Understanding the metabolic burden of recombinant antibody production in Saccharomyces cerevisiae using a quantitative metabolomics approach

The cellular changes induced by heterologous protein expression in the yeast Saccharomyces cerevisiae have been analysed on many levels and found to be significant. However, even though high‐level protein production poses a metabolic burden, evaluation of the expression host at the level of the metabolome has often been neglected. We present a comparison of metabolite profiles of a wild‐type strain with those of three strains producing recombinant antibody variants of increasing size and complexity: an scFv fragment, an scFv–Fc fusion protein and a full‐length IgG molecule. Under producing conditions, all three recombinant strains showed a clear decrease in growth rate compared with the wild‐type strain and the severity of the growth phenotype increased with size of the protein. The levels of 76 intracellular metabolites were determined using a targeted (semi) quantitative mass spectrometry based approach. Based on unsupervised and supervised multivariate analysis of metabolite profiles, together with pathway activity profiling, the recombinant strains were found to be significantly different from each other and from the wild‐type strain. We observed the most prominent changes in metabolite levels for metabolites involved in amino acid and redox metabolism. Induction of the unfolded protein response was detected in all producing strains and is considered to be a contributing factor to the overall metabolic burden on the cells.     

Location Related Signals with Satellite Image Fusion Method Using Visual Image Integration Method

Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand of upgrading the view of a scene by combining data caught from various picture sensors is usually known as multisensor picture combination. This paper displays a territory based picture combination calculation to consolidate SAR (Synthetic Aperture Radar) and optical pictures. The co-enlistment of the two images is first led utilizing the proposed enrollment method prior to picture combination. The paper displays a parallel execution of existing picture combination techniques on a graphical group. Parallel executions of techniques in view of discrete wavelet changes are created. Division into dynamic and motionless regions is then executed on the SAR surface picture for particular injection of the SAR picture into panchromatic (PAN) picture. An integrated image in view of these two pictures is produced by the novel region based combination plot, which forces diverse combination rules for each fragmented region. At long last, this picture is melded into a multispectral(MS) picture through the half breed skillet honing technique proposed in past research. Exploratory outcomes exhibit that the proposed strategy demonstrates preferred execution over different fusion algorithms and can possibly be connected to the multisensory combination of SAR and optical pictures.     

High-throughput analysis of multispectral images of breast cancer tissue.

Statistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast.     

Mechanical Properties and Dry Sliding Wear Behaviour of Molybdenum Disulphide Reinforced Zinc–Aluminium Alloy Composites

ZA-27 alloy is a lightest alloy which offers excellent bearing and mechanical properties in automobile and industrial applications. In this study, the MoS₂ particles with 0.5, 1 and 1.5 (wt%) weight percentages were reinforced in ZA-27 alloy to form composites, which were fabricated by using ultrasonic assisted stir casting method. The ZA-27/MoS₂ composite specimens were examined for chemical composition with the aid of XRD technique and EDS. Microstructure analysis of the ZA-27/MoS₂ composites was studied using SEM. Tests were conducted for mechanical properties such as tensile strength and hardness on ZA-27/MoS₂ composites samples as per ASTM standards. Dry sliding wear behavior of the composites was tested at various operating conditions by using pin-on-disc apparatus. Microstructural images of the ZA-27 composites reveal that there is a uniform dispersion of the MoS₂ particles in the base material. From the results it is observed that the mechanical properties increases with ZA-27 reinforced with 0.5 wt% MoS₂ composite and further decreases with increase in the filler content. The enhanced wear resistance is observed in ZA-27 reinforced MoS₂ composites as compared to the unreinforced alloy. The wear rate of the ZA-27 composites decreases with the increase in filler content, further the worn surfaces as examined using SEM reveals the wear mechanism explaining the improved wear resistance of the particulate composites.     

Electrical conductivity measurements of nanofluids and development of new correlations

In this study the electrical conductivity of aluminum oxide (Al2O3), silicon dioxide (SiO2) and zinc oxide (ZnO) nanoparticles dispersed in propylene glycol and water mixture were measured in the temperature range of 0 degrees C to 90 degrees C. The volumetric concentration of nanoparticles in these fluids ranged from 0 to 10% for different nanofluids. The particle sizes considered were from 20 nm to 70 nm. The electrical conductivity measuring apparatus and the measurement procedure were validated by measuring the electrical conductivity of a calibration fluid, whose properties are known accurately. The measured electrical conductivity values agreed within +/- 1% with the published data reported by the manufacturer. Following the validation, the electrical conductivities of different nanofluids were measured. The measurements showed that electrical conductivity of nanofluids increased with an increase in temperature and also with an increase in particle volumetric concentration. For the same nanofluid at a fixed volumetric concentration, the electrical conductivity was found to be higher for smaller particle sizes. From the experimental data, empirical models were developed for three nanofluids to express the electrical conductivity as functions of temperature, volumetric concentration and the size of the nanoparticles.     

