780 resultados para embedded computing


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The calculation of projection structures (PSs) from Protein Data Bank (PDB)-coordinate files of membrane proteins is not well-established. Reports on such attempts exist but are rare. In addition, the different procedures are barely described and thus difficult if not impossible to reproduce. Here we present a simple, fast and well-documented method for the calculation and visualization of PSs from PDB-coordinate files of membrane proteins: the projection structure visualization (PSV)-method. The PSV-method was successfully validated using the PS of aquaporin-1 (AQP1) from 2D crystals and cryo-transmission electron microscopy, and the PDB-coordinate file of AQP1 determined from 3D crystals and X-ray crystallography. Besides AQP1, which is a relatively rigid protein, we also studied a flexible membrane transport protein, i.e. the L-arginine/agmatine antiporter AdiC. Comparison of PSs calculated from the existing PDB-coordinate files of substrate-free and L-arginine-bound AdiC indicated that conformational changes are detected in projection. Importantly, structural differences were found between the PSV-method calculated PSs of the detergent-solubilized AdiC proteins and the PS from cryo-TEM of membrane-embedded AdiC. These differences are particularly exciting since they may reflect a different conformation of AdiC induced by the lateral pressure in the lipid bilayer.

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The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.

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This thesis presents two frameworks- a software framework and a hardware core manager framework- which, together, can be used to develop a processing platform using a distributed system of field-programmable gate array (FPGA) boards. The software framework providesusers with the ability to easily develop applications that exploit the processing power of FPGAs while the hardware core manager framework gives users the ability to configure and interact with multiple FPGA boards and/or hardware cores. This thesis describes the design and development of these frameworks and analyzes the performance of a system that was constructed using the frameworks. The performance analysis included measuring the effect of incorporating additional hardware components into the system and comparing the system to a software-only implementation. This work draws conclusions based on the provided results of the performance analysis and offers suggestions for future work.

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We developed a real-time PCR which allowed the highly sensitive detection of Naegleria fowleri in histological brain tissue sections from experimentally infected mice. This genus-specific small-subunit (18S) rRNA gene-based PCR can complement conventional (immuno-) histology for the diagnosis of primary amoebic meningoencephalitis in paraffin-embedded brain necropsy specimens that had been fixed in formalin buffered with phosphate-buffered saline.

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BACKGROUND: Diagnosis and prognosis in breast cancer are mainly based on histology and immunohistochemistry of formalin-fixed, paraffin-embedded (FFPE) material. Recently, gene expression analysis was shown to elucidate the biological variance between tumors and molecular markers were identified that led to new classification systems that provided better prognostic and predictive parameters. Archived FFPE samples represent an ideal source of tissue for translational research, as millions of tissue blocks exist from routine diagnostics and from clinical studies. These should be exploited to provide clinicians with more accurate prognostic and predictive information. Unfortunately, RNA derived from FFPE material is partially degraded and chemically modified and reliable gene expression measurement has only become successful after implementing novel and optimized procedures for RNA isolation, demodification and detection. METHODS: In this study we used tissue cylinders as known from the construction of tissue microarrays. RNA was isolated with a robust protocol recently developed for RNA derived from FFPE material. Gene expression was measured by quantitative reverse transcription PCR. RESULTS: Sixteen tissue blocks from 7 patients diagnosed with multiple histological subtypes of breast cancer were available for this study. After verification of appropriate localization, sufficient RNA yield and quality, 30 tissue cores were available for gene expression measurement on TaqMan(R) Low Density Arrays (16 invasive ductal carcinoma (IDC), 8 ductal carcinoma in situ (DCIS) and 6 normal tissue), and 14 tissue cores were lost. Gene expression values were used to calculate scores representing the proliferation status (PRO), the estrogen receptor status and the HER2 status. The PRO scores measured from entire sections were similar to PRO scores determined from IDC tissue cores. Scores determined from normal tissue cores consistently revealed lower PRO scores than cores derived from IDC or DCIS of the same block or from different blocks of the same patient. CONCLUSION: We have developed optimized protocols for RNA isolation from histologically distinct areas. RNA prepared from FFPE tissue cores is suitable for gene expression measurement by quantitative PCR. Distinct molecular scores could be determined from different cores of the same tumor specimen.