Physical Exercise Intervention on Hypertension Patients

Chronic diseases prevailed along with economic growth as well as life style changed in recent years in Taiwan. According to the governmental statistics, hypertension related disease is the tenth of death causes with 1,816 died directly from hypertension in 2010. There were more death causes amongst the top ten had been proofed that having strong association with the hypertension, such as heart diseases, cardiovascular diseases, and diabetes. Hypertension or High blood pressure is one of the major indicators for chronic diseases, and was generally perceived as the major causes of mortality. The literature generally suggested that regular physical exercise was helpful to prevent the occurrence or to ease the progress of a hypertension. This paper reported the process and outcomes in detailed of an improvement project of physical exercise intervention specific for hypertension patients. Physical information were measured before and after the project to obtain information such as weight, waistline, cholesterol (HD & LD), blood examination, as well as self-perceived health status. The intervention project involved a six-week exercise program, of which contained three times a week, 30 minutes of tutored physical exercise intervention. The project had achieved several gains in changing the subjects- behavior in terms of many important biophysical indexes. Around 20% of the participants had significantly improved their cholesterols, BMI, and changed unhealthy behaviors. Results from the project were encouraging, and would be good reference for other samples.

A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Red Diode Laser in the Treatment of Epidermal Diseases in PDT

The process of laser absorption in the skin during laser irradiation was a critical point in medical application treatments. Delivery the correct amount of laser light is a critical element in photodynamic therapy (PDT). More amounts of laser light able to affect tissues in the skin and small amount not able to enhance PDT procedure in skin. The knowledge of the skin tone laser dependent distribution of 635 nm radiation and its penetration depth in skin is a very important precondition for the investigation of advantage laser induced effect in (PDT) in epidermis diseases (psoriasis). The aim of this work was to estimate an optimum effect of diode laser (635 nm) on the treatment of epidermis diseases in different color skin. Furthermore, it is to improve safety of laser in PDT in epidermis diseases treatment. Advanced system analytical program (ASAP) which is a new approach in investigating the PDT, dependent on optical properties of different skin color was used in present work. A two layered Realistic Skin Model (RSM); stratum corneum and epidermal with red laser (635 nm, 10 mW) were used for irradiative transfer to study fluence and absorbance in different penetration for various human skin colors. Several skin tones very fair, fair, light, medium and dark are used to irradiative transfer. This investigation involved the principles of laser tissue interaction when the skin optically injected by a red laser diode. The results demonstrated that the power characteristic of a laser diode (635 nm) can affect the treatment of epidermal disease in various color skins. Power absorption of the various human skins were recorded and analyzed in order to find the influence of the melanin in PDT treatment in epidermal disease. A two layered RSM show that the change in penetration depth in epidermal layer of the color skin has a larger effect on the distribution of absorbed laser in the skin; this is due to the variation of the melanin concentration for each color.

Association of Selected Biochemical Markers and Body Mass Index in Women with Endocrine Disorders

Obesity is frequent attendant phenomenon of patients with endocrinological disease. Between BMI and endocrinological diseases is close correlation. In thesis we focused on the allocation of hormone concentration – PTH and TSH, CHOL a mineral element Ca in a blood serum. The examined group was formed by 100 respondents (women) aged 36 – 83 years, who were divided into two groups – control group (CG), group with diagnosed endocrine disease (DED). The concentration of PTH and TSH, Ca and CHOL was measured through the medium of analyzers Cobas e411 (Japan); Cobas Integra 400 (Switzerland). At individuals was measured body weight as well as stature and thereupon from those data we enumerated BMI. On the basis of Student T-test in biochemical parameter of PTH and Ca we found out significantly meaningful difference (p

Fenugreek in the Ecological Areas of Belarus and France

On the territory of France fenugreek is spread since long on a line from the Gironde to the Italian border. In Belarus experimental cultivation has begun since 2004. Experiments with fenugreek variety Ovari 4 were conducted about time of sowing in order to study their growth, development, and evaluation of productivity in the North-east part of Belarus and Central part of France. Reaching full ripeness of seeds the plants of fenugreek in the Central part of France requires about 94-97 days. Average seeds yield of 2011-2012 is 1259 kg/ha. Plant height is about 36,8 cm. Plants were affected by aphid and in the high moist agro-climatic conditions by powdery mildew. In North-east part of Belarus plants need 86-93 days to full ripeness. Plants of fenugreek have steam about 59 cm. The average seeds yield of 2007-2009 was about 723 kg/ha. Plants were resistant to aphid and diseases.

