Production of L1 protein from different types of HPV in Pichia pastoris using an integrative vector

Human papillomavirus (HPV) infection is the most common sexually transmitted disease in the world and is related to the etiology of cervical cancer. The most common high-risk HPV types are 16 and 18; however, the second most prevalent type in the Midwestern region of Brazil is HPV-33. New vaccine strategies against HPV have shown that virus-like particles (VLP) of the major capsid protein (L1) induce efficient production of antibodies, which confer protection against the same viral type. The methylotrophic yeast Pichia pastoris is an efficient and inexpensive expression system for the production of high levels of heterologous proteins stably using a wild-type gene in combination with an integrative vector. It was recently demonstrated that P. pastoris can produce the HPV-16 L1 protein by using an episomal vector associated with the optimized L1 gene. However, the use of an episomal vector is not appropriate for protein production on an industrial scale. In the present study, the vectors were integrated into the Pichia genome and the results were positive for L1 gene transcription and protein production, both intracellularly and in the extracellular environment. Despite the great potential for expression by the P. pastoris system, our results suggest a low yield of L1 recombinant protein, which, however, does not make this system unworkable. The achievement of stable clones containing the expression cassettes integrated in the genome may permit optimizations that could enable the establishment of a platform for the production of VLP-based vaccines.

Overexpression of Fc receptor-like 1 associated with B-cell activation during hepatitis B virus infection

The role of B cells in the pathogenesis of hepatitis B virus (HBV) infection has not been explored in depth. In the present study, the activation status of B cells from peripheral blood of healthy controls (N = 20) and patients with acute hepatitis B (AHB, N = 15) or chronic hepatitis B (CHB, N = 30) was evaluated by measuring the expression levels of B-cell activation markers CD69 and CD86, using quantitative real-time PCR and flow cytometry. Moreover, the potential mechanism underlying B-cell activation during HBV infection was further investigated by analyzing the expression profile of FCRL1, an intrinsic activation molecule of B cells. An elevation in the levels of B-cell activation markers including CD69 and CD86 was observed in the AHB patients (44.31 ± 9.27, 27.64 ± 9.26%) compared to CHB patients (30.35 ± 11.27, 18.41 ± 6.56%, P < 0.05), which was still higher than healthy controls (12.23 ± 7.84, 8.22 ± 3.43%, P < 0.05). Furthermore, the expression of FCRL1 was found to be similar to B-cell activation markers, which was highest in AHB patients (70.15 ± 17.11%), lowest in healthy donors (36.32 ± 9.98%, P < 0.05) and half-way between these levels in patients with CHB (55.17 ± 12.03%, P < 0.05). The results were positively associated with aberrant B-cell activation. These data suggest that B cells can play a role in HBV infection, and therefore more effort should be devoted to exploring their functions.

PPARγ induces growth inhibition and apoptosis through upregulation of insulin-like growth factor-binding protein-3 in gastric cancer cells

Peroxisome proliferator activator receptor-gamma (PPARγ) is a ligand-activated transcriptional factor involved in the carcinogenesis of various cancers. Insulin-like growth factor-binding protein-3 (IGFBP-3) is a tumor suppressor gene that has anti-apoptotic activity. The purpose of this study was to investigate the anticancer mechanism of PPARγ with respect to IGFBP-3. PPARγ was overexpressed in SNU-668 gastric cancer cells using an adenovirus gene transfer system. The cells in which PPARγ was overexpressed exhibited growth inhibition, induction of apoptosis, and a significant increase in IGFBP-3 expression. We investigated the underlying molecular mechanisms of PPARγ in SNU-668 cells using an IGFBP-3 promoter/luciferase reporter system. Luciferase activity was increased up to 15-fold in PPARγ transfected cells, suggesting that PPARγ may directly interact with IGFBP-3 promoter to induce its expression. Deletion analysis of the IGFBP-3 promoter showed that luciferase activity was markedly reduced in cells without putative p53-binding sites (-Δ1755, -Δ1795). This suggests that the critical PPARγ-response region is located within the p53-binding region of the IGFBP-3 promoter. We further demonstrated an increase in PPARγ-induced luciferase activity even in cells treated with siRNA to silence p53 expression. Taken together, these data suggest that PPARγ exhibits its anticancer effect by increasing IGFBP-3 expression, and that IGFBP-3 is a significant tumor suppressor.

