Search results for: devic's disease

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Elizabeth Stojanovski

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Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance, and within study variance and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: random-effects, meta-analysis, Bayesian, variation

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: R. Gadea, J. M. Monzó, F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. J. Colom

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There exists a wide array of ailments impacting the structural soundness of the esophageal walls, predominantly linked to digestive issues. Presently, the techniques employed for identifying esophageal tract complications are excessively invasive and discomforting, subjecting patients to prolonged discomfort in order to achieve an accurate diagnosis. This study proposes the creation of a sensor with profound measuring capabilities designed to detect fluids coursing through the esophageal tract. The multi-sensor detection system relies on radiofrequency photospectrometry. During experimentation, individuals representing diverse demographics in terms of gender and age were utilized, positioning the sensors amidst the trachea and diaphragm and assessing measurements in vacuum conditions, water, orange juice, and saline solutions. The findings garnered enabled the identification of various liquid mediums within the esophagus, segregating them based on their ionic composition.

Keywords: radiofrequency spectrophotometry, medical device, gastroesophageal disease, photonics

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Authors: Neelam Singha

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The present work intends to analyze the system dynamics of Hashimoto’s thyroiditis with the assistance of fractional calculus. Hashimoto’s thyroiditis or chronic lymphocytic thyroiditis is an autoimmune disorder in which the immune system attacks the thyroid gland, which gradually results in interrupting the normal thyroid operation. Consequently, the feedback control of the system gets disrupted due to thyroid follicle cell lysis. And, the patient perceives life-threatening clinical conditions like goiter, hyperactivity, euthyroidism, hyperthyroidism, etc. In this work, we aim to obtain the approximate solution to the posed fractional-order problem describing Hashimoto’s thyroiditis. We employ the Adomian decomposition method to solve the system of fractional-order differential equations, and the solutions obtained shall be useful to provide information about the effect of medical care. The numerical technique is executed in an organized manner to furnish the associated details of the progression of the disease and to visualize it graphically with suitable plots.

Keywords: adomian decomposition method, fractional derivatives, Hashimoto's thyroiditis, mathematical modeling

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Authors: Jisun Jun, Eun Ko, Sooim Shin, Kitae Kim, Moonsung Choi

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Diabetes is a metabolic disease characterized by hyperglycemia, insulin resistant, mitochondrial dysfunction. Diabetes is associated with the development of diabetic retinopathy resulting in worsening vision and eventual blindness. In this study, eyes were enucleated from glucose-immersed zebrafish which is a good animal model to generate diabetes, and then mitochondria were isolated to evaluate activities of mitochondrial electron transfer complexes. Surprisingly, the amount of isolated mitochondria was increased in eyes from glucose-immersed zebrafish compared to those from non-glucose-immerged zebrafish. Spectrophotometric analysis for measuring activities of mitochondrial complex I, II, III, and IV revealed that mitochondria functions was even enhanced in eyes from glucose-immersed zebrafish. These results indicated that 3 days or 7 days glucose-immersion on zebrafish to induce diabetes might contribute metabolic compensatory mechanism to restore their mitochondrial homeostasis on the early stage of diabetes in eyes.

Keywords: diabetes, glucose immersion, mitochondrial complexes, zebrafish

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Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

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Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover, this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

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Authors: Liang Zhou, Xiaojing Zhu, Yin Lu

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Danshen can induce the angiogenesis in advanced ischemic heart disease while inhibiting the angiogenesis in cancer. Additionally, Danshen mainly contains two groups of ingredients: the hydrophilic phenolic acids (danshensu, caffeic acid and salvianolic acid B), and the lipophilic tanshinones (dihydrotanshinone I, tanshinone II A, and cryptotanshinone). The lipophilic tanshinones reduced the VEGF- and bFGF-induced proliferation of HUVECs in dose-dependent manner, but cannot perform in others. Conversely, caffeic acid and salvianolic acid B had the opposite effect. Danshensu inhibited the VEGF- and bFGF-induced migration of HUVECs, and others were not. Most of them interrupted the forming capillary-like structures of HUVECs, except the danshensu and caffeic acid. Oppositely, caffeic acid enhanced the ability of forming capillary-like structures of HUVECs. Ultimately, the lipophilic tanshinones, danshensu and salvianolic acid B inhibited the angiogenesis, whereas the caffeic acid induced the angiogenesis. These data provide useful information for the classification of ingredients of Danshen for angiogenesis.

