Excellence in Research and Innovation for Humanity

International Science Index

Commenced in January 1999 Frequency: Monthly Edition: International Paper Count: 11

Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering

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  • 11
    Biosensor Measurement of Urea Coonncentration in Human Blood Serum

    An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.

    Data Mining Classification Methods Applied in Drug Design
    Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.
    Comparison of Valuation Techniques for Bone Age Assessment
    This comparison of valuation techniques for bone age assessment is a work carried out by the Telemedicine Research Group of the Military University - TIGUM, as a preliminary to the Design and development a treatment system of hand and wrist radiological images for children aged 0-6 years to bone age assessment . In this paper the techniques mentioned for decades have been the most widely used and the statistically significant. Althought, initially with the current project, it wants to work with children who have limit age, this comparison and evaluation techniques work will help in the future to expand the study subject in the system to bone age assessment, implementing more techniques, tools and deeper analysis to accomplish this purpose.
    An Automatic Sleep Spindle Detector based on WT, STFT and WMSD
    Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.
    Evaluation of Newly Developed Dot-ELISA Test for Identification of Naja-naja sumantrana and Calloselasma rhodostoma Venom Antigens
    Snake bite cases in Malaysia most often involve the species Naja-naja and Calloselasma rhodostoma. In keeping with the need for a rapid snake venom detection kit in a clinical setting, plate and dot-ELISA test for the venoms of Naja-naja sumatrana, Calloselasma rhodostoma and the cobra venom fraction V antigen was developed. Polyclonal antibodies were raised and further used to prepare the reagents for the dot-ELISA test kit which was tested in mice, rabbit and virtual human models. The newly developed dot- ELISA kit was able to detect a minimum venom concentration of 244ng/ml with cross reactivity of one antibody type. The dot-ELISA system was sensitive and specific for all three snake venom types in all tested animal models. The lowest minimum venom concentration detectable was in the rabbit model, 244ng/ml of the cobra venom fraction V antigen. The highest minimum venom concentration was in mice, 1953ng/ml against a multitude of venoms. The developed dot-ELISA system for the detection of three snake venom types was successful with a sensitivity of 95.8% and specificity of 97.9%.
    Computational Study on Cardiac-Coronary Interaction in Terms of Coronary Flow-Pressure Waveforms in Presence of Drugs: Comparison Between Simulated and In Vivo Data
    Cardiovascular human simulator can be a useful tool in understanding complex physiopathological process in cardiocirculatory system. It can also be a useful tool in order to investigate the effects of different drugs on hemodynamic parameters. The aim of this work is to test the potentiality of our cardiovascular numerical simulator CARDIOSIM© in reproducing flow/pressure coronary waveforms in presence of two different drugs: Amlodipine (AMLO) and Adenosine (ADO). In particular a time-varying intramyocardial compression, assumed to be proportional to the left ventricular pressure, was related to the venous coronary compliances in order to study its effects on the coronary blood flow and the flow/pressure loop. Considering that coronary circulation dynamics is strongly interrelated with the mechanics of the left ventricular contraction, relaxation, and filling, the numerical model allowed to analyze the effects induced by the left ventricular pressure on the coronary flow.
    Microalbuminuria in Human Immunodeficiency Virus Infection and Acquired Immunodeficiency Syndrome
    Human immunodeficiency virus infection and acquired immunodeficiency syndrome is a global pandemic with cases reporting from virtually every country and continues to be a common infection in developing country like India. Microalbuminuria is a manifestation of human immunodeficiency virus associated nephropathy. Therefore, microalbuminuria may be an early marker of human immunodeficiency virus associated nephropathy, and screening for its presence may be beneficial. A strikingly high prevalence of microalbuminuria among human immunodeficiency virus infected patients has been described in various studies. Risk factors for clinically significant proteinuria include African - American race, higher human immunodeficiency virus ribonucleic acid level and lower CD4 lymphocyte count. The cardiovascular risk factors of increased systolic blood pressure and increase fasting blood sugar level are strongly associated with microalbuminuria in human immunodeficiency virus patient. These results suggest that microalbuminuria may be a sign of current endothelial dysfunction and micro-vascular disease and there is substantial risk of future cardiovascular disease events. Positive contributing factors include early kidney disease such as human immunodeficiency virus associated nephropathy, a marker of end organ damage related to co