redundant features to reduce the search space of the second stage. QPSO is then used to optimize the feature in the second stage to obtain the optimal feature subset. Considering that both dimensionality and classification accuracy affect the performance of feature subsets, we design a new fitness function. Moreover, we optimize the parameters of the classifier while optimizing the feature subset to improve the classification accuracy and reduce the running time of the algorithm. Finally, experiments were performed on EEG and UCI datasets and compared with five existing feature selection methods. The results show that the feature subsets obtained by the proposed method have low dimensionality, high classification accuracy, and low computational complexity, which validates the effectiveness of the proposed method