Investigation of electrophoretic loading and enhanced mechanical properties of hydrogels for delivery of therapeutic proteins

Hydrogels, which are three-dimensional crosslinked hydrophilic polymers, have been used and studied widely as vehicles for drug delivery due to their good biocompatibility. Traditional methods to load therapeutic proteins into hydrogels have some disadvantages. Biological activity of drugs or proteins can be compromised during polymerization process or the process of loading protein can be really timeconsuming. Therefore, different loading methods have been investigated. Based on the theory of electrophoresis, an electrochemical gradient can be used to transport proteins into hydrogels. Therefore, an electrophoretic method was used to load protein in this study. Chemically and radiation crosslinked polyacrylamide was used to set up the model to load protein electrophoretically into hydrogels. Different methods to prepare the polymers have been studied and have shown the effect of the crosslinker (bisacrylamide) concentration on the protein loading and release behaviour. The mechanism of protein release from the hydrogels was anomalous diffusion (i.e. the process was non-Fickian). The UV-Vis spectra of proteins before and after reduction show that the bioactivities of proteins after release from hydrogel were maintained. Due to the concern of cytotoxicity of residual monomer in polyacrylamide, poly(2-hydroxyethyl- methacrylate) (pHEMA) was used as the second tested material. In order to control the pore size, a polyethylene glycol (PEG) porogen was introduced to the pHEMA. The hydrogel disintegrated after immersion in water indicating that the swelling forces exceeded the strength of the material. In order to understand the cause of the disintegration, several different conditions of crosslinker concentration and preparation method were studied. However, the disintegration of the hydrogel still occurred after immersion in water principally due to osmotic forces. A hydrogel suitable for drug delivery needs to be biocompatible and also robust. Therefore, an approach to improving the mechanical properties of the porogen-containing pHEMA hydrogel by introduction of an inter-penetrating network (IPN) into the hydrogel system has been researched. A double network was formed by the introduction of further HEMA solution into the system by both electrophoresis and slow diffusion. Raman spectroscopy was used to observe the diffusion of HEMA into the hydrogel prior to further crosslinking by ã-irradiation. The protein loading and release behaviour from the hydrogel showing enhanced mechanical property was also studied. Biocompatibility is a very important factor for the biomedical application of hydrogels. Different hydrogels have been studied on both a three-dimensional HSE model and a HSE wound model for their biocompatibilities. They did not show any detrimental effect to the keratinocyte cells. From the results reported above, these hydrogels show good biocompatibility in both models. Due to the advantage of the hydrogels such as the ability to absorb and deliver protein or drugs, they have potential to be used as topical materials for wound healing or other biomedical applications.

Essais sur les logiciels libres : licences doubles, effets de réseau, et concurrence

This thesis examines the microeconomic consequences of the arrival of open source in the software market. Specifically, it analyzes three features of open source software by using specific models of industrial organization. Open source software is free, and may be modified or duplicated by anyone. The first paper studies the entry of an open source software in a closed source software market. Using a model of horizontal differentiation, the analysis considers a closed source firm's investment in the quality of its software. The introduction of open source on the market reduces the firm's investment in quality and increases the price of its software. Moreover, the entry of open source software may reduce consumer welfare. Post-entry by an open source software, the reduction in market share lowers the firm's incentive to invest in quality. The second paper features vertical differentiation to study a monopolist selling supporting product to its software. The study begins by contrasting the supply of support by an open source provider and a closed source vendor. The model shows that in both cases the levels of support offered are the same. In addition, consumer welfare is higher and profit lower under an open source software. Then, the paper considers the competition in the provision of support. Here, the supply of high level support is greater than under a monopolist. Finally, the monopolist adopts a dual licensing strategy to extract more surplus from developers interested in modifying open source software and redistributing the resulting product. This technique, when the developers place high value on the source code, generates more profit if the monopolist chooses to publish as open source rather than closed source. The last paper studies how a closed source firm is affected by the introduction of an open source benefiting from contributions by users. A vertical differentiation model is used, and reveals that, when contribution of users is present, the closed source vendor may lower its price to a level where it forces the open source out of the market. The firm's lower price not only increases demand for its software, but also induces consumers into switching from open to closed source software therefore reducing the contribution of users.