morbidities of diabetes or hypertension, or more diffuse endothelial cells dysfunction. Nevertheless after adjustment for non human immunodeficiency virus factors, human immunodeficiency virus itself is a major risk factor. The presence of human immunodeficiency virus infection is independent risk to develop microalbuminuria in human immunodeficiency virus patient. Cardiovascular risk factors appeared to be stronger predictors of microalbuminuria than markers of human immunodeficiency virus severity person with human immunodeficiency virus infection and microalbuminuria therefore appear to potentially bear the burden of two separate damage related to known vascular end organ damage related to know vascular risk factors, and human immunodeficiency virus specific processes such as the direct viral infection of kidney cells.The higher prevalence of microalbuminuria among the human immunodeficiency virus infected could be harbinger of future increased risks of both kidney and cardiovascular disease. Further study defining the prognostic significance of microalbuminuria among human immunodeficiency virus infected persons will be essential. Microalbuminuria seems to be a predictor of cardiovascular disease in diabetic and non diabetic subjects, hence it can also be used for early detection of micro vascular disease in human immunodeficiency virus positive patients, thus can help to diagnose the disease at the earliest.
    Classification Algorithms in Human Activity Recognition using Smartphones
    Rapid advancement in computing technology brings computers and humans to be seamlessly integrated in future. The emergence of smartphone has driven computing era towards ubiquitous and pervasive computing. Recognizing human activity has garnered a lot of interest and has raised significant researches- concerns in identifying contextual information useful to human activity recognition. Not only unobtrusive to users in daily life, smartphone has embedded built-in sensors that capable to sense contextual information of its users supported with wide range capability of network connections. In this paper, we will discuss the classification algorithms used in smartphone-based human activity. Existing technologies pertaining to smartphone-based researches in human activity recognition will be highlighted and discussed. Our paper will also present our findings and opinions to formulate improvement ideas in current researches- trends. Understanding research trends will enable researchers to have clearer research direction and common vision on latest smartphone-based human activity recognition area.
    Effect of Secondary Curvature on Mixing Characteristic within Constant Circular Tubes
    In this study, numerical simulations on laminar flow in sinusoidal wavy shaped tubes were conducted for mean Reynolds number of 250, which is in the range of physiological flow-rate and investigated flow structures, pressure distribution and particle trajectories both in steady and periodic inflow conditions. For extensive comparisons, various wave lengths and amplitudes of sine function for geometry of tube models were employed. The results showed that small amplitude secondary curvature has significant influence on the nature of flow patterns and particle mixing mechanism. This implies that characterizing accurate geometry is essential in accurate predicting of in vivo hemodynamics and may motivate further study on any possibility of reflection of secondary flow on vascular remodeling and pathophysiology.
    An Improved QRS Complex Detection for Online Medical Diagnosis
    This paper presents the work of signal discrimination specifically for Electrocardiogram (ECG) waveform. ECG signal is comprised of P, QRS, and T waves in each normal heart beat to describe the pattern of heart rhythms corresponds to a specific individual. Further medical diagnosis could be done to determine any heart related disease using ECG information. The emphasis on QRS Complex classification is further discussed to illustrate the importance of it. Pan-Tompkins Algorithm, a widely known technique has been adapted to realize the QRS Complex classification process. There are eight steps involved namely sampling, normalization, low pass filter, high pass filter (build a band pass filter), derivation, squaring, averaging and lastly is the QRS detection. The simulation results obtained is represented in a Graphical User Interface (GUI) developed using MATLAB.
    Predictability Analysis on HIV/AIDS System using Hurst Exponents
    Methods of contemporary mathematical physics such as chaos theory are useful for analyzing and understanding the behavior of complex biological and physiological systems. The three dimensional model of HIV/AIDS is the basis of active research since it provides a complete characterization of disease dynamics and the interaction of HIV-1 with the immune system. In this work, the behavior of the HIV system is analyzed using the three dimensional HIV model and a chaotic measure known as the Hurst exponent. Results demonstrate that Hurst exponents of CD4, CD8 cells and viral load vary nonlinearly with respect to variations in system parameters. Further, it was observed that the three dimensional HIV model can accommodate both persistent (H>0.5) and anti-persistent (H