Capacitive Air Bubble Detector Operated at Different Frequencies for Application in Hemodialysis

Air bubbles have been detected in human circulation of end-stage renal disease patients who are treated by hemodialysis. The consequence of air embolism, air bubbles, is under recognized and usually overlooked in daily practice. This paper shows results of a capacitor based detection method that capable of detecting the presence of air bubbles in the blood stream in different frequencies. The method is based on a parallel plates capacitor made of platinum with an area of 1.5 cm2 and a distance between the two plates is 1cm. The dielectric material used in this capacitor is Dextran70 solution which mimics blood rheology. Simulations were carried out using RC circuit at two frequencies 30Hz and 3 kHz and results compared with experiments and theory. It is observed that by injecting air bubbles of different diameters into the device, there were significant changes in the capacitance of the capacitor. Furthermore, it is observed that the output voltage from the circuit increased with increasing air bubble diameter. These results demonstrate the feasibility of this approach in improving air bubble detection in Hemodialysis.

MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Study of EEGs from Somatosensory Cortex and Alzheimer's Disease Sources

This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.

Segmentation of Lungs from CT Scan Images for Early Diagnosis of Lung Cancer

Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. The CAD (Computer Aided Diagnosis ) of lung CT generally first segment the area of interest (lung) and then analyze the separately obtained area for nodule detection in order to diagnosis the disease. For normal lung, segmentation can be performed by making use of excellent contrast between air and surrounding tissues. However this approach fails when lung is affected by high density pathology. Dense pathologies are present in approximately a fifth of clinical scans, and for computer analysis such as detection and quantification of abnormal areas it is vital that the entire and perfectly lung part of the image is provided and no part, as present in the original image be eradicated. In this paper we have proposed a lung segmentation technique which accurately segment the lung parenchyma from lung CT Scan images. The algorithm was tested against the 25 datasets of different patients received from Ackron Univeristy, USA and AGA Khan Medical University, Karachi, Pakistan.

Mathematical Model of Dengue Disease with the Incubation Period of Virus

Dengue virus is transmitted from person to person through the biting of infected Aedes Aegypti mosquitoes. DEN-1, DEN-2, DEN-3 and DEN-4 are four serotypes of this virus. Infection with one of these four serotypes apparently produces permanent immunity to it, but only temporary cross immunity to the others. The length of time during incubation of dengue virus in human and mosquito are considered in this study. The dengue patients are classified into infected and infectious classes. The infectious human can transmit dengue virus to susceptible mosquitoes but infected human can not. The transmission model of this disease is formulated. The human population is divided into susceptible, infected, infectious and recovered classes. The mosquito population is separated into susceptible, infected and infectious classes. Only infectious mosquitoes can transmit dengue virus to the susceptible human. We analyze this model by using dynamical analysis method. The threshold condition is discussed to reduce the outbreak of this disease.

Predictions Using Data Mining and Case-based Reasoning: A Case Study for Retinopathy

Diabetes is one of the high prevalence diseases worldwide with increased number of complications, with retinopathy as one of the most common one. This paper describes how data mining and case-based reasoning were integrated to predict retinopathy prevalence among diabetes patients in Malaysia. The knowledge base required was built after literature reviews and interviews with medical experts. A total of 140 diabetes patients- data were used to train the prediction system. A voting mechanism selects the best prediction results from the two techniques used. It has been successfully proven that both data mining and case-based reasoning can be used for retinopathy prediction with an improved accuracy of 85%.

Production of H5N1 Hemagglutinin inTrichoplusia ni Larvae by a Novel Bi-cistronic Baculovirus Expression Vector

Highly pathogenic avian influenza (HPAI) H5N1 viruses have created demand for a cost-effective vaccine to prevent a pandemic of the disease. Here, we report that Trichoplusia ni (T. ni) larvae can act as a cost-effective bioreactor to produce recombinant HA5 (rH5HA) proteins as an potential effective vaccine for chickens. To facilitate the recombinant virus identification, virus titer determination and access the infected larvae, we employed the internal ribosome entry site (IRES) derived from Perina nuda virus (PnV, belongs to insect picorna like Iflavirus genus) to construct a bi-cistronic baculovirus expression vector that can express the rH5HA protein and enhanced green fluorescent protein (EGFP) simultaneously. Western blot analysis revealed that the 70 kDa rH5HA protein and partially cleaved products (40 kDa H5HA1) were generated in T. ni larvae infected with recombinant baculovirus carrying the H5HA gene. These data suggest that the baculovirus-larvae recombinant protein expression system could be a cost-effective platform for H5N1 vaccine production.