Experimental determination of thermal conductivity of three nanofluids and development of new correlations

Experimental investigations have been carried out for determining the thermal conductivity of three nanofluids containing aluminum oxide, copper oxide and zinc oxide nanoparticles dispersed in a base fluid of 60:40 (by mass) ethylene glycol and water mixture. Particle volumetric concentration tested was up to 10% and the temperature range of the experiments was from 298 to 363 K. The results show an increase in the thermal conductivity of nanofluids compared to the base fluids with an increasing volumetric concentration of nanoparticles. The thermal conductivity also increases substantially with an increase in temperature. Several existing models for thermal conductivity were compared with the experimental data obtained from these nanofluids, and they do not exhibit good agreement. Therefore, a model was developed, which is a refinement of an existing model, which incorporates the classical Maxwell model and the Brownian motion effect to account for the thermal conductivity of nanofluids as a function of temperature, particle volumetric concentration, the properties of nanoparticles, and the base fluid, which agrees well with the experimental data.     

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In this study the pH levels of aluminum oxide (Al₂O₃), silicon dioxide (SiO₂), and zinc oxide (ZnO) nanoparticles dispersed in propylene glycol and water mixture were measured in the temperature range of 0°C to 90°C. The volumetric concentration of nanoparticles in these fluids ranged from 0 to 10% for different nanofluids. The average particle sizes (APS) considered were from 10 nm to 70 nm. The pH measuring apparatus and the measurement procedure were validated by measuring the pH of a calibration fluid, whose properties are known accurately. The measured pH values agreed within less than ±0.5% with the published data reported by the manufacturer. Following the validation, the pH values of different nanofluids were measured. The measurements showed that pH of nanofluids decreased with an increase in temperature and increased with an increase in particle volumetric concentration. For the same nanofluid at a fixed volumetric concentration, the pH was found to be higher for larger particle sizes. From the experimental data, empirical models were developed for three nanofluids to express the pH as functions of temperature, volumetric concentration, and the size of the nanoparticles.     

Automating the simulation of complex discrete-time control systems:a mathematical framework, algorithms, and a software package

With the rapid proliferation of complex control systems, such as adaptive control systems, a need has arisen to automate as much as possible of the time-consuming preparatory work needed to simulate such systems. This burden currently falls on the user. The smaller the user time required and the more effortless the process, the greater, the authors believe, will be the eventual widespread acceptability of these control systems. This paper is aimed at bridging this gap between the theoretical specification of a complex discrete-time control system as described in a typical research paper and the obtaining of a first simulation. It provides a graph theoretical formulation of the issues involved, discrete algorithms to execute these tasks, and finally describes ISIM, an interpretive simulator which incorporates these features. These algorithms automate the simulation process, as seen by the user. The net result is a package which essentially requires only that the user type in a control system more or less verbatim from a technical paper to obtain a simulation output     

Geographic Information System for Coordination of Fast-Track Projects

To meet the increasing demands to deliver projects within a short period of time, many projects are being executed on a fast-track basis. On fast-track projects, the construction begins when the design is between 35% and 65% complete. This poses numerous challenges. One of the key challenges is to ensure that the flow of information and deliverables between the engineering, procurement, and construction is synchronized. This work initially studied the information flow on process plant projects, the disruptions to information flow, and the problems faced due to the disruptions. It was identified that an information system that has the capability to (1) capture the relationships between different deliverables, (2) record the status of deliverables, and (3) process queries from any of the teams regarding status and impact of disruptions will support the decision-making required for rapid development of pragmatic plans. Further, as the information requirements require the representation and querying of both spatial and nonspatial data, the design and implementation of the system using the concepts and features of a geographic information system was explored. The paper discusses the design of the geographic information system and its implementation within the AutoCAD Map environment. The use of the system to retrieve information required for project coordination is illustrated through sample queries.