326 research outputs found

    An Efficient Targeted Drug Delivery through Apotransferrin Loaded Nanoparticles

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    BACKGROUND: Cancerous state is a highly stimulated environment of metabolically active cells. The cells under these conditions over express selective receptors for assimilation of factors essential for growth and transformation. Such receptors would serve as potential targets for the specific ligand mediated transport of pharmaceutically active molecules. The present study demonstrates the specificity and efficacy of protein nanoparticle of apotransferrin for targeted delivery of doxorubicin. METHODOLOGY/PRINCIPAL FINDINGS: Apotransferrin nanoparticles were developed by sol-oil chemistry. A comparative analysis of efficiency of drug delivery in conjugated and non-conjugated forms of doxorubicin to apotransferrin nanoparticle is presented. The spherical shaped apotransferrin nanoparticles (nano) have diameters of 25-50 etam, which increase to 60-80 etam upon direct loading of drug (direct-nano), and showed further increase in dimension (75-95 etam) in conjugated nanoparticles (conj-nano). The competitive experiments with the transferrin receptor specific antibody showed the entry of both conj-nano and direct-nano into the cells through transferrin receptor mediated endocytosis. Results of various studies conducted clearly establish the superiority of the direct-nano over conj-nano viz. (a) localization studies showed complete release of drug very early, even as early as 30 min after treatment, with the drug localizing in the target organelle (nucleus) (b) pharmacokinetic studies showed enhanced drug concentrations, in circulation with sustainable half-life (c) the studies also demonstrated efficient drug delivery, and an enhanced inhibition of proliferation in cancer cells. Tissue distribution analysis showed intravenous administration of direct nano lead to higher drug localization in liver, and blood as compared to relatively lesser localization in heart, kidney and spleen. Experiments using rat cancer model confirmed the efficacy of the formulation in regression of hepatocellular carcinoma with negligible toxicity to kidney and liver. CONCLUSIONS: The present study thus demonstrates that the direct-nano is highly efficacious in delivery of drug in a target specific manner with lower toxicity to heart, liver and kidney

    Gravitational Waves from Gravitational Collapse

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    Gravitational wave emission from the gravitational collapse of massive stars has been studied for more than three decades. Current state of the art numerical investigations of collapse include those that use progenitors with realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non--axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with advanced ground--based and future space--based interferometric observatories.Comment: 68 pages including 13 figures; revised version accepted for publication in Living Reviews in Relativity (http://www.livingreviews.org

    Bacterial diversity in snow on North Pole ice floes

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    The microbial abundance and diversity in snow on ice floes at three sites near the North Pole was assessed using quantitative PCR and 454 pyrosequencing. Abundance of 16S rRNA genes in the samples ranged between 43 and 248 gene copies per millilitre of melted snow. A total of 291,331 sequences were obtained through 454 pyrosequencing of 16S rRNA genes, resulting in 984 OTUs at 97 % identity. Two sites were dominated by Cyanobacteria (72 and 61 %, respectively), including chloroplasts. The third site differed by consisting of 95 % Proteobacteria. Principal component analysis showed that the three sites clustered together when compared to the underlying environments of sea ice and ocean water. The Shannon indices ranged from 2.226 to 3.758, and the Chao1 indices showed species richness between 293 and 353 for the three samples. The relatively low abundances and diversity found in the samples indicate a lower rate of microbial input to this snow habitat compared to snow in the proximity of terrestrial and anthropogenic sources of microorganisms. The differences in species composition and diversity between the sites show that apparently similar snow habitats contain a large variation in biodiversity, although the differences were smaller than the differences to the underlying environment. The results support the idea that a globally distributed community exists in snow and that the global snow community can in part be attributed to microbial input from the atmosphere. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00792-014-0660-y) contains supplementary material, which is available to authorized users

    Atomically-thin micas as proton conducting membranes

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    Monolayers of graphene and hexagonal boron nitride (hBN) are highly permeable to thermal protons. For thicker two-dimensional (2D) materials, proton conductivity diminishes exponentially so that, for example, monolayer MoS2 that is just three atoms thick is completely impermeable to protons. This seemed to suggest that only one-atom-thick crystals could be used as proton conducting membranes. Here we show that few-layer micas that are rather thick on the atomic scale become excellent proton conductors if native cations are ion-exchanged for protons. Their areal conductivity exceeds that of graphene and hBN by one-two orders of magnitude. Importantly, ion-exchanged 2D micas exhibit this high conductivity inside the infamous gap for proton-conducting materials, which extends from 100 C to 500 C. Areal conductivity of proton-exchanged monolayer micas can reach above 100 S cm-2 at 500 C, well above the current requirements for the industry roadmap. We attribute the fast proton permeation to 5 A-wide tubular channels that perforate micas' crystal structure which, after ion exchange, contain only hydroxyl groups inside. Our work indicates that there could be other 2D crystals with similar nm-scale channels, which could help close the materials gap in proton-conducting applications

    Molecular Structures of Quiescently Grown and Brain-Derived Polymorphic Fibrils of the Alzheimer Amyloid Aβ9-40 Peptide: A Comparison to Agitated Fibrils

