Search results for: end-stage renal disease (ESRD)

Authors: Maryam Nazari

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COVID-19 is a respiratory disease triggered by the novel coronavirus, SARS-CoV-2, that has reached pandemic status today. Acute inflammation and immune cells infiltration into lung injuries result in multi-organ failure. The presence of other non-communicable diseases (NCDs) with systemic inflammation derived from COVID-19 may exacerbate the patient's situation and increase the risk for adverse effects and mortality. This pandemic is a novel situation and the scientific community at this time is looking for vaccines or drugs to treat the pathology. One of the biggest challenges is focused on reducing inflammation without compromising the correct immune response of the patient. In this regard, addressing the nutritional factors should not be overlooked not only as a matter of avoiding the presence of NCDs with severe infections but also as an adjunctive way to modulate the inflammatory status of the patients. Despite the pivotal role of nutrition in modifying immune response, due to the novelty of the COVID-19 disease, information about the effects of specific dietary agents is limited in this area. From the macronutrients point of view, protein deficiency (quantity or quality) has negative effects on the number of functional immunoglobulins and gut-associated lymphoid tissue (GALT). High biological value proteins or some amino acids like arginine and glutamine are well known for their ability to augment the immune system. Among lipids, fish oil has the ability to inactivate enveloped viruses, suppress pro-inflammatory prostaglandin production and block platelet-activating factors and their receptors. In addition, protectin D1, which is an Omega-3 PUFAs derivation, is a novel antiviral drug. So it seems that these fatty acids can reduce the severity and/or improve recovery of patients with COVID-19. Carbohydrates with lower glycemic index and fibers are associated with lower levels of inflammatory cytokines (CRP, TNF-α, and IL-6). Short-Chain Fatty acids not only exert a direct anti-inflammatory effect but also provide appropriate gut microbial, which is important in gastrointestinal issues related to COVID-19. From the micronutrients point of view, Vitamins A, C, D, E, iron, magnesium, zinc, selenium and copper play a vital role in the maintenance of immune function. Inadequate status in these nutrients may result in decreased resistance against COVID-19 infection. There are specific bioactive compounds in the diet that interact with the ACE2 receptor, which is the gateway for SARS and SARS-CoV-2, and thus controls the viral infection. Regarding this, the potential benefits of probiotics, resveratrol (a polyphenol found in grape), oleoylethanolamide (derived from oleic acid), and natural peroxisome proliferator-activated receptor γ agonists in foodstuffs (like curcumin, pomegranate, hot pepper) are suggested. Yet, it should be pointed out that most of these results have been reported in animal models and further human studies are needed to be verified.

Keywords: Covid-19, inflammation, nutrition, dietary agents

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Authors: Nabin Prasad Joshi, Samiksha Neupane

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Since its emergence in December 2019, Corona Virus disease has impacted several countries, affecting many people. The first cases were recorded in Wuhan, China, between December 2019 and January 2020. Italy is one of the affected countries in Europe. The relations between India and Nepal have reverted to the pre-pandemic period as both countries have open borders. The study focused on the overall psychosocial impact among covid-19 survivors in their life what are the changes they are facing after covid also how are their relations with friends and relatives after they have covid in different municipalities of Kathmandu valley, where people from different regions are living in rent and have their own houses. Support from friends and family during a pandemic can prevent it if it is strong enough. Nonetheless, there were risk factors for psychosocial damage, including a lack of or insufficient family and social support, psychiatric assistance, and inadequate insurance or compensation. Poorer mental health outcomes were inversely correlated with social rejection or isolation.

Keywords: stress, anxiety, depression, Kathmandu

Procedia PDF Downloads 103

Authors: Paul Bigala, Samuel Oladipo, Steven Adebowale

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This study examines factors influencing knowledge of HIV/AIDS Prevention Practices and Transmission (KHAPPT) among young undergraduate students (15-24 years). Knowledge composite index was computed for 820 randomly selected students. Chi-square, ANOVA, and multinomial logistic regression were used for the analyses (α=.05). The overall mean knowledge score was 16.5±3.4 out of a possible score of 28. About 83% of the students have undergone HIV test, 21.0% have high KHAPPT, 18% said there is cure for the disease, 23% believed that asking for condom is embarrassing and 11.7% said it is safe to share unsterilized sharp objects with friends or family members. The likelihood of high KHAPPT was higher among students who have had HIV test (OR=3.314; C.I=1.787-6.145, p<0.001) even when other variables were used as control. The identified predictors of high KHAPPT were; ever had HIV test, faculty, and ever used any HIV/AIDS prevention services. North-West University Mafikeng should intensify efforts on the HIV/AIDS awareness program on the campus.

