Hydroxyapatite/tricalcium silicate composites cement derived from novel two-step sol-gel process with good biocompatibility and applications as bone cement and potential coating materials

Tricalcium silicate (C₃S) and hydroxyapatite (HAp) composites were fabricated through the sol-gel process. The aim of this research is to improve the biocompatibility of C₃S through HAp addition and study the potential of using this as coating materials. The composites (HAp/C₃S) were characterised by Fourier transform infrared spectrometry, thermal gravity-differential thermal analysis and X-ray diffraction. The working and setting times of cement pastes were tested using Gillmore needle. Mechanical properties were examined by nanoindentation and material testing system. In vitro biocompatibility of the materials were studied by cell attachment and viability of L929 and MG-63 cells. HAp/C₃S as a coating material on gelatin film were measured with the surface roughness and imaged by scanning electron microscope. With the addition of HAp, no undesirable free CaO was detected with the synthesis by the sol-gel preparation. The pH values of HAp added groups were between 7.54 and 8.76, which were much lower than pure C₃S group (pH?=?11.75). For in vitro studies, the presence of HAp could effectively enhance the cell attachment and viability of both L929 and MG-63 cells grown in the extract or directly on the composites. However, the mechanical properties of the composites were impaired as compared to pure C₃S. Lastly, HAp/C₃S cement could be evenly coated on gelatin film. HAp is successfully demonstrated to improve C₃S biocompatibility with this new composites HAp/C₃S. C-75 (75% C₃S and 25% HAp), in particular, has good biocompatibility, relatively high compressive strength and can be uniformly coated onto gelatin film. Thus, C-75 is a promising material for further investigation as a coating on other biopolymers.     

Glucocorticoids and aging

In this review we analyze the morphologic changes, hypothalamic-pituitary-adrenal (HPA) axis functions, glucocorticoid (GC) receptors, and steroidogenic enzyme activities in both animals and humans during aging. In rodent studies, older animals tend to show: 1) hypertrophy of adrenal zona fasciculata (ZF) cells; 2) neuronal loss in the hypothalamic area; 3) loss of GC receptors in the hippocampus; 4) raised circulating adrenocorticotropic hormone (ACTH) and GC levels, and increased release of corticotropin-releasing hormone from the hypothalamus; 5) reduced suppression of endogenous GC secretion after administration of dexamethasone; 6) decreased attenuation of response to chronic stress; and 7) increased activity of P450scc and 21-hydroxylase. According to the GC cascade hypothesis, stress and GCs facilitate the aging process in rats. Stress induces downregulation of GC receptors in the hippocampus, then impairs GC feedback on stress-induced HPA axis activation. Finally, an increase in the basal level of corticosterone and extended GC secretion following stress occurs. Because activation of the hippocampus decreases HPA axis function, the unrestrained elevation of GC concentration and the reduction in the level of GC receptors in the hippocampus may gradually weaken the feedback mechanisms and halt the response to stress. In humans, there are conflicting reports of HPA axis function during aging, so it is difficult to make a final conclusion regarding the relationship between aging and HPA axis function.     

Molecular Imaging and Preclinical Studies of Radiolabeled Long-Term RGD Peptides in U-87 MG Tumor-Bearing Mice

The Arg–Gly–Asp (RGD) peptide shows a high affinity for α_vβ₃ integrin, which is overexpressed in new tumor blood vessels and many types of tumor cells. The radiolabeled RGD peptide has been studied for cancer imaging and radionuclide therapy. We have developed a long-term tumor-targeting peptide DOTA-EB-cRGDfK, which combines a DOTA chelator, a truncated Evans blue dye (EB), a modified linker, and cRGDfK peptide. The aim of this study was to evaluate the potential of indium-111(¹¹¹In) radiolabeled DOTA-EB-cRGDfK in α_vβ₃ integrin-expressing tumors. The human glioblastoma cell line U-87 MG was used to determine the in vitro binding affinity of the radiolabeled peptide. The in vivo distribution of radiolabeled peptides in U-87 MG xenografts was investigated by biodistribution, nanoSPECT/CT, pharmacokinetic and excretion studies. The in vitro competition assay showed that ¹¹¹In-DOTA-EB-cRGDfK had a significant binding affinity to U-87 MG cancer cells (IC₅₀ = 71.7 nM). NanoSPECT/CT imaging showed ¹¹¹In-DOTA-EB-cRGDfK has higher tumor uptake than control peptides (¹¹¹In-DOTA-cRGDfK and ¹¹¹In-DOTA-EB), and there is still a clear signal until 72 h after injection. The biodistribution results showed significant tumor accumulation (27.1 ± 2.7% ID/g) and the tumor to non-tumor ratio was 22.85 at 24 h after injection. In addition, the pharmacokinetics results indicated that the ¹¹¹In-DOTA-EB-cRGDfK peptide has a long-term half-life (T_1/2λz = 77.3 h) and that the calculated absorbed dose was safe for humans. We demonstrated that radiolabeled DOTA-EB-cRGDfK may be a promising agent for glioblastoma tumor imaging and has the potential as a theranostic radiopharmaceutical.     

Fall detection for multiple pedestrians using depth image processing technique

A fall detection method based on depth image analysis is proposed in this paper. As different from the conventional methods, if the pedestrians are partially overlapped or partially occluded, the proposed method is still able to detect fall events and has the following advantages: (1) single or multiple pedestrian detection; (2) recognition of human and non-human objects; (3) compensation for illumination, which is applicable in scenarios using indoor light sources of different colors; (4) using the central line of a human silhouette to obtain the pedestrian tilt angle; and (5) avoiding misrecognition of a squat or stoop as a fall. According to the experimental results, the precision of the proposed fall detection method is 94.31% and the recall is 85.57%. The proposed method is verified to be robust and specifically suitable for applying in family homes, corridors and other public places.     