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    The presence of amyloid deposits consisting primarily of Amyloid-β (Aβ) fibril in the brain is a hallmark of Alzheimer's disease (AD). The morphologies of these fibrils are exquisitely sensitive to environmental conditions. Using molecular dynamics simulations combined with data from previously published solid-state NMR experiments, we propose the first atomically detailed structures of two asymmetric polymorphs of the Aβ9-40 peptide fibril. The first corresponds to synthetic fibrils grown under quiescent conditions and the second to fibrils derived from AD patients' brain-extracts. Our core structure in both fibril structures consists of a layered structure in which three cross-β subunits are arranged in six tightly stacked β-sheet layers with an antiparallel hydrophobic-hydrophobic and an antiparallel polar-polar interface. The synthetic and brain-derived structures differ primarily in the side-chain orientation of one β-strand. The presence of a large and continually exposed hydrophobic surface (buried in the symmetric agitated Aβ fibrils) may account for the higher toxicity of the asymmetric fibrils. Our model explains the effects of external perturbations on the fibril lateral architecture as well as the fibrillogenesis inhibiting action of amphiphilic molecules

    Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

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    <p>Abstract</p> <p>Background</p> <p>A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution.</p> <p>Results</p> <p>Our experimentation with <it>E. coli </it>and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms; this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives.</p> <p>Conclusion</p> <p>Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influences the prediction accuracy of the PPC approach. We note that the predictive power of the PPC approach, especially in eukaryotes, is heavily influenced by the primary endosymbiosis and subsequent bacterial contributions. The over-representation of parasitic unicellular eukaryotes and vertebrates additionally make eukaryotes less useful in the reference sets. Reference sets composed of highly non-redundant set of genomes from all three super-kingdoms fare better with pathways showing considerable vertical inheritance and strong conservation (e.g. translation apparatus), while reference sets solely composed of prokaryotic genomes fare better for more variable pathways like carbohydrate metabolism. Differential performance of the PPC approach on various pathways, and a weak positive correlation between functional and profile similarities suggest that caution should be exercised while interpreting functional linkages inferred from genome-wide large-scale profile comparisons using a single reference set.</p

    Improving protein function prediction methods with integrated literature data

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    <p>Abstract</p> <p>Background</p> <p>Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity.</p> <p>Results</p> <p>We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder, but co-occurrence data still proves beneficial.</p> <p>Conclusion</p> <p>Co-occurrence data is a valuable supplemental source for graph-theoretic function prediction algorithms. A rapidly growing literature corpus ensures that co-occurrence data is a readily-available resource for nearly every studied organism, particularly those with small protein interaction databases. Though arguably biased toward known genes, co-occurrence data provides critical additional links to well-studied regions in the interaction network that graph-theoretic function prediction algorithms can exploit.</p

    Clinical and Non-Clinical Aspects of Distal Radioulnar Joint Instability

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    Untreated distal radioulnar joint (DRUJ) injuries can give rise to long lasting complaints. Although common, diagnosis and treatment of DRUJ injuries remains a challenge. The articulating anatomy of the distal radius and ulna, among others, enables an extensive range of forearm pronosupination movements. Stabilization of this joint is provided by both intrinsic and extrinsic stabilizers and the joint capsule. These structures transmit the load and prevent the DRUJ from luxation during movement. Several clinical tests have been suggested to determine static or dynamic DRUJ stability, but their predictive value is unclear. Radiologic evaluation of DRUJ instability begins with conventional radiographs in anterioposterior and true lateral view. If not conclusive, CT-scan seems to be the best additional modality to evaluate the osseous structures. MRI has proven to be more sensitive and specific for TFCC tears, potentially causing DRUJ instability. DRUJ instability may remain asymptomatic. Symptomatic DRUJ injuries treatment can be conservative or operative. Operative treatment should consist of restoration of osseous and ligamenteous anatomy. If not successful, salvage procedures can be performed to regain stability

    Treatment of post-traumatic degenerative changes of the radio-carpal and distal radio-ulnar joints by combining radius, scaphoid, and lunate (RSL) fusion with ulnar head replacement

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    Distal radial fractures are a common type of fracture. In the case of intra-articular fractures, they often result in post-traumatic arthrosis. The objective of this study is to describe a novel alternative to the established salvage techniques for the treatment of post-traumatic arthrosis of the radio-carpal and distal radio-ulnar joints (DRUJ). Six patients with radio-carpal and DRUJ arthrosis were treated with a combined radius, scaphoid, and lunate (RSL) arthrodesis and as a Herbert ulnar head prosthesis. Follow-up consisted of both radiographic and functional assessments. Functional measurements were noted both pre- and postoperatively. No non-union or pseudoarthrosis was seen; neither did any of the ulnar head prostheses show loosening. Clinical examination showed an improvement in strength, pain, and range of movement, as well as a decrease in disability. Combining RSL arthrodesis with a Herbert ulnar head prosthesis, which deals with pain while retaining partial wrist movement, can be an alternative to established salvage procedures
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