Keywords: HIV/AIDS knowledge, undergraduate students, HIV testing, Mafikeng

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Authors: Shirin Jalili, Ramin Ghasemi Shayan

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Coarctation of the aorta (CoA) may be a common (CHD), which is the seventh most common sort of CHD. Still, this is often likely a think little off since the determination may be deferred, indeed within the pediatric populace. The choice for surgical repair incorporates resection of the contracted section with end-to-end or end-to-side anastomosis, subclavian fold aortoplasty, resection, and join the intervention, or prosthetic fix aortoplasty. Drastically expanded end-to-end repair or switched subclavian fold aortoplasty can be utilized when the coarctation expands to the distal arch. Swell angioplasty can be a palliative choice sometime recently the conclusive redress. Its objective is to stabilize high-risk patients that cannot be submitted to quick surgical intercession, such as untimely newborns. For disconnected and discrete coarctations, it can, as a rule, be drawn nearer and repaired by means of cleared out thoracotomy, extraction of the infected aorta (coarctectomy), and remaking, ordinarily by amplified end-to-end anastomosis. In this article, we need to supply a diagram of current proposals and strategies utilized to picture coarctations of the aorta.

Keywords: coarctation of the aorta, congenital heart disease, strategies, surgical repair

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi

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Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.

Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation

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Authors: Arun Karoriya, Mrinal Agrawal

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Health is one of the basic requirements of human being. And today India is facing a major degradation of health at every age group. As society evolves and flourishes, there are different types of rules, norms, standards which are required to control the conduct of the human being for its well-being and growth. Right to health is one of those aspects that can be counted, discovered and examined under the purview of constitutional provisions of India. The condition of health is at downfall despite the fact that there are several policies framed by the government. There is an urgent call for rigid public health laws to ensure safe and disease free society. The effectiveness of health law has to be examined by keeping in mind that it is hampering growth and economy and society establishment. Health in any society is a main social aspect as it plays a major role for economic development. The multidimensional approach to determine it is by discussing i) rational selection and use of medicines ii) sustainable adequate financing iii) affordable prices iv)reliable health and supply systems.

Keywords: degradation, flourish, multidimensional, policies

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Authors: Hanan M. Hassan, Laila Abouzeid, Lamya H. Al-Wahaibi, George S. G. Shehatou, Ali A. El-Emam

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Cancer is a major public health problem and the second leading cause of death worldwide. In 2020, cancer diagnosis and treatment have been negatively affected by the coronavirus 2019 (COVID-19) pandemic. During the quarantine, because of the limited access to healthcare and avoiding exposure to COVID-19 as a contagious disease; patients of cancer suffered deferments in follow-up and treatment regimens leading to substantial worsening of disease, death, and increased healthcare costs. Thus, this study is designed to investigate the molecular mechanisms by which adamantne derivatives attenuate hepatocllular carcinoma experimentally and theoretically. There is a close association between increased resistance to anticancer drugs and defective apoptosis that considered a causative factor for oncogenesis. Cancer cells use different molecular pathways to inhibit apoptosis, BAX and Bcl-2 proteins have essential roles in the progression or inhibition of intrinsic apoptotic pathways triggered by mitochondrial dysfunction. Therefore, their balance ratio can promote the cellular apoptotic fate. In this study, the in vitro cytotoxic effects of seven synthetic adamantyl isothiorea derivatives were evaluated against five human tumor cell lines by MTT assay. Compounds 5 and 6 showed the best results, mostly against hepatocellular carcinoma (HCC). Hence, in vivo studies were performed in male Sprague-Dawley (SD) rats in which experimental hepatocellular carcinoma was induced with thioacetamide (TAA) (200 mg/kg, i.p., twice weekly) for 16 weeks. The most promising compounds, 5 and 6, were administered to treat liver cancer rats at a dose of 10 mg/kg/day for an additional two weeks, and the effects were compared with doxorubicin (DR), the anticancer drug. Hepatocellular carcinoma was evidenced by a dramatic increase in liver indices, oxidative stress markers, and immunohistochemical studies that were accompanied by a plethora of inflammatory mediators and alterations in the apoptotic cascade. Our results showed that treatment with adamantane derivatives 5 and 6 significantly suppressed fibrosis, inflammation, and other histopathological insults resulting in the diminished formation of hepatocyte tumorigenesis. Moreover, administration of the tested compounds resulted in amelioration of EGFR protein expression, upregulation of BAX, and lessening down of Bcl-2 levels that prove their role as apoptosis inducers. Also, the docking simulations performed for adamantane showed good fit and binding to the EGFR protein through hydrogen bond formation with conservative amino acids, which gives a shred of strong evidence for its hepatoprotective effect. In most analyses, the effects of compound 6 were more comparable to DR than compound 5. Our findings suggest that adamantane derivatives 5 and 6 are shown to have cytotoxic activity against HCC in vitro and in vivo, by more than one mechanism, possibly by inhibiting the TLR4-MyD88-NF-κB pathway and targeting EGFR signaling.