Keywords: angiogenesis, Danshen, HUVECs, ingredients

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

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This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Ifeyinwa Victor-Uadiale, Georgina Pearson, Sophie Witter, D. Reidpath

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Introduction: Smoking, alcohol misuse, unhealthy diet, and physical inactivity are the primary drivers of noncommunicable diseases (NCD), including cardiovascular diseases, cancers, respiratory diseases, and diabetes, worldwide. Collectively, these diseases are the leading cause of all global deaths, most of which are premature, affecting people between 30 and 70 years. Empirical evidence suggests that these risk behaviors can be modified by community-based interventions (CBI). However, there is little insight into the mechanisms and contextual factors of successful community interventions that impact risk behaviours for chronic diseases. This study examined “Under what circumstances, for whom, and how, do community-based interventions modify smoking, alcohol use, unhealthy diet, and physical inactivity among adults”. Adopting the Capability (C), Opportunity (O), Motivation (M), Behavior (B) (COM-B) framework for behaviour change, it sought to: (1) identify the mechanisms through which CBIs could reduce tobacco use and alcohol consumption and increase physical activity and the consumption of healthy diets and (2) examine the contextual factors that trigger the impact of these mechanisms on these risk behaviours among adults. Methods: Pawson’s realist review method was used to examine the literature. Empirical evidence and theoretical understanding were combined to develop a realist program theory that explains how CBIs influence NCD risk behaviours. Documents published between 2002 and 2020 were systematically searched in five electronic databases (CINAHL, Cochrane Library, Medline, ProQuest Central, and PsycINFO). They were included if they reported on community-based interventions aimed at cardiovascular diseases, cancers, respiratory diseases, and diabetes in a global context; and had an outcome targeted at smoking, alcohol, physical activity, and diet. Findings: Twenty-nine scientific documents were retrieved and included in the review. Over half of them (n = 18; 62%) focused on three of the four risk behaviours investigated in this review. The review identified four mechanisms: capability, opportunity, motivation, and social support that are likely to change the dietary and physical activity behaviours in adults given certain contexts. There were weak explanations of how the identified mechanisms could likely change smoking and alcohol consumption habits. In addition, eight contextual factors that may affect how these mechanisms impact physical activity and dietary behaviours were identified: suitability to work and family obligations, risk status awareness, socioeconomic status, literacy level, perceived need, availability and access to resources, culture, and group format. Conclusion: The findings suggest that CBIs are likely to improve the physical activity and dietary habits of adults if the intervention function seeks to educate, incentivize, change the environment, and model the right behaviours. The review applies and advances theory, realist research, and the design and implementation of community-based interventions for NCD prevention.

Keywords: community-based interventions, noncommunicable disease, realist program theory, risk behaviors

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Authors: Saimir Heta, Ilma Robo, Nevila Alliu, Tea Meta

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Background: Plasma levels of inflammatory markers are the expression of the infectious wastes of existing periodontitis, as well as of existing inflammation everywhere in the body. Materials and Methods: The study consists of the clinical part of the measurement of inflammatory markers of 23 patients diagnosed with chronic periodontitis and the recording of parental periodontal parameters of patient periodontal status: hemorrhage index and probe values, before and 7-10 days after non-surgical periodontal treatment. Results: The level of fibrinogen drops according to the categorization of disease progression, active and passive, with the biggest % (18%-30%) at the fluctuation 10-20 mg/d. Fluctuations in fibrinogen level according to the age of patients in the range 0-10 mg/dL under 40 years and over 40 years was 13%-26%, in the range 10-20 mg/dL was 26%-22%, in the 20-40 mg/dL was 9%-4%. Conclusions: Non-surgical periodontal treatment significantly reduces the level of non-inflammatory markers in the blood. Oral health significantly reduces the potential source for periodontal bacteria, with the potential of promoting thromboembolism, through interaction between thrombocytes.