Antibacterial Activity of Ethanol Extract from Some Thai Medicinal Plants against Campylobacter Jejuni

In this study, the forty Thai medicinal plants were used to screen the antibacterial activity against Campylobacter jejuni. Crude 95% ethanolic extracts of each plant were prepared. Antibacterial activity was investigated by the disc diffusion assay, and MICs and MBCs were determined by broth microdilution. The results of antibacterial screening showed that five plants have activity against C.jejuni including Adenanthera pavonina L., Moringa oleifera Lam., Annona squamosa L., Hibiscus sabdariffa L. and Eupotorium odortum L. The extraction of A. pavonina L. and A. squamosa L. produced an outstanding against C. jejuni, inhibiting growth at 62.5-125 and 250-500 μg/mL, respectively. The MBCs of two extracts were just 4-fold higher than MICs against C. jejuni, suggesting the extracts are bactericidal against this species. These results indicate that A. pavonina and A. squamosa could potentially be used in modern applications aimed at treatment or prevention of foodborne disease from C. jejuni.

Finding Approximate Tandem Repeats with the Burrows-Wheeler Transform

Approximate tandem repeats in a genomic sequence are two or more contiguous, similar copies of a pattern of nucleotides. They are used in DNA mapping, studying molecular evolution mechanisms, forensic analysis and research in diagnosis of inherited diseases. All their functions are still investigated and not well defined, but increasing biological databases together with tools for identification of these repeats may lead to discovery of their specific role or correlation with particular features. This paper presents a new approach for finding approximate tandem repeats in a given sequence, where the similarity between consecutive repeats is measured using the Hamming distance. It is an enhancement of a method for finding exact tandem repeats in DNA sequences based on the Burrows- Wheeler transform.

The First Prevalence Report of Direct Identification and Differentiation of B. abortus and B. melitensis using Real Time PCR in House Mouse of Iran

Brucellosis is a zoonotic disease; its symptoms and appearances are not exclusive in human and its traditional diagnosis is based on culture, serological methods and conventional PCR. For more sensitive, specific detection and differentiation of Brucella spp., the real time PCR method is recommended. This research has performed to determine the presence and prevalence of Brucella spp. and differentiation of Brucella abortus and Brucella melitensis in house mouse (Mus musculus) in west of Iran. A TaqMan analysis and single-step PCR was carried out in total 326 DNA of Mouse's spleen samples. From the total number of 326 samples, 128 (39.27%) gave positive results for Brucella spp. by conventional PCR, also 65 and 32 out of the 128 specimens were positive for B. melitensis, B. abortus, respectively. These results indicate a high presence of this pathogen in this area and that real time PCR is considerably faster than current standard methods for identification and differentiation of Brucella species. To our knowledge, this study is the first prevalence report of direct identification and differentiation of B. abortus and B. melitensis by real time PCR in mouse tissue samples in Iran.

The Integrated Studies of Infectious Disease Using Mathematical Modeling and Computer Simulation

In this paper we develop and analyze the model for the spread of Leptospirosis by age group in Thailand, between 1997 and 2010 by using mathematical modeling and computer simulation. Leptospirosis is caused by pathogenic spirochetes of the genus Leptospira. It is a zoonotic disease of global importance and an emerging health problem in Thailand. In Thailand, leptospirosis is a reportable disease, the top three age groups are 23.31% in 35-44 years olds group, 22.76% in 25-34 year olds group, 17.60% in 45-54 year olds group from reported leptospirosis between 1997 and 2010, with a peak in 35-44 year olds group. Our paper, the Leptosipirosis transmission by age group in Thailand is studied on the mathematical model. Some analytical and simulation results are presented.

Two States Mapping Based Neural Network Model for Decreasing of Prediction Residual Error

The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Influence of Jerusalem Artichoke Powder on the Nutritional Value of Pastry Products

From year to year, the incidence of different diseases is increasing in humans, and the cause is inadequate intake of dietary fibre, vitamins, and minerals. One of the possibilities to take care of your health preventively is including in the diet products with increased dietary fibre, vitamin, and mineral content.Jerusalem artichoke powder (JAP) made from Jerusalem artichoke (Helianthus tuberosus L) roots is a valuable product. By adding it to pastry goods, we can obtain a fibre-rich food that could be healthier and an excellent alternative to the classical pastry products of this kind.Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Results of experiments showed that addition of Jerusalem artichoke powder has significant impact on all the studied pastry products nutritional value (p

Depression and Anxiety Levels in Armenian Crohn's Disease Patients

The Zung self-depression scale and Beck Anxiety Inventory were used to study the depression and anxiety levels of Armenian Crohn's disease patients, as well as to reveal the relation between emotional status and placebo effect of these patients. Despite of registered high levels of depression and anxiety, the high placebo rate during investigations was described. The importance of use of psychotherapies for optimal outcomes during treatments of Crohn's disease is obvious.

Validation on 3D Surface Roughness Algorithm for Measuring Roughness of Psoriasis Lesion

Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.