Activation of locus coeruleus heme oxygenase-carbon monoxide pathway promoted an anxiolytic-like effect in rats

The heme oxygenase-carbon monoxide pathway has been shown to play an important role in many physiological processes and is capable of altering nociception modulation in the nervous system by stimulating soluble guanylate cyclase (sGC). In the central nervous system, the locus coeruleus (LC) is known to be a region that expresses the heme oxygenase enzyme (HO), which catalyzes the metabolism of heme to carbon monoxide (CO). Additionally, several lines of evidence have suggested that the LC can be involved in the modulation of emotional states such as fear and anxiety. The purpose of this investigation was to evaluate the activation of the heme oxygenase-carbon monoxide pathway in the LC in the modulation of anxiety by using the elevated plus maze test (EPM) and light-dark box test (LDB) in rats. Experiments were performed on adult male Wistar rats weighing 250-300 g (n=182). The results showed that the intra-LC microinjection of heme-lysinate (600 nmol), a substrate for the enzyme HO, increased the number of entries into the open arms and the percentage of time spent in open arms in the elevated plus maze test, indicating a decrease in anxiety. Additionally, in the LDB test, intra-LC administration of heme-lysinate promoted an increase on time spent in the light compartment of the box. The intracerebroventricular microinjection of guanylate cyclase, an sGC inhibitor followed by the intra-LC microinjection of the heme-lysinate blocked the anxiolytic-like reaction on the EPM test and LDB test. It can therefore be concluded that CO in the LC produced by the HO pathway and acting via cGMP plays an anxiolytic-like role in the LC of rats.

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.

Energy evaluation of an evaporative cooling system using water driven ejector

The search for efficient and accessible cooling systems has increased worldwide. This study aims to build and evaluate an evaporative cooling system using a water driven ejector, allowing it to be installed in places with plenty of water. The system was investigated varying the flow rate and temperature of the circulating water, temperature of the replacement water, and coefficient of performance. The best vacuum obtained was 8.5 kPa at nominal operating conditions of 4.1 ± 0.1 m³/h and 5 ± 0.5 ºC for the circulating water reaching the temperature of 9.7 ± 0.5 ºC. The pulse-like disturbance generated by replacing the cooling water at different periods of times did not result in significant affect vacuum destabilization and the temperature rise in the cooling tank. The coefficient of performance of the system at the highest thermal power of 92.27 W was 0.077, which was underestimated due to possible problems related to pump efficiency. The system evaluated under the conditions proposed can be very efficient for cooling fluids at higher temperatures, and it can be complementary to main refrigeration systems.

Fusion of Data from Quadcopter’s Inertial Measurement Unit Using Complementary Filter

A quadcopter is a helicopter with four rotors, which is mechanically simple device, but requires complex electrical control for each motor. Control system needs accurate information about quadcopter’s attitude in order to achieve stable flight. The goal of this bachelor’s thesis was to research how this information could be obtained. Literature review revealed that most of the quadcopters, whose source-code is available, use a complementary filter or some derivative of it to fuse data from a gyroscope, an accelerometer and often also a magnetometer. These sensors combined are called an Inertial Measurement Unit. This thesis focuses on calculating angles from each sensor’s data and fusing these with a complementary filter. On the basis of literature review and measurements using a quadcopter, the proposed filter provides sufficiently accurate attitude data for flight control system. However, a simple complementary filter has one significant drawback – it works reliably only when the quadcopter is hovering or moving at a constant speed. The reason is that an accelerometer can’t be used to measure angles accurately if linear acceleration is present. This problem can be fixed using some derivative of a complementary filter like an adaptive complementary filter or a Kalman filter, which are not covered in this thesis.