Keywords: chronic periodontitis, atherosclerosis, risk factor, inflammatory markers

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

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Authors: Nsubuga Bright Titus

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The resource curse is an unavoidable phenomenon among oil producing states in Africa. There is no oil production currently in Uganda although exploration projections set 2020 as the year of initial production. But as the exploration proceeds and Production Sharing Agreements (PSA) are negotiated, so does the anticipation for oil revenues. The Indigenous people of Bunyoro are claiming the right to their indigenous lands through the African Commission on Human and People’s Rights (ACHPR) of the African Union. They urge the commission to investigate the government of Uganda on violations of their human rights. In this paper, oil as a resource curse is examined through the Dutch disease. Regional and global entanglements, as well as the contestation between the indigenous Bunyoro group and the oil industry in Uganda is explored. The paper also demonstrates that oil as a local possibility and national reality has propelled anxiety about oil revenues among various, local actors, State actors, regional and global actors.

Keywords: Entanglements, Extractive resources, Framing, web of relations

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Authors: Md Shohidul Islam, Jongmyon Kim, Ui-pil Chong

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Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.

Keywords: medical image watermarking, e-health system, error correction, Hamming code, GPU

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Authors: Noha Mohamed Abdelhafez Dahy, Azza Abd El-Aziz, Eman Ahmed, Marwa El-Sayed

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Osteoporosis is a metabolic bone disease characterized by low bone mass, deterioration of bone tissue, and disruption of bone microarchitecture, which leads to compromised bone strength and an increased risk of fracture, commonly it occurs in women 10-15 years after menopause, the mean age of menopause is 51 years. Menopause is natural physiological changes primary because of decline of ovaries function with age which leads to decrease of estrogen hormone production which is the main hormone for bone continuous remodeling for bone density maintenance. Exercise increase stimulation of bone growth to keep bone mass by the effect of the mechanical stimulation, antigravity loading and stress exerted on musculoskeletal muscles. Purpose: This study aimed to determine the effect of aerobic exercise on estrogen hormone and bone mineral density (BMD) in osteoporotic women and the correlation between the estrogen and BMD.

Keywords: Osteoporosis, Postmenopause, Aerobic exercise, DEXA, Serum Estrogen

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Authors: Leo Nnamdi Ozurumba-Dwight

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Messenger ribooxynucleic acid (mRNA) molecules are compositional, protein-based. These proteins, encoding mRNA molecules (which collectively connote the transcriptome), when analyzed by RNA sequencing (RNAseq), unveils the nature of gene expression in the RNA. The obtained gene expression provides clues of cellular traits and their dynamics in presentations. These can be studied in relation to function and responses. RNAseq is a practical concept in Genomics as it enables detection and quantitative analysis of mRNA molecules. Single cell and spatial transcriptomics both present varying avenues for expositions in genomic characteristics of single cells and pooled cells in disease conditions such as cancer, auto-immune diseases, hematopoietic based diseases, among others, from investigated biological tissue samples. Single cell transcriptomics helps conduct a direct assessment of each building unit of tissues (the cell) during diagnosis and molecular gene expressional studies. A typical technique to achieve this is through the use of a single-cell RNA sequencer (scRNAseq), which helps in conducting high throughput genomic expressional studies. However, this technique generates expressional gene data for several cells which lack presentations on the cells’ positional coordinates within the tissue. As science is developmental, the use of complimentary pre-established tissue reference maps using molecular and bioinformatics techniques has innovatively sprung-forth and is now used to resolve this set back to produce both levels of data in one shot of scRNAseq analysis. This is an emerging conceptual approach in methodology for integrative and progressively dependable transcriptomics analysis. This can support in-situ fashioned analysis for better understanding of tissue functional organization, unveil new biomarkers for early-stage detection of diseases, biomarkers for therapeutic targets in drug development, and exposit nature of cell-to-cell interactions. Also, these are vital genomic signatures and characterizations of clinical applications. Over the past decades, RNAseq has generated a wide array of information that is igniting bespoke breakthroughs and innovations in Biomedicine. On the other side, spatial transcriptomics is tissue level based and utilized to study biological specimens having heterogeneous features. It exposits the gross identity of investigated mammalian tissues, which can then be used to study cell differentiation, track cell line trajectory patterns and behavior, and regulatory homeostasis in disease states. Also, it requires referenced positional analysis to make up of genomic signatures that will be sassed from the single cells in the tissue sample. Given these two presented approaches to RNA transcriptomics study in varying quantities of cell lines, with avenues for appropriate resolutions, both approaches have made the study of gene expression from mRNA molecules interesting, progressive, developmental, and helping to tackle health challenges head-on.

