THE ROLE OF SMALL GTPASES IN REGULATING BLOOD-BRAIN BARRIER MECHANOTRANSDUCTION

Fluid shear stress is an important mediator of vascular permeability, yet the molecular mechanisms underlying the effect of shear on the blood-brain barrier (BBB) have yet to be clarified in cerebral vasculature despite its importance for brain homeostasis.. Neurological symptoms including the formation of microclots, stroke, and other neurological pathologies associated with changes in cerebral blood flow are hallmarks of BBB dysfunction. The in vitro model used in this dissertation is compatible with real-time measurement of barrier function using a transendothelial electrical resistance as well as immunocytochemistry and dextran permeability assays. These experiments reveal that there is a threshold level of shear stress required for barrier formation and that the composition of the extracellular matrix, specifically the presence of high molecular weight hyaluronan, dictates the flow response. Gene editing to modulate the expression of CD44, a mechanosensitive receptor for hyaluronan, demonstrates that the receptor is required for the endothelial response to shear stress. Manipulation of small GTPase activity reveals CD44 activates Rac1 while inhibiting RhoA activation. Additionally, adducin-gamma localizes to tight junctions in response to shear stress and RhoA inhibition and is required to maintain the barrier. This dissertation identifies specific components of the mechanosensing complex associated with the BBB response to fluid shear stress and, therefore, illuminates potential targets for barrier manipulation in vivo

Hardware implementation of boost power factor correction converter.

Nowadays, there has been an increasing demand of unity power factor in electrical power sector. Due to the nonlinear nature of load equipment, switching devices, source voltage and current are out of phase with each other. Many power converters topologies are used for the power factor correction. The boost converter with controller is most common for power factor correction circuits. The controller objective is to maintain the output voltage regulation and input current tracking with source voltage. The voltage ripple present due to the ac component of the current tracking objective, hence instead of ignoring that ripple, it is used in controller designing. The mathematical modeling of system depends on ac and dc dynamics of the circuit. The Lypunov stability analysis used for designing the controller of boost converter. In this work, experimental set-up for boost power factor correction converter was made with power pole board and NI compact RIO. The controller algorithm executed in LabVIEW FPGA module and results were verified. This novel controller ensures the convergence of the error signal by stability analysis

Assessment of clinical profile of acute viral hepatitis among paediatric age group patients at tertiary care centre

Background:Viral hepatitis keeps on being a significant medical issue worldwide and India. This issue is brought about by the 5 pathogenic hepatotropic infections perceived to date: hepatitis A (HAV), E(HEV), C(HCV), B(HBV) and D(HDV) infections. Be that as it may, most successive viral operators of acute viral hepatitis with significant wellbeing trouble in India are hepatitis A infection and hepatitis E infections. Material & Methods:The present prospective study was conducted at department of pediatrics of our tertiary care hospital. The study was anobservational study conducted during a period of one year. A total of 100 children who were of age 1 to 16 years and who were diagnosed withtwo or more symptoms of loss of appetite, nausea, vomiting, pain abdomen, itching and jaundice enrolled for study. along with patients who had positive serum levels of IgM HAV, IgM HEV and IgM HCV and hepatitis B surface antigen [HBsAg] were enrolled for study. Results: In present study, out of total study participants, based on the signs and symptoms, the most common presenting symptom was jaundice present in92% patientswhich was followed by hepatomegaly present in83% patients,which was followed by dark urinepresent in 82% patientswhich was followed by loss of appetite present in 82% patients. Out of total study participants, nausea was present among 76% patientswhich was followed by vomiting present in73% patients,which was followed by feverpresent in 70% patientswhich was followed by pain abdomen present in 82% patients. Out of total study participants, loose stools was present among 54% patientswhich was followed by itching present in38% patients,which was followed by Splenomegaly present in 21% patientswhich was followed by ascites present in 14% patients.Conclusion:It's critical to make mindfulness in the general public with respect to preventive measures including accessibility of immunization particularly in rustic territory. Better sterilization, arrangement of clean drinking water appropriate sewage removal, and government funded instruction are the backbones for counteraction of HAV and HEV contamination. Key words:Clinical profile, Viral hepatitis, hepatitis

MDFRCNN: Malware Detection using Faster Region Proposals Convolution Neural Network

Technological advancement of smart devices has opened up a new trend: Internet of Everything (IoE), where all devices are connected to the web. Large scale networking benefits the community by increasing connectivity and giving control of physical devices. On the other hand, there exists an increased ‘Threat’ of an ‘Attack’. Attackers are targeting these devices, as it may provide an easier ‘backdoor entry to the users’ network’.MALicious softWARE (MalWare) is a major threat to user security. Fast and accurate detection of malware attacks are the sine qua non of IoE, where large scale networking is involved. The paper proposes use of a visualization technique where the disassembled malware code is converted into gray images, as well as use of Image Similarity based Statistical Parameters (ISSP) such as Normalized Cross correlation (NCC), Average difference (AD), Maximum difference (MaxD), Singular Structural Similarity Index Module (SSIM), Laplacian Mean Square Error (LMSE), MSE and PSNR. A vector consisting of gray image with statistical parameters is trained using a Faster Region proposals Convolution Neural Network (F-RCNN) classifier. The experiment results are promising as the proposed method includes ISSP with F-RCNN training. Overall training time of learning the semantics of higher-level malicious behaviors is less. Identification of malware (testing phase) is also performed in less time. The fusion of image and statistical parameter enhances system performance with greater accuracy. The benchmark database from Microsoft Malware Classification challenge has been used to analyze system performance, which is available on the Kaggle website. An overall average classification accuracy of 98.12% is achieved by the proposed method