Coolability of porous core debris beds : Effects of bed geometry and multi-dimensional flooding

This thesis addresses the coolability of porous debris beds in the context of severe accident management of nuclear power reactors. In a hypothetical severe accident at a Nordic-type boiling water reactor, the lower drywell of the containment is flooded, for the purpose of cooling the core melt discharged from the reactor pressure vessel in a water pool. The melt is fragmented and solidified in the pool, ultimately forming a porous debris bed that generates decay heat. The properties of the bed determine the limiting value for the heat flux that can be removed from the debris to the surrounding water without the risk of re-melting. The coolability of porous debris beds has been investigated experimentally by measuring the dryout power in electrically heated test beds that have different geometries. The geometries represent the debris bed shapes that may form in an accident scenario. The focus is especially on heap-like, realistic geometries which facilitate the multi-dimensional infiltration (flooding) of coolant into the bed. Spherical and irregular particles have been used to simulate the debris. The experiments have been modeled using 2D and 3D simulation codes applicable to fluid flow and heat transfer in porous media. Based on the experimental and simulation results, an interpretation of the dryout behavior in complex debris bed geometries is presented, and the validity of the codes and models for dryout predictions is evaluated. According to the experimental and simulation results, the coolability of the debris bed depends on both the flooding mode and the height of the bed. In the experiments, it was found that multi-dimensional flooding increases the dryout heat flux and coolability in a heap-shaped debris bed by 47–58% compared to the dryout heat flux of a classical, top-flooded bed of the same height. However, heap-like beds are higher than flat, top-flooded beds, which results in the formation of larger steam flux at the top of the bed. This counteracts the effect of the multi-dimensional flooding. Based on the measured dryout heat fluxes, the maximum height of a heap-like bed can only be about 1.5 times the height of a top-flooded, cylindrical bed in order to preserve the direct benefit from the multi-dimensional flooding. In addition, studies were conducted to evaluate the hydrodynamically representative effective particle diameter, which is applied in simulation models to describe debris beds that consist of irregular particles with considerable size variation. The results suggest that the effective diameter is small, closest to the mean diameter based on the number or length of particles.

Analysis of PWR-PACTEL Small Break LOCA experiment using TRACE

Currently, the power generation is one of the most significant life aspects for the whole man-kind. Barely one can imagine our life without electricity and thermal energy. Thus, different technologies for producing those types of energy need to be used. Each of those technologies will always have their own advantages and disadvantages. Nevertheless, every technology must satisfy such requirements as efficiency, ecology safety and reliability. In the matter of the power generation with nuclear energy utilization these requirements needs to be highly main-tained, especially since accidents on nuclear power plants may cause very long term deadly consequences. In order to prevent possible disasters related to the accident on a nuclear power plant strong and powerful algorithms were invented in last decades. Such algorithms are able to manage calculations of different physical processes and phenomena of real facilities. How-ever, the results acquired by the computing must be verified with experimental data.

Building IT architecture for developing nations using TOGAF

Developing nations vary in data usage techniques with respect to developed nations because of lack of standard information technology architecture. With the concept of globalization in the modern times, there is a necessity of information sharing between different developing nations for better advancements in socio-economic and science and technology fields. A robust IT architecture is needed and has to be built between different developing nations which eases information sharing and other data usage methods. A framework like TOGAF may work in this case as a normal IT framework may not fit to meet the requirements of an enterprise architecture. The intention of the thesis is to build an enterprise architecture between different developing nations using a framework TOGAF

Calculation of the optical conductivity for the Anderson impurity model using the slave boson technique

The optical conductivity of the Anderson impurity mode l has been calculated by emp l oying the slave boson technique and an expansion in powers of l i N, where N is the d egeneracy o f the f electron level . This method has been used to find the effective mass of the conduction electrons for temperatures above and below the Kondo tempera ture. For low temperatures, the mass enhancement is f ound to be large while a t high t emperatures, the mass enhancement is sma ll. The conductivity i s f ound to be Drude like with frequency dependent effective mass and scattering time for low independent effective mass and temperatures and scattering time f requency for high t emperatures. The behavior of both the effective mass and the conductivity is in qualitative agreement with experimental r esul t s .