Keywords: transcriptomics, RNA sequencing, single cell, spatial, gene expression.

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Authors: B. Prashantha, S. Anish

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The aim of the present study is to computationally evaluate the hemodynamic factors which affect the formation of atherosclerosis and plaque rupture in the human artery. An increase of atherosclerosis disease in the artery causes geometry changes, which results in hemodynamic changes such as flow separation, reattachment, and adhesion of new cells (chemotactic) in the artery. Hence, geometry plays an important role in the determining the nature of hemodynamic patterns. Influence of stenosis in the non-bifurcating artery, under pulsatile flow condition, has been studied on an idealized geometry. Analysis of flow through symmetric and asymmetric stenosis in the artery revealed the significance of oscillating shear index (OSI), flow separation, low WSS zones and secondary flow patterns on plaque formation. The observed characteristic of flow in the post-stenotic region highlight the importance of plaque eccentricity on the formation of secondary stenosis on the arterial wall.

Keywords: atherosclerotic plaque, oscillatory shear index, stenosis nature, wall shear stress

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Authors: Mary Ghobrial, Sahar Wefky

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Marine macroalgae have proven to be rich source of bioactive compounds with biomedical potential, not only for human but also for veterinary medicine. Emergence of microbial disease in aquaculture industries implies serious loses. Usage of commercial antibiotics for fish disease treatment produces undesirable side effects. Marine organisms are a rich source of structurally novel biologically active metabolites. Competition for space and nutrients led to the evolution of antimicrobial defense strategies in the aquatic environment. The interest in marine organisms as a potential and promising source of pharmaceutical agents has increased in the last years. Many bioactive and pharmacologically active substances have been isolated from microalgae. Compounds with antibacterial, antifungal and antiviral activities have been also detected in green, brown and red algae. Selected species of marine benthic algae belonging to the Phaeophyta and Rhodophyta, collected from different coastal areas of Alexandria (Egypt), were investigated for their antibacterial and antifungal, activities. Macroalgae samples were collected during low tide from the Alexandria Mediterranean coast. Samples were air dried under shade at room temperature. The dry algae were ground, using electric mixer grinder. They were soaked in 10 ml of each of the solvents acetone, ethanol, methanol and hexane. Antimicrobial activity was evaluated using well-cut diffusion technique In vitro screening of organic solvent extracts from the marine macroalgae Laurencia pinnatifida, Pterocladia capillaceae, Stepopodium zonale, Halopteris scoparia and Sargassum hystrix, showed specific activity in inhibiting the growth of five virulent strains of bacteria pathogenic to fish Pseudomonas fluorescens, Aeromonas hydrophila, Vibrio anguillarum, V. tandara, Escherichia coli and two fungi Aspergillus flavus and A. niger. Results showed that, acetone and ethanol extracts of all test macroalgae exhibited antibacterial activity, while acetone extract of the brown Sargassum hystrix displayed the highest antifungal activity. The extracts of seaweeds inhibited bacteria more strongly than fungi and species of the Rhodophyta showed the greatest activity against the bacteria rather than fungi tested. The gas liquid chromatography coupled with mass spectrometry detection technique allows good qualitative and quantitative analysis of the fractionated extracts with high sensitivity to the smaller amounts of components. Results indicated that, the main common component in the acetone extracts of L. pinnatifida and P. capillacea is 4-hydroxy-4-methyl2-pentanone representing 64.38 and 58.60%. Thus, the extracts derived from the red macroalgae were more efficient than those obtained from the brown macroalgae in combating bacterial pathogens rather than pathogenic fungi. The most preferred species over all was the red Laurencia pinnatifida. In conclusion, the present study provides the potential of red and brown macroalgae extracts for development of anti-pathogenic agents for use in fish aquaculture.