Keywords: adamantane, EGFR, HCC, apoptosis

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Authors: Priyoth Kittiteerasack, Alana Steffen, Alicia K. Matthews

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Depression is a leading cause of the worldwide burden of disability and disease burden. Notably, lesbian, gay, bisexual, and transgender (LGBT) populations are more likely to be a high-risk group for depression compared to their heterosexual and cisgender counterparts. To date, little is known about the rates and predictors of depression among Thai LGBT populations. As such, the purpose of this study was to: 1) measure the prevalence of depression among a diverse sample of Thai LGBT adults and 2) determine the influence of minority stress variables (discrimination, victimization, internalized homophobia, and identity concealment), general stress (stress and loneliness), and coping strategies (problem-focused, avoidance, and seeking social support) on depression outcomes. This study was guided by the Minority Stress Model (MSM). The MSM posits that elevated rates of mental health problems among LGBT populations stem from increased exposures to social stigma due to their membership in a stigmatized minority group. Social stigma, including discrimination and violence, represents unique sources of stress for LGBT individuals and have a direct impact on mental health. This study was conducted as part of a larger descriptive study of mental health among Thai LGBT adults. Standardized measures consistent with the MSM were selected and translated into the Thai language by a panel of LGBT experts using the forward and backward translation technique. The psychometric properties of translated instruments were tested and acceptable (Cronbach’s alpha > .8 and Content Validity Index = 1). Study participants were recruited using convenience and snowball sampling methods. Self-administered survey data were collected via an online survey and via in-person data collection conducted at a leading Thai LGBT organization. Descriptive statistics and multivariate analyses using multiple linear regression models were conducted to analyze study data. The mean age of participants (n = 411) was 29.5 years (S.D. = 7.4). Participants were primarily male (90.5%), homosexual (79.3%), and cisgender (76.6%). The mean score for depression of study participant was 9.46 (SD = 8.43). Forty-three percent of LGBT participants reported clinically significant levels of depression as measured by the Beck Depression Inventory. In multivariate models, the combined influence of demographic, stress, coping, and minority stressors explained 47.2% of the variance in depression scores (F(16,367) = 20.48, p < .001). Minority stressors independently associated with depression included discrimination (β = .43, p < .01) victimization (β = 1.53, p < .05), and identity concealment (β = -.54, p < .05). In addition, stress (β = .81, p < .001), history of a chronic disease (β = 1.20, p < .05), and coping strategies (problem-focused coping β = -1.88, p < .01, seeking social support β = -1.12, p < .05, and avoidance coping β = 2.85, p < .001) predicted depression scores. The study outcomes emphasized that minority stressors uniquely contributed to depression levels among Thai LGBT participants over and above typical non-minority stressors. Study findings have important implications for nursing practice and the development of intervention research.

Keywords: depression, LGBT, minority stress, sexual and gender minority, Thailand

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Authors: Sang Hun Park, Chul Gyu Song

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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

Procedia PDF Downloads 344

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

Procedia PDF Downloads 331

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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