Decoding algorithms using side-effect machines

Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems with applications to DNA. By using side effect machines we hope to be able to provide efficient decoding algorithms for this open problem. Two ideas for decoding algorithms are presented and examined. Both decoders use Side Effect Machines(SEMs) which are generalizations of finite state automata. Single Classifier Machines(SCMs) use a single side effect machine to classify all words within a code. Locking Side Effect Machines(LSEMs) use multiple side effect machines to create a tree structure of subclassification. The goal is to examine these techniques and provide new decoders for existing codes. Presented are ideas for best practices for the creation of these two types of new edit metric decoders.

Mode of action of FMRFamide-like peptide on drosophila body wall muscle conractions

Neuropeptides are the largest group of signalling chemicals that can convey the information from the brain to the cells of all tissues. DPKQDFMRFamide, a member of one of the largest families of neuropeptides, FMRFamide-like peptides, has modulatory effects on nerve-evoked contractions of Drosophila body wall muscles (Hewes et aI.,1998) which are at least in part mediated by the ability of the peptide to enhance neurotransmitter release from the presynaptic terminal (Hewes et aI., 1998, Dunn & Mercier., 2005). However, DPKQDFMRFamide is also able to act directly on Drosophila body wall muscles by inducing contractions which require the influx of extracellular Ca 2+ (Clark et aI., 2008). The present study was aimed at identifying which proteins, including the membrane-bound receptor and second messenger molecules, are involved in mechanisms mediating this myotropic effect of the peptide. DPKQDFMRFamide induced contractions were reduced by 70% and 90%, respectively, in larvae in which FMRFamide G-protein coupled receptor gene (CG2114) was silenced either ubiquitously or specifically in muscle tissue, when compared to the response of the control larvae in which the expression of the same gene was not manipulated. Using an enzyme immunoassay (EIA) method, it was determined that at concentrations of 1 ~M- 0.01 ~M, the peptide failed to increase cAMP and cGMP levels in Drosophila body wall muscles. In addition, the physiological effect of DPKQDFMRFamide at a threshold dose was not potentiated by 3-lsobutyl-1-methylxanthine, a phosphodiesterase inhibitor, nor was the response to 1 ~M peptide blocked or reduced by inhibitors of cAMP-dependent or cGMP-dependent protein kinases. The response to DPKQDFMRFamide was not affected in the mutants of the phosholipase C-~ (PLC~) gene (norpA larvae) or IP3 receptor mutants, which suggested that the PLC-IP3 pathway is not involved in mediat ing the peptide's effects. Alatransgenic flies lacking activity of calcium/calmodul in-dependent protein kinase (CamKII showed an increase in muscle tonus following the application of 1 JlM DPKQDFMRFamide similar to the control larvae. Heat shock treatment potentiated the response to DPKQDFMRFamide in both ala1 and control flies by approximately 150 and 100 % from a non heat-shocked larvae, respectively. Furthermore, a CaMKII inhibitor, KN-93, did not affect the ability of peptide to increase muscle tonus. Thus, al though DPKQDFMRFamide acts through a G-protein coupled FMRFamide receptor, it does not appear to act via cAMP, cGMP, IP3, PLC or CaMKl1. The mechanism through which the FMRFamide receptor acts remains to be determined.

Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).

Disease-Gene Association Using a Genetic Algorithm

Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.