An experimental study of the dynamics of the curing process of sheet molding compound (SMC) paste

The dynamic curing behavior of sheet molding compound (SMC) has been investigated by using a cylindrical cure reactor. Both thermal and mechanical responses were determined for R-25 SMC paste. The responses from this material were analyzed to determine the chemical and physical transformations that occur during the SMC molding process. The thermal response was obtained from a thermocouple placed along the centerline of the paste sample in the cure reactor. The thermal history at this location shows distinctive stages associated with heat transfer and crosslinking reactions during the cure cycle. The R-25 paste has a precure time of 160 seconds, a reaction time of 25 seconds, and a temperature rise of 134°C. The mechanical response describes the volume change and the pressure of the paste. The displacement curve shows volume changes due to thermal expansion, cure shrinkage, and thermal contraction during the course of a cure cycle. We found a less than 1% shrinkage during the reaction of the R-25 paste. The pressure response of the paste was found to parallel the volume transformation, although it also is strongly influenced by mechanical interactions between the press and the paste.     

Solving the team orienteering problem using effective multi-start simulated annealing

The team orienteering problem (TOP) is known as an NP-complete problem. A set of locations is provided and a score is collected from the visit to each location. The objective is to maximize the total score given a fixed time limit for each available tour. Given the computational complexity of this problem, a multi-start simulated annealing (MSA) algorithm which combines a simulated annealing (SA) based meta-heuristic with a multi-start hill climbing strategy is proposed to solve TOP. To verify the developed MSA algorithm, computational experiments are performed on well-known benchmark problems involving numbers of locations ranging between 42 and 102. The experimental results demonstrate that the multi-start hill climbing strategy can significantly improve the performance of the traditional single-start SA. Meanwhile, the proposed MSA algorithm is highly effective compared to the state-of-the-art meta-heuristics on the same benchmark instances. The proposed MSA algorithm obtained 135 best solutions to the 157 benchmark problems, including five new best solutions. In terms of both solution quality and computational expense, this study successfully constructs a high-performance method for solving this challenging problem.     

The impact of media on collaborative learning in virtual settings: The perspective of social construction

This study examines an alternative function of information sharing – social construction of meaning. Drawing on social construction, social interaction, and task closure theories, we explored the influence of both the media environment in which students are situated and the medium that group members choose to communicate with one another on the intricate relationships among breadth of information sharing, depth of information sharing, and performance of computer-supported collaborative learning (CSCL). A total of 126 students participated in the experiment – including 63 students (15 groups of four students and one group of three students) in the control and experimental groups respectively. Our findings show that most of the proposed hypotheses are supported. Intersubjective interpretation underlies groups information sharing and plays a key role in student learning performance. Evidence shows that when facing a relatively complex task in multimedia environments, students who choose to utilize a medium lower in social presence (i.e., electronic information sharing) are more likely to achieve task closure than a medium higher in social presence (i.e., verbal information sharing). This in turn leads to higher learning performance. The implications for both theory and pedagogy are also discussed.     

Throughput analysis of IEEE 802.11e EDCA under heterogeneous traffic

The amended version of IEEE 802.11e defines the enhanced distributed channel access (EDCA) for quality of service (QoS) connections. EDCA provides a priority scheme to classify different traffic categories by the arbitration inter-frame space (AIFS), and the initial and maximum contention window sizes. Most previous Markov chain analyses of EDCA have concentrated on the effect of contention window size, they neglected the effect of AIFS. In this paper, we consider of AIFS events among each back-off procedure and evaluate the saturation throughput of the IEEE 802.11e EDCA under heterogeneous traffic scenarios. The analytical model is based on the differentiated AIFS and uses the discrete time slot to analyses the external collision time. We take advantage of extensive simulation studies to validate the accuracy of the proposed model. Our models accurately estimate the effects of varied back-off window size and AIFS under heterogeneous traffic.     

Parameter determination of support vector machine and feature selection using simulated annealing approach

Support vector machine (SVM) is a novel pattern classification method that is valuable in many applications. Kernel parameter setting in the SVM training process, along with the feature selection, significantly affects classification accuracy. The objective of this study is to obtain the better parameter values while also finding a subset of features that does not degrade the SVM classification accuracy. This study develops a simulated annealing (SA) approach for parameter determination and feature selection in the SVM, termed SA-SVM.To measure the proposed SA-SVM approach, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate. The proposed approach was compared with grid search which is a conventional method of performing parameter setting, and various other methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of grid search and other approaches. The SA-SVM is thus useful for parameter determination and feature selection in the SVM.     

Makespan minimization for scheduling unrelated parallel machines with setup times

This study considers the problem of scheduling jobs on unrelated parallel machines with machine-dependent and job sequence-dependent setup times. In this study, a restricted simulated annealing (RSA) algorithm which incorporates a restricted search strategy is presented to minimize the makespan. The proposed RSA algorithm can effective reduce the search effort required to find the best neighborhood solution by eliminating ineffective job moves. The effectiveness and efficiency of the proposed RSA algorithm is compared with the basic simulated annealing and existing meta-heuristics on a benchmark problem dataset used in earlier studies. Computational results indicate that the proposed RSA algorithm compares well with the state-of-the-art meta-heuristic for small-sized problems, and significantly outperforms basic simulated annealing algorithm and existing algorithms for large-sized problems.