Keywords: bacteria, fungi, extracts, solvents

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Authors: Boma Nellie S, Nambiar Ritu, K. Kanchanmala, T. Rashida, Israell Imelda, Moul Khusnud, Michael Marina

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Gestational diabetes (GDM) imparts an increased life long risk of developing Type 2 Diabetes Mellitus (T2DM) and cardiovascular disease in women. Once diagnosed with GDM women have up to 74% increased cumulative risk developing T2DM in 10-15 years. Identifying women at increased risk of developing T2DM and offering them pharmacological and lifestyle management interventions will delay or eliminate the development of diabetes in this population. While ADA recommends that all gestational diabetics be offered postnatal screening, worldwide the screening rates from 35-75% and Al Rahba Hospital with a robust universal antenatal screening program for GDM was at a dismal 9% in 2011. A multidisciplinary team was put together involving OB/Gyn Physicians, Midwives, Nurses (ward and OPD) Diabetic Educators, Dietitians, Medical Records, Laboratory & IT with the implementation of multiple strategies to increase the uptake of postpartum screening of the gestational diabetic.

Keywords: GDM, postnatal screening, preventing type 2 diabetes, lifestyle management

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Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa, Annabella Habinka Ejiri

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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to a lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. We aimed at; i) increase awareness and understanding of teledermatology among prison health workers and ii) improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons. Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prison staff with AD. We conducted five days of training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient-Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: We have the very first iconographic atlas of the main dermatoses in pigmented African skin. We increased; i) the proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80%; ii) the proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year; iii) increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year and iv)Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one year. Our study contributes to the use, evaluation, and verification of the use of teledermatology to increase access to specialist dermatology services to the most hard to reach areas and vulnerable populations such as that of prisoners.

Keywords: teledermatology, prisoners, reaching, un-reachable

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Authors: Cynthia Sau Chun Yip, Richard Fielding

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High meat and especially red meat intakes are significantly and positively associated with a multiple burden of diseases and also high greenhouse gas (GHG) emissions. This study investigated population meat intake patterns in Hong Kong. It quantified the burden of disease and GHG emission outcomes by modeling to adjust Hong Kong population meat intakes to recommended healthy levels. It compared age- and sex-specific population meat, fruit and vegetable intakes obtained from a population survey among adults aged 20 years and over in Hong Kong in 2005-2007, against intake recommendations suggested in the Modelling System to Inform the Revision of the Australian Guide to Healthy Eating (AGHE-2011-MS) technical document. This study found that meat and meat alternatives, especially red meat intakes among Hong Kong males aged 20+ years and over are significantly higher than recommended. Red meat intakes among females aged 50-69 years and other meat and alternatives intakes among aged 20-59 years are also higher than recommended. Taking the 2005-07 age- and sex-specific population meat intake as baselines, three counterfactual scenarios of adjusting Hong Kong adult population meat intakes to AGHE-2011-MS and Pre-2011 AGHE recommendations by the year 2030 were established. Consequent energy intake gaps were substituted with additional legume, fruit and vegetable intakes. To quantify the consequent GHG emission outcomes associated with Hong Kong meat intakes, Cradle-to-ready-to-eat lifecycle assessment emission outcome modelling was used. Comparative risk assessment of burden of disease model was used to quantify the health outcomes. This study found adjusting meat intakes to recommended levels could reduce Hong Kong GHG emission by 17%-44% when compared against baseline meat intake emissions, and prevent 2,519 to 7,012 premature deaths in males and 53 to 1,342 in females, as well as multiple burden of diseases when compared to the baseline meat intake scenario. Comparing lump sum meat intake reduction and outcome measures across the entire population, and using emission factors, and relative risks from individual studies in previous co-benefit studies, this study used age- and sex-specific input and output measures, emission factors and relative risks obtained from high quality meta-analysis and meta-review respectively, and has taken government dietary recommendations into account. Hence evaluations in this study are of better quality and more reflective of real life practices. Further to previous co-benefit studies, this study pinpointed age- and sex-specific population and meat-type-specific intervention points and leverages. When compared with similar studies in Australia, this study also showed that intervention points and leverages among populations in different geographic and cultural background could be different, and that globalization also globalizes meat consumption emission effects. More regional and cultural specific evaluations are recommended to promote more sustainable meat consumption and enhance global food security.

