Search results for: disease trajectory

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 114

Authors: Bhaskar Chakravorti, Christopher Tunnard, Ravi Shankar Chaturvedi

Abstract:

This report introduces the Digital Evolution Index (DEI) as a way to gauge the transformation of economies in the advanced and developing world from traditional brick-and-mortar to digitally enabled. The DEI measures the digital trajectories of 50 countries to provide actionable, data-informed insights for businesses, investors and policymakers. Created by The Fletcher School, in collaboration with MasterCard Worldwide and DataCash, the DEI analyzes the key underlying drivers and barriers that govern a country’s evolution into a digital economy: Demand, Supply, Institutional Environment and Innovation. A longitudinal analysis of these four drivers during the years 2008 to 2013 reveals both the current state of a country’s digital economy, as well as changes over time. Combining these two measures allows us to assign each country to one of four Trajectory Zones: • Stand Out countries have shown high levels of digital development in the past and continue to remain on an upward trajectory. • Stall Out countries have achieved a high level of evolution in the past but are losing momentum and risk falling behind. • Break Out countries have the potential to develop strong digital economies. Though their overall score is still low, they are moving upward and are poised to become Stand Out countries in the future. • Watch Out countries face significant opportunities and challenges, with low scores on both current level and upward motion of their DEI. Some may be able to overcome limitations with clever innovations and stopgap measures, while others seem to be stuck.

Keywords: e-commerce, digital evolution, digital commerce ecosystems, e-consumer

Procedia PDF Downloads 371

Authors: Moustafa Gabr

Abstract:

Galectin-3 has been identified as a critical player in driving the neuroinflammatory responses in Alzheimer's disease (AD). A key feature of this function of galectin-3 is associated with its interaction with the triggering receptor expressed on myeloid cells-2 (TREM2). Herein, we report a high-throughput screening (HTS) platform that can be used for the identification of inhibitors of TREM2 and galectin-3 interaction. We have utilized this HTS assay to screen a focused library of compounds optimized for central nervous system (CNS)-related diseases. MG-257 was identified from this screen as the first example of a small molecule that can attenuate TREM2 signaling based on its high affinity to galectin-3 (endogenous ligand of TREM2). Remarkably, MG-257 reduced the levels of proinflammatory cytokines in activated microglial cells, which highlights its ability to inhibit the neuroinflammatory response associated with AD.

Keywords: medicinal chemistry, Alzheimer's disease, drug discovery, therapeutics

Procedia PDF Downloads 12

Authors: Diana C. El Assal, Fatima Monteiro, Caroline May, Peter Barbuti, Silvia Bolognin, Averina Nicolae, Hulda Haraldsdottir, Lemmer R. P. El Assal, Swagatika Sahoo, Longfei Mao, Jens Schwamborn, Rejko Kruger, Ines Thiele, Kathrin Marcus, Ronan M. T. Fleming

Abstract:

Degeneration of substantia nigra pars compacta dopaminergic neurons is one of the hallmarks of Parkinson's disease. These neurons have a highly complex axonal arborisation and a high energy demand, so any reduction in ATP synthesis could lead to an imbalance between supply and demand, thereby impeding normal neuronal bioenergetic requirements. Synaptic mitochondria exhibit increased vulnerability to dysfunction in Parkinson's disease. After biogenesis in and transport from the cell body, synaptic mitochondria become highly dependent upon oxidative phosphorylation. We applied a systems biochemistry approach to identify the metabolic pathways used by neuronal mitochondria for energy generation. The mitochondrial component of an existing manual reconstruction of human metabolism was extended with manual curation of the biochemical literature and specialised using omics data from Parkinson's disease patients and controls, to generate reconstructions of synaptic and somal mitochondrial metabolism. These reconstructions were converted into stoichiometrically- and fluxconsistent constraint-based computational models. These models predict that Parkinson's disease is accompanied by an increase in the rate of glycolysis and a decrease in the rate of oxidative phosphorylation within synaptic mitochondria. This is consistent with independent experimental reports of a compensatory switching of bioenergetic pathways in the putamen of post-mortem Parkinson's disease patients. Ongoing work, in the context of the SysMedPD project is aimed at computational prediction of mitochondrial drug targets to slow the progression of neurodegeneration in the subset of Parkinson's disease patients with overt mitochondrial dysfunction.

Keywords: bioenergetics, mitochondria, Parkinson's disease, systems biochemistry

Procedia PDF Downloads 295

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

Procedia PDF Downloads 129

Authors: Hami Ashraf, Farid Kosari

Abstract:

Graft-versus-host disease (GvHD) is a common complication of allogeneic hematopoietic stem cell transplantation that can lead to significant morbidity and mortality. Histopathological examination of affected tissues is an essential tool for diagnosing and grading GvHD in animal models, which are used to study disease mechanisms and evaluate new therapies. In this systematic review, we identified and analyzed original research articles in PubMed, Scopus, Web of Science, and Google Scholar that described grading systems for GvHD in animal models based on histopathological features. We found that several grading systems have been developed, which vary in the tissues and criteria they assess, the severity scoring scales they use, and the level of detail they provide. Skin, liver, and gut are the most commonly evaluated tissues, but lung and thymus are also included in some systems. Our analysis highlights the need for standardized criteria and consistent use of grading systems to enable comparisons between studies and facilitate the translation of preclinical findings to clinical practice.

Keywords: graft-versus-host disease, GvHD, animal model, histopathology, grading system

Procedia PDF Downloads 64

Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

Abstract:

Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

Procedia PDF Downloads 146

Authors: P. S. Akami, H. Nahunnaro, A. Zubainatu

Abstract:

Cercospora leaf spot (Cercospora sesami. Zimm) has been identified as one of the most prevalent diseases, posing serious constraints to sesame production in producing areas. Two sets of experiments were carried out. The first and second experiments were conducted in the Modibbo Adama University of Technology Yola at the Crop Production and Horticulture and Plant Science Departments, respectively. The field experiment was carried out using a Randomized Complete Block Design and was replicated three times on a plot size of 4m x 5m with four sesame varieties and three Mancob-M fungicide levels (0g, 2g and 4g) to give a total of Twelve treatments. The laboratory experiment involved the isolation of the pathogens from diseased leaves with symptoms of Cercospora leaf spot, which was identified as Cercospora sesami. Data collected were subjected to analysis of variance for a randomized complete block design using SAS (1999) statistical package. The treatment means that are significantly different were separated using the Least Significant Difference at P=0.05. The result revealed that 4g Mancob M recorded the lowest mean value for disease incidence and severity at 8WAS, which was 90.30% and 35.60%, respectively, while the control (0g) recorded the highest mean value for disease incidence and severity at 90.30% and 59.80% respectively. Ex-Sudan recorded the lowest value of 720