Electrically conductive, tough hydrogels with pH sensitivity

Electrically conductive, mechanically tough hydrogels based on a double network (DN) comprised of poly(ethylene glycol) methyl ether methacrylate (PPEGMA) and poly(acrylic acid) (PAA) were produced. Poly(3,4-ethylenedioxythiophene) (PEDOT) was chemically polymerized within the tough DN gel to provide electronic conductivity. The effects of pH on the tensile and compressive mechanical properties of the fully swollen hydrogels, along with their electrical conductivity and swelling ratio were determined. Compressive and tensile strengths as high as 11.6 and 0.6 MPa, respectively, were obtained for hydrogels containing PEDOT with a maximum conductivity of 4.3 S cm–1. This conductivity is the highest yet reported for hydrogel materials of high swelling ratios. These hydrogels may be useful as soft strain sensors because their electrical resistance changed significantly when cyclically loaded in compression.

Progress Toward Robust Polymer Hydrogels

In this review we highlight new developments in tough hydrogel materials in terms of their enhanced mechanical performance and their corresponding toughening mechanisms. These mechanically robust hydrogels have been developed over the past 10 years with many now showing mechanical properties comparable with those of natural tissues. By first reviewing the brittleness of conventional synthetic hydrogels, we introduce each new class of tough hydrogel: homogeneous gels, slip-link gels, double-network gels, nanocomposite gels and gels formed using poly-functional crosslinkers. In each case we provide a description of the fracture process that may be occurring. With the exception of double network gels where the enhanced toughness is quite well understood, these descriptions remain to be confirmed. We also introduce material property charts for conventional and tough synthetic hydrogels to illustrate the wide range of mechanical and swelling properties exhibited by these materials and to highlight links between these properties and the network topology. Finally, we provide some suggestions for further work particularly with regard to some unanswered questions and possible avenues for further enhancement of gel toughness.

Room-temperature photoluminescence in amorphous SrTiO3-The influence of acceptor-type dopants

Room-temperature photoluminescence (PL) was observed in undoped and 2 mol% Cr-, Al- and Y-doped amorphous SrTiO3 thin films. Doping increased the PL, and in the case of Cr significantly reduced the associated PL wavelength. The optical bandgaps, calculated by means of UV-vis absorption spectra, increased with crystallinity and decreased with the doping level. It was considered that yttrium and aluminum substituted Sr2+, whereas chromium replaced Ti4+. It is believed that luminescence centers are oxygen-deficient BO6 complexes, or the same centers with some other defects, such as oxygen or strontium vacancies, or BO6 complexes with some other defects placed in their neighborhood. The character of excitation and the competition for negatively charged non-bridging oxygen (NBO) among numerous types of BO6 defect complexes in doped SrTiO3 results in various broadband luminescence peak positions. The results herein reported are an indicative that amorphous titanates are sensitive to doping, which is important for the control of the electro-optic properties of these materials. The probable incorporation of Cr into the Ti site suggests that the existence of a double network former can lead to materials displaying a more intense photoluminescence.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Improving matching process in social network

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

Recent advances in cancer therapy targeting proteins involved in DNA double-strand break repair

Damage to genetic material represents a persistent and ubiquitous threat to genomic stability. Once DNA damage is detected, a multifaceted signaling network is activated that halts the cell cycle, initiates repair, and in some instances induces apoptotic cell death. In this article, we will review DNA damage surveillance networks, which maintain the stability of our genome, and discuss the efforts underway to identify chemotherapeutic compounds targeting the core components of DNA double-strand breaks (DSB) response pathway. The majority of tumor cells have defects in maintaining genomic stability owing to the loss of an appropriate response to DNA damage. New anticancer agents are exploiting this vulnerability of cancer cells to enhance therapeutic indexes, with limited normal tissue toxicity. Recently inhibitors of the checkpoint kinases Chk1 and Chk2 have been shown to sensitize tumor cells to DNA damaging agents. In addition, the treatment of BRCA1- or BRCA2-deficient tumor cells with poly(ADP-ribose) polymerase (PARP) inhibitors also leads to specific tumor killing. Due to the numerous roles of p53 in genomic stability and its defects in many human cancers, therapeutic agents that restore p53 activity in tumors are the subject of multiple clinical trials. In this article we highlight the proteins mentioned above and catalog several additional players in the DNA damage response pathway, including ATM, DNA-PK, and the MRN complex, which might be amenable to pharmacological interventions and lead to new approaches to sensitize cancer cells to radio- and chemotherapy. The challenge is how to identify those patients most receptive to these treatments.