Keywords: burden of diseases, greenhouse gas emissions, Hong Kong diet, sustainable meat consumption

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Authors: Okolie Pius Ifeanyi, Emerenini Emilymary Chima

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Aims: The study investigated the diversity and identities of Lactic Acid Bacteria (LAB) isolated from different fresh fruits using Molecular Nested PCR analysis and the efficacy of cell free supernatants from Lactic Acid Bacteria (LAB) isolated from fresh fruits for in vitro control of some tomato pathogens. Study Design: Nested PCR approach was used in this study employing universal 16S rRNA gene primers in the first round PCR and LAB specific Primers in the second round PCR with the view of generating specific Nested PCR products for the LAB diversity present in the samples. The inhibitory potentials of supernatant obtained from LAB isolates of fruits origin that were molecularly characterized were investigated against some tomato phytopathogens using agar-well method with the view to develop biological agents for some tomato disease causing organisms. Methodology: Gram positive, catalase negative strains of LAB were isolated from fresh fruits on Man Rogosa and Sharpe agar (Lab M) using streaking method. Isolates obtained were molecularly characterized by means of genomic DNA extraction kit (Norgen Biotek, Canada) method. Standard methods were used for Nested Polymerase Chain Reaction (PCR) amplification targeting the 16S rRNA gene using universal 16S rRNA gene and LAB specific primers, agarose gel electrophoresis, purification and sequencing of generated Nested PCR products (Macrogen Inc., USA). The partial sequences obtained were identified by blasting in the non-redundant nucleotide database of National Center for Biotechnology Information (NCBI). The antimicrobial activities of characterized LAB against some tomato phytopathogenic bacteria which include (Xanthomonas campestries, Erwinia caratovora, and Pseudomonas syringae) were obtained by using the agar well diffusion method. Results: The partial sequences obtained were deposited in the database of National Centre for Biotechnology Information (NCBI). Isolates were identified based upon the sequences as Weissella cibaria (4, 18.18%), Weissella confusa (3, 13.64%), Leuconostoc paramensenteroides (1, 4.55%), Lactobacillus plantarum (8, 36.36%), Lactobacillus paraplantarum (1, 4.55%) and Lactobacillus pentosus (1, 4.55%). The cell free supernatants of LAB from fresh fruits origin (Weissella cibaria, Weissella confusa, Leuconostoc paramensenteroides, Lactobacillus plantarum, Lactobacillus paraplantarum and Lactobacillus pentosus) can inhibits these bacteria by creating clear zones of inhibition around the wells containing cell free supernatants of the above mentioned strains of lactic acid bacteria. Conclusion: This study shows that potentially LAB can be quickly characterized by molecular methods to specie level by nested PCR analysis of the bacteria isolate genomic DNA using universal 16S rRNA primers and LAB specific primer. Tomato disease causing organisms can be most likely biologically controlled by using extracts from LAB. This finding will reduce the potential hazard from the use of chemical herbicides on plant.

Keywords: nested pcr, molecular characterization, 16s rRNA gene, lactic acid bacteria

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Authors: Berengere Vire, Nicolas Salvetat, Yoann Lannay, Guillaume Marcellin, Siem Van Der Laan, Franck Molina, Dinah Weissmann

