Development and <Emphasis Type="Italic">In Vitro</Emphasis> Characterization of Galactosylated Low Molecular Weight Chitosan Nanoparticles Bearing Doxorubicin

The aim of the present research was to evaluate the potential of galactosylated low molecular weight chitosan (Gal-LMWC) nanoparticles bearing positively charged anticancer, doxorubicin (DOX) for hepatocyte targeting. The chitosan from crab shell was depolymerized, and the lactobionic acid was coupled with LMWC using carbodiimide chemistry. The depolymerized and galactosylated polymers were characterized. Two types of Gal-LMWC(s) with variable degree of substitution were employed to prepare the nanoparticles using ionotropic gelation with pentasodium tripolyphosphate anions. Factors affecting nanoparticles formation were discussed. The nanoparticles were characterized by transmission electron microscopy and photon correlation spectroscopy and found to be spherical in the size range 106–320 nm. Relatively higher percent DOX entrapment was obtained for Gal-LMWC(s) nanoparticles than for LMWC nanoparticles. A further increase in drug entrapment was found with nanoparticles prepared by Gal-LMWC with higher degree of substitution. A hypothesis which correlates the ionic concentration of DOX in nanoparticles preparation medium and percent DOX entrapment in cationic polymer has been proposed to explain the enhanced DOX entrapment. In-vitro drug release study demonstrated an initial burst release followed by a sustained release. The targeting potential of the prepared nanoparticles was assessed by in vitro cytotoxicity study using the human hepatocellular carcinoma cell line (HepG₂) expressing the ASGP receptors on their surfaces. The enthusiastic results showed the feasibility of Gal-LMWC(s) to entrap the cationic DOX and targeting potential of developed Gal-LMWC(s) nanoparticles to HepG₂ cell line.     

Use of supervised discretization with PCA in wavelet packet transformation-based surface electromyogram classification

This paper describes a preprocessing stage for nonlinear classifier used in wavelet packet transformation (WPT)-based multichannel surface electromyogram (EMG) classification. The preprocessing stage named sdPCA, which consists of supervised discretization coupled with principal component analysis (PCA), was developed for improving surface EMG classifier generalization ability and training speed on overlap segmented signals. The sdPCA outperforms the fast correlation-based filter (FCBF), PCA, supervised discretization, and their combinations in terms of the highest generalization ability, fast training speed, the small feature size, and an ability to reduce the risks of developing oscillation and being trapped in nonlinear classifier training. The experiments were conducted on a data set consisting of 4-channel surface EMG signals measured from 6 hand and wrist gestures of 12 subjects. The experimental results indicate that the classification system using sdPCA has the highest generalization ability along with the second fastest training speed. The classification accuracy in 12 subjects of the system using sdPCA is 93.30 ± 2.42% taking 400 epochs for training by overlap segmented signals within 100 s. This result is very attractive for further development because we can achieve high-classification accuracy for large data sets by means of the proposed sdPCA without the application of additional algorithms such as local discriminant bases (LDB), majority voting (MV), or WPT sub-bands clustering.     

Adenoviral expression of 15-lipoxygenase-1 in rabbit aortic endothelium: role in arachidonic acid-induced relaxation

Endothelium-dependent vasorelaxation of the rabbit aorta is mediated by either nitric oxide (NO) or arachidonic acid (AA) metabolites from cyclooxygenase (COX) and 15-lipoxygenase (15-LO) pathways. 15-LO-1 metabolites of AA, 11,12,15-trihydroxyeicosatrienoic acid (THETA), and 15-hydroxy-11,12-epoxyeicosatrienoic acid (HEETA) cause concentration-dependent relaxation. We tested the hypothesis that in the 15-LO pathway of AA metabolism, 15-LO-1 is sufficient and is the rate-limiting step in inducing relaxations in rabbit aorta. Aorta and rabbit aortic endothelial cells were treated with adenoviruses containing human 15-LO-1 cDNA (Ad-15-LO-1) or beta-galactosidase (Ad-beta-Gal). Ad-15-LO-1-transduction increased the expression of a 75-kDa protein corresponding to 15-LO-1, detected by immunoblotting with an anti-human15-LO-1 antibody, and increased the production of HEETA and THETA from [(14)C]AA. Immunohistochemical studies on Ad-15-LO-1-transduced rabbit aorta showed the presence of 15-LO-1 in endothelial cells. Ad-15-LO-1-treated aortic rings showed enhanced relaxation to AA (max 31.7 +/- 3.2%) compared with Ad-beta-Gal-treated (max 12.7 +/- 3.2%) or control nontreated rings (max 13.1 +/- 1.6%) (P < 0.01). The relaxations in Ad-15-LO-1-treated aorta were blocked by the 15-LO inhibitor cinnamyl-3,4-dihydroxy-a-cyanocinnamate. Overexpression of 15-LO-1 in the rabbit aortic endothelium is sufficient to increase the production of the vasodilatory HEETA and THETA and enhance the relaxations to AA. This confirms the role of HEETA and THETA as endothelium-derived relaxing factors.     

MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins

MOTIVATION: Protein-lipid interactions play a central role in cellular signaling and membrane trafficking and at the core of these interactions are domains specialized in lipid binding and membrane targeting. Considering the importance of these domains, we have created MeTaDoR, a comprehensive resource dedicated to membrane targeting domains (MTDs). RESULT: MeTaDoR begins with a brief introduction about all the important MTDs including their subcellular localization and structural features. Sequences of all known MTDs are then provided in two formats: standard Prosite format and a parsed tab-delimited format that provides a manually curated classification into binding or non-binding. Structures of all MTDs and host proteins known so far are provided with links to PDB and Pfam databases. Membrane-binding orientation of these proteins, whether experimentally determined or proposed, is also provided with links to the appropriate literature. To facilitate molecular dynamics studies of these proteins, the force-field parameters for many non-standard lipids that commonly interact with these proteins are also provided. Finally, an online server for predicting membrane-binding proteins and a search function with various search fields are included. The resource is publicly available and will be updated on a regular basis.     

Modeling bioaffinity-based targeted delivery of antimicrobials to Escherichia coli biofilms using yeast microparticles. Part II: Parameter evaluation and validation

The design of bioaffinity-based targeted delivery systems for biofilm inactivation may require a comprehensive understanding of physicochemical and biochemical properties of biobased antimicrobial particles and their interactions with biofilm. In this study, Escherichia coli biofilm inactivation by chlorine-charged yeast microparticles was numerically simulated, and the roles of chemical stability, binding affinity, and controlled release of this targeted delivery system were assessed using this numerical simulation. The simulation results were experimentally validated using two different types of yeast microparticles. The results of this study illustrate that chorine stability achieved by yeast microparticles was a key factor for improved biofilm inactivation in an organic-rich environment (>6 additional log reduction in 20 min compared to the free chlorine treatment). Moreover, the binding affinity of yeast microparticles to E. coli biofilms was another key factor for an enhanced inactivation of biofilm, as a 10-fold increase in binding rate resulted in a 4.2-fold faster inactivation. Overall, the mechanistic modeling framework developed in this study could guide the design and development of biobased particles for targeted inactivation of biofilms.     

Integration of protein motions with molecular networks reveals different mechanisms for permanent and transient interactions

The integration of molecular networks with other types of data, such as changing levels of gene expression or protein-structural features, can provide richer information about interactions than the simple node-and-edge representations commonly used in the network community. For example, the mapping of 3D-structural data onto networks enables classification of proteins into singlish- or multi-interface hubs (depending on whether they have >2 interfaces). Similarly, interactions can be classified as permanent or transient, depending on whether their interface is used by only one or by multiple partners. Here, we incorporate an additional dimension into molecular networks: dynamic conformational changes. We parse the entire PDB structural databank for alternate conformations of proteins and map these onto the protein interaction network, to compile a first version of the Dynamic Structural Interaction Network (DynaSIN). We make this network available as a readily downloadable resource file, and we then use it to address a variety of downstream questions. In particular, we show that multi-interface hubs display a greater degree of conformational change than do singlish-interface ones; thus, they show more plasticity which perhaps enables them to utilize more interfaces for interactions. We also find that transient associations involve smaller conformational changes than permanent ones. Although this may appear counterintuitive, it is understandable in the following framework: as proteins involved in transient interactions shuttle between interchangeable associations, they interact with domains that are similar to each other and so do not require drastic structural changes for their activity. We provide evidence for this hypothesis through showing that interfaces involved in transient interactions bind fewer classes of domains than those in a control set.