The future of power in the network era

This article asks questions about the futures of power in the network era. Two critical emerging issues are at work with uncertain outcomes. The first is the emergence of the collaborative economy, while the second is the emergence of surveillance capabilities from both civic, state and commercial sources. While both of these emerging issues are expected by many to play an important role in the future development of our societies, it is still unclear whose values and whose purposes will be furthered. This article argues that the futures of these emerging issues depend on contests for power. As such, four scenarios are developed for the futures of power in the network era using the double variable scenario approach.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Integrated decoupling and matching network incorporated in the ground plane of a compact monopole array

Compact arrays enable various applications such as antenna beam-forming and multi-input, multi-output (MIMO) schemes on limited-size platforms. The reduced element spacing in compact arrays introduces high levels of mutual coupling which can affect the performance of the adaptive array. This coupling causes a mismatch at the input ports, which disturbs the performance of the individual elements in the array and affects the implementation of beam steering. In this article, a reactive decoupling network for a 3-element monopole array is used to establish port isolation while simultaneously matching input impedance at each port to the system impendence. The integrated decoupling and matching network is incorporated in the ground plane of the monopole array, providing further development scope for beamforming using phase shifters and power splitters in double-layered circuits.

L-dopa modulates functional connectivity in striatal cognitive and motor networks: A double-blind placebo-controlled study

Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 healthy young adults.Weexamined the FC of 6 striatal regions of interest (ROIs) previously shown to elicit networks known to be associated with motivational, cognitive and motor subdivisions of the caudate and putamen (Di Martino et al., 2008). In addition to replicating the previously demonstrated patterns of striatal FC, we observed robust effects of L-dopa. Specifically, L-dopa increased FC in motor pathways connecting the putamen ROIs with the cerebellum and brainstem. Although L-dopa also increased FC between the inferior ventral striatum and ventrolateral prefrontal cortex, it disrupted ventral striatal and dorsal caudate FC with the default mode network. These alterations in FC are consistent with studies that have demonstrated dopaminergic modulation of cognitive and motor striatal networks in healthy participants. Recent studies have demonstrated altered resting state FC in several conditions believed to be characterized by abnormal dopaminergic neurotransmission. Our findings suggest that the application of similar experimental pharmacological manipulations in such populations may further our understanding of the role of dopaminergic neurotransmission in those conditions.

Optimizing a piezometric network in the estimation of the groundwater budget: a case study from a crystalline-rock watershed in southern India

An estimate of the groundwater budget at the catchment scale is extremely important for the sustainable management of available water resources. Water resources are generally subjected to over-exploitation for agricultural and domestic purposes in agrarian economies like India. The double water-table fluctuation method is a reliable method for calculating the water budget in semi-arid crystalline rock areas. Extensive measurements of water levels from a dense network before and after the monsoon rainfall were made in a 53 km(2)atershed in southern India and various components of the water balance were then calculated. Later, water level data underwent geostatistical analyses to determine the priority and/or redundancy of each measurement point using a cross-validation method. An optimal network evolved from these analyses. The network was then used in re-calculation of the water-balance components. It was established that such an optimized network provides far fewer measurement points without considerably changing the conclusions regarding groundwater budget. This exercise is helpful in reducing the time and expenditure involved in exhaustive piezometric surveys and also in determining the water budget for large watersheds (watersheds greater than 50 km(2)).

Allosteric Communication in Cysteinyl tRNA Synthetase A NETWORK OF DIRECT AND INDIRECT READOUT

Protein structure networks are constructed for the identification of long-range signaling pathways in cysteinyl tRNA synthetase (CysRS). Molecular dynamics simulation trajectory of CysRS-ligand complexes were used to determine conformational ensembles in order to gain insight into the allosteric signaling paths. Communication paths between the anticodon binding region and the aminoacylation region have been identified. Extensive interaction between the helix bundle domain and the anticodon binding domain, resulting in structural rigidity in the presence of tRNA, has been detected. Based on the predicted model, six residues along the communication paths have been examined by mutations (single and double) and shown to mediate a coordinated coupling between anticodon recognition and activation of amino acid at the active site. This study on CysRS clearly shows that specific key residues, which are involved in communication between distal sites in allosteric proteins but may be elusive in direct structure analysis, can be identified from dynamics of protein structure networks.