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Predicting suicidal behaviors is one of the most complex challenges of daily psychiatric practices. Today, suicide risk prediction using biological tools is not validated and is only based on subjective clinical reports of the at-risk individual. Therefore, there is a great need to identify biomarkers that would allow early identification of individuals at risk of suicide. Alterations of adenosine-to-inosine (A-to-I) RNA editing of neurotransmitter receptors and other proteins have been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behavior. RNA editing is a co- or post-transcriptional process leading to a site-specific alteration in RNA sequences. It plays an important role in the epi transcriptomic regulation of RNA metabolism. On postmortem human brain tissue (prefrontal cortex) of depressed suicide victims, Alcediag found specific alterations of RNA editing activity on the mRNA coding for the serotonin 2C receptor (5-HT2cR). Additionally, an increase in expression levels of ADARs, the RNA editing enzymes, and modifications of RNA editing profiles of prime targets, such as phosphodiesterase 8A (PDE8A) mRNA, have also been observed. Interestingly, the PDE8A gene is located on chromosome 15q25.3, a genomic region that has recurrently been associated with the early-onset major depressive disorder (MDD). In the current study, we examined whether modifications in RNA editing profile of prime targets allow identifying disease-relevant blood biomarkers and evaluating suicide risk in patients. To address this question, we performed a clinical study to identify an RNA editing signature in blood of depressed patients with and without the history of suicide attempts. Patient’s samples were drawn in PAXgene tubes and analyzed on Alcediag’s proprietary RNA editing platform using next generation sequencing technology. In addition, gene expression analysis by quantitative PCR was performed. We generated a multivariate algorithm comprising various selected biomarkers to detect patients with a high risk to attempt suicide. We evaluated the diagnostic performance using the relative proportion of PDE8A mRNA editing at different sites and/or isoforms as well as the expression of PDE8A and the ADARs. The significance of these biomarkers for suicidality was evaluated using the area under the receiver-operating characteristic curve (AUC). The generated algorithm comprising the biomarkers was found to have strong diagnostic performances with high specificity and sensitivity. In conclusion, we developed tools to measure disease-specific biomarkers in blood samples of patients for identifying individuals at the greatest risk for future suicide attempts. This technology not only fosters patient management but is also suitable to predict the risk of drug-induced psychiatric side effects such as iatrogenic increase of suicidal ideas/behaviors.

Keywords: blood biomarker, next-generation-sequencing, RNA editing, suicide

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Authors: Bayan Almofty, Yuto Yamaki, Tadamasa Terai, Sadahito Uto

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Culture techniques of skeletal muscle cells are advanced in the field of regenerative medicine and applied research of cultured muscle. As applied research of cultured muscle, myopathy (muscles disease) treatment is expected and development bio of actuator is also expected in biomedical engineering. Grayanotoxins (GTXs) is known as neurotoxins that enhance the permeability of cell membrane for Na ions. Grayanotoxins are extracted from a famous Pieris japonica and Ericaceae as well as a phytotoxin. In this study, we investigated the effect of GTXs on muscle cells (C2C12) contraction and membrane potential. Contraction of myotubes is induced by applied external electrical stimulation. Contraction and membrane potential change of skeletal muscle cells are induced by injection of current. We, therefore, concluded that effect of Grayanotoxins on contraction and membrane potential of C2C12 relate to acute toxicity of GTXs.

Keywords: skeletal muscle cells C2C12, grayanotoxins, contraction, membrane potential, acute toxicity, pytotoxin, motubes

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Authors: Bernice Jeanne Lottering, Yi-Wen Lin

