973 resultados para Fusion Proteins


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The 15 members of the kallikrein-related serine peptidase (KLK) family have diverse tissue-specific expression profiles and roles in a range of cellular processes, including proliferation, migration, invasion, differentiation, inflammation and angiogenesis that are required in both normal physiology as well as pathological conditions. These roles require cleavage of a range of substrates, including extracellular matrix proteins, growth factors, cytokines as well as other proteinases. In addition, it has been clear since the earliest days of KLK research that cleavage of cell surface substrates is also essential in a range of KLK-mediated cellular processes where these peptidases are essentially acting as agonists and antagonists. In this review we focus on these KLK-regulated cell surface receptor systems including bradykinin receptors, proteinase-activated receptors, as well as the plasminogen activator, ephrins and their receptors, and hepatocyte growth factor/Met receptor systems and other plasma membrane proteins. From this analysis it is clear that in many physiological and pathological settings KLKs have the potential to regulate multiple receptor systems simultaneously; an important issue when these peptidases and substrates are targeted in disease.

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The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

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As the Internet becomes deeply embedded into consumers’ daily life, the digital virtual world brings significant influence to consumers’ self and narrative. Prior studies look at consumer self from either from a certain online space or comparing consumers’ physical and digital virtual selves but not the integration of the physical/digital world. This paper aims to explore the meanings of the digital virtual space on consumers’ narrative as a whole (their interests, dreams, or subjectivity). We utilise a postmodern concept of the cyborg to understand the cultural complexity, subjective meanings of, and the extent to which the digital virtual space plays a role in consumers’ self-narrative. We conducted in-depth interviews and gathered three consumer narratives. Our findings indicate that consumers’ narrative contains important fragments from both physical and digital virtual worlds and their physical and digital virtual selves form a feedback loop that strengthen their overall narrative.

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Methods are presented for the preparation, ligand density analysis and use of an affinity adsorbent for the purification of a glutathione S-transferase (GST) fusion protein in packed and expanded bed chromatographic processes. The protein is composed of GST fused to a zinc finger transcription factor (ZnF). Glutathione, the affinity ligand for GST purification, is covalently immobilized to a solid-phase adsorbent (Streamline™). The GST–ZnF fusion protein displays a dissociation constant of 0.6 x10-6 M to glutathione immobilized to Streamline™. Ligand density optimization, fusion protein elution conditions (pH and glutathione concentration) and ligand orientation are briefly discussed.

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Upon infection, Legionella pneumophila uses the Dot/Icm type IV secretion system to translocate effector proteins from the Legionella-containing vacuole (LCV) into the host cell cytoplasm. The effectors target a wide array of host cellular processes that aid LCV biogenesis, including the manipulation of membrane trafficking. In this study, we used a hidden Markov model screen to identify two novel, non-eukaryotic soluble NSF attachment protein receptor (SNARE) homologs: the bacterial Legionella SNARE effector A (LseA) and viral SNARE homolog A proteins. We characterized LseA as a Dot/Icm effector of L. pneumophila, which has close homology to the Qc-SNARE subfamily. The lseA gene was present in multiple sequenced L. pneumophila strains including Corby and was well distributed among L. pneumophila clinical and environmental isolates. Employing a variety of biochemical, cell biological and microbiological techniques, we found that farnesylated LseA localized to membranes associated with the Golgi complex in mammalian cells and LseA interacted with a subset of Qa-, Qb- and R-SNAREs in host cells. Our results suggested that LseA acts as a SNARE protein and has the potential to regulate or mediate membrane fusion events in Golgi-associated pathways.

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Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

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There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

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Erythropoietin (EPO), a glycoprotein hormone of ∼34 kDa, is an important hematopoietic growth factor, mainly produced in the kidney and controls the number of red blood cells circulating in the blood stream. Sensitive and rapid recombinant human EPO (rHuEPO) detection tools that improve on the current laborious EPO detection techniques are in high demand for both clinical and sports industry. A sensitive aptamer-functionalized biosensor (aptasensor) has been developed by controlled growth of gold nanostructures (AuNS) over a gold substrate (pAu/AuNS). The aptasensor selectively binds to rHuEPO and, therefore, was used to extract and detect the drug from horse plasma by surface enhanced Raman spectroscopy (SERS). Due to the nanogap separation between the nanostructures, the high population and distribution of hot spots on the pAu/AuNS substrate surface, strong signal enhancement was acquired. By using wide area illumination (WAI) setting for the Raman detection, a low RSD of 4.92% over 150 SERS measurements was achieved. The significant reproducibility of the new biosensor addresses the serious problem of SERS signal inconsistency that hampers the use of the technique in the field. The WAI setting is compatible with handheld Raman devices. Therefore, the new aptasensor can be used for the selective extraction of rHuEPO from biological fluids and subsequently screened with handheld Raman spectrometer for SERS based in-field protein detection.

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The stoned locus in Drosophila encodes two proteins StonedA (STNA) and StonedB (STNB), both of which have been suggested to act as adaptins in mediating synaptic vesicle recycling. A combination of immunological, genetic and biochemical studies have shown an interaction of STNA and STNB with the C2B domain of Synaptotagmin-I (SYT-1), an integral synaptic vesicle protein that mediates Ca2+-dependent exocytosis, as well as endocytosis. The C2B domain of SYT-1 contains an AP-2 binding site that controls the size of recycled vesicles, and a C-terminal tryptophan-containing motif that acts as an internalization signal. Investigation of SYT-1 mutations in Drosophila has shown that altering the Ca2+ binding region of the C2B domain, results in a reduction in the rate of vesicle recycling, implicating this region in SYT-I endocytosis. In this poster, we report the molecular dissection of the interactions between the STNA and STNB proteins and the C2B domain of SYT-1. Deletion of the AP-2 binding site decreased the binding of both STNA and STNB. However, C-terminal deletions of the C2B domain significantly increased STNB binding. In contrast, the same C-terminal deletions reduced the affinity of the C2B domain for STNA. The possible interactions of both STNB and STNA with the Ca2+ binding region of SYT-1 will be also investigated.

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Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

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MicroRNAs (miRNAs) are small regulatory RNAs produced by Dicer proteins that regulate gene expression in development and adaptive responses to the environment1,​2,​3,​4. In animals, the degree of base pairing between a miRNA and its target messenger RNA seems to determine whether the regulation occurs through cleavage or translation inhibition1. In contrast, the selection of regulatory mechanisms is independent of the degree of mismatch between a plant miRNA and its target transcript5. However, the components and mechanism(s) that determine whether a plant miRNA ultimately regulates its targets by guiding cleavage or translational inhibition are unknown6. Here we show that the form of regulatory action directed by a plant miRNA is determined by DRB2, a DICER-LIKE1 (DCL1) partnering protein. The dependence of DCL1 on DRB1 for miRNA biogenesis is well characterized7,​8,​9, but we show that it is only required for miRNA-guided transcript cleavage. We found that DRB2 determines miRNA-guided translational inhibition and represses DRB1 expression, thereby allowing the active selection of miRNA regulatory action. Furthermore, our results reveal that the core silencing proteins ARGONAUTE1 (AGO1) and SERRATE (SE) are highly regulated by miRNA-guided translational inhibition. DRB2 has been remarkably conserved throughout plant evolution, raising the possibility that translational repression is the ancient form of miRNA-directed gene regulation in plants, and that Dicer partnering proteins, such as human TRBP, might play a similar role in other eukaryotic systems.

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Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.