Streets as Public Spaces: Lessons from Street Vending in Ahmedabad, India

Public spaces go beyond the typical definition of being an open space. They reflect the diversity and vibrancy of the urban fabric and hold the power to create memories. Among all public spaces, streets emerge as the most public. Streets are engines of economic activities, social hubs, and platforms for civic engagement. They break socio-economic divides and foster social cohesion. Planning, designing, and managing better public spaces have become important global discussions. Sustainable Development Goals (8 and 11) and the New Urban Agenda emphasize the significance of inclusive and sustainable economy and safe, accessible and quality public spaces for all. The proposed article uses the case of street vending to understand the manifestation of these goals in an Indian context by assessing street vendors’ role in Ahmedabad’s urban fabric through extensive spatial analysis of 4,000 vendors at four different time points of the day, perception studies of their clientele disaggregated by gender, income and age, and their relationship with surrounding land-use and street hierarchy. It showcases how street vendors make the streets more vibrant by increasing activities, safer through ensuring inflow of people, and inclusive in its true sense by allowing people from different backgrounds to participate in the exchange of goods and services. It further argues that street vendors are vital elements of more equitable and exciting streets and public space

Machine Learning Approach for Comparative Analysis of De-Noising Techniques in Ultrasound Images of Ovarian Tumors

Ovarian abnormalities such ovarian cysts, tumors, and polycystic ovaries are one of the serious disorders affecting women's health. In ultrasound imaging of ovarian abnormalities, noise during capturing of the image and its transmission process frequently corrupts the image. In order to make the best judgments possible at the appropriate moment, ovarian cysts in females must be accurately detected.  In computer aided diagnosis of ovarian tumors, preprocessing is a very important step. In preprocessing, de-noising of medical images is a particularly a difficult task since it must be done while maintaining image features that are essential for diagnosis. In this research work we are using various denoising filters on ultrasound images of ovarian tumors. For different noise denoising techniques, performance measures like MSE, PSNR, SSIM, and UQI etc. are calculated. According to experimental findings, Block matching 3-D filter outperforms all other methods. Radiologists can better diagnose the condition with the use of this computer-assisted system

Heavy metal induced histopathological alterations in liver of Channa gachua (Ham)

Discharge of heavy metals into aquatic environment from various sources even below permissible levels, creates health hazards in aquatic organisms. The persistence and ubiquitous nature of these pollutant compounds coupled with their tendency to accumulate in organisms ultimately produce toxic reaction in aquatic biota especially, fish. This study aims to investigate histopathological impact of lethal (1.0625 ppm, 1.4202ppm) and sublethal (0.1062ppm, 0.0531ppm and 0.1420ppm, 0.0710ppm) concentrations of mercury chloride and copper chloride in liver of fresh water teleost, Channa gachua (Ham) .The histopathology studies revealed vacuolation in cytoplasm, degeneration of nuclei, vacuolation in stroma, cloudy swellings, pycnotic nuclei, necrosis, rupture of blood sinusoids, disarray of hepatic cords, loss of shape of hepatocytes. Severity of damage was found to be dose dependent and time of exposure

Efficient Image Processing Based Liver Cancer Detection Method

The hepar is the extensive internal organ in the human body. The liver is the second organ most generic involved by metastatic disease being liver cancer one of the prominent causes of death worldwide. Without healthy liver a person cannot survive. It is life threatening disease which is very challenging perceptible for both medical and engineering technologists. Medical image processing is used as a non-invasive method to detect tumours. The chances of survival having liver Tumor highly depends on early detection of Tumor and then classification as cancerous and non-cancerous tumours. Image processing techniques for automatic detection of brain are includes pre-processing and enhancement, image segmentation, classification and volume calculation, Poly techniques have been developed for the detection of liver Tumor and different liver toM oR detection algorithms and methodologies utilized for Tumor diagnosis. Novel methodology for the detection and diagnosis of liver Tumor

NANOPARTICLE: AS TARGETED DRUG DELIVERY SYSTEM FOR DEPRESSION

Nanoparticles (NP) are defined as particles with a diameter smaller than 100 nm, are increasingly used in different applications, including drug carrier systems and to pass organ barriers such as the blood-brain barrier. Particulate systems like nanoparticles have been used as a physical approach to alter and improve the pharmacokinetic and pharmacodynamic properties of various types of drug molecules. Different methods containing various polymers are used for formulation of nanoparticle to increase therapeutic benefit, while minimizing side effect for drug delivery research. While benefits of nanotechnology are widely publicised, the discussion of the potential effects of their widespread use in the consumer and industrial products are just beginning to emerge. This review provides comprehensive analysis of data available on health effects of nanomaterials