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Introduction: Chronic pain has a definitive lack of objective parameters in the measurement and treatment efficacy of diseases such as Fibromyalgia (FM). Persistent widespread pain and generalized tenderness are the characteristic symptoms affecting a large majority of the global population, particularly females. This disease has indicated a refractory tendency to conventional treatment ventures, largely resultant from a lack of etiological and pathogenic understanding of the disease development. Emerging evidence indicates that the central nervous system (CNS) plays a critical role in the amplification of pain signals and the neurotransmitters associated therewith. Various stimuli have been found to activate the channels existent on nociceptor terminals, thereby actuating nociceptive impulses along the pain pathways. The transient receptor potential vanalloid 1 (TRPV1) channel functions as a molecular integrator for numerous sensory inputs, such as nociception, and was explored in the current study. Current intervention approaches face a multitude challenges, ranging from effective therapeutic interventions to the limitation of pathognomonic criteria resultant from incomplete understanding and partial evidence on the mechanisms of action of FM. It remains unclear whether electroacupuncture (EA) plays an integral role in the functioning of the TRPV1 pathway, and whether or not it can reduce the chronic pain induced by FM. Aims: The aim of this study was to explore the mechanisms underlying the activation and modulation of the TRPV1 channel pathway in a cold stress model of FM applied to a murine model. Furthermore, the effect of EA in the treatment of mechanical and thermal pain, as expressed in FM was also to be investigated. Methods: 18 C57BL/6 wild type and 6 TRPV1 knockout (KO) mice, aged 8-12 weeks, were exposed to an intermittent cold stress-induced fibromyalgia-like pain model, with or without EA treatment at ZusanLi ST36 (2Hz/20min) on day 3 to 5. Von Frey and Hargreaves behaviour tests were implemented in order to analyze the mechanical and thermal pain thresholds on day 0, 3 and 5 in control group (C), FM group (FM), FM mice with EA treated group (FM + EA) and FM in KO group. Results: An increase in mechanical and thermal hyperalgesia was observed in the FM, EA and KO groups when compared to the control group. This initial increase was reduced in the EA group, which directs focus at the treatment efficacy of EA in nociceptive sensitization, and the analgesic effect EA has attenuating FM associated pain. Discussion: An increase in the nociceptive sensitization was observed through higher withdrawal thresholds in the von Frey mechanical test and the Hargreaves thermal test. TRPV1 function in mice has been scientifically associated with these nociceptive conduits, and the increased behaviour test results suggest that TRPV1 upregulation is central to the FM induced hyperalgesia. This data was supported by the decrease in sensitivity observed in results of the TRPV1 KO group. Moreover, the treatment of EA showed a decrease in this FM induced nociceptive sensitization, suggesting TRPV1 upregulation and overexpression can be attenuated by EA at bilateral ST36. This evidence compellingly implies that the analgesic effect of EA is associated with TRPV1 downregulation.

Keywords: fibromyalgia, electroacupuncture, TRPV1, nociception

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Authors: Gagandeep Singh Grover, Vini Mahajan, Bhagmal, Priti Thaware, Jaspreet Takkar

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Dengue is a mosquito-borne viral disease endemic in many countries in the tropics and sub-tropics. The state of Punjab in India shows cyclical and seasonal variation in dengue cases. The Case Fatality Rate of Dengue has ranged from 0.6 to 1.0 in the past years. The department has initiated a review of the cases that have died due to dengue in order to know the exact cause of the death in a case of dengue. The study has been undertaken to know the other associated co-morbidities and factors causing death in a case of dengue. The study used the predesigned proforma on which the records (medical and Lab) were recorded and reviewed by the expert committee of the doctors. This study has revealed that cases of dengue having co-morbidities have a longer stay in the hospital. Fluid overload and co-morbidities have been found as major factors leading to death, however, in a confirmed case of dengue hepatorenal shutdown was found to be a major cause of mortality. The data obtained will help in sensitizing the treating physicians in order to decrease the mortality due to dengue in future.

Keywords: dengue, death, morbidities, DHF, DSS

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Authors: Nitin Dwivedi, Jigna Shah

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Brain tumor is metastatic neoplasm of central nervous system, in most of cases it is life threatening disease with low survival rate. Despite of enormous efforts in the development of therapeutics and diagnostic tools, the treatment of brain tumors and gliomas remain a considerable challenge in the area of neuro-oncology. The most reason behind of this the presence of physiological barriers including blood brain barrier and blood brain tumor barrier, lead to insufficient reach ability of therapeutic agents at the site of tumor, result of inadequate destruction of gliomas. So there is an indeed need empowerment of brain tumor imaging for better characterization and delineation of tumors, visualization of malignant tissue during surgery, and tracking of response to chemotherapy and radiotherapy. Multifunctional different generations of dendrimer offer an improved effort for potentiate drug delivery at the site of brain tumor and gliomas. So this article emphasizes the innovative dendrimer approaches in tumor targeting, tumor imaging and delivery of therapeutic agent.

Keywords: blood brain barrier, dendrimer, gliomas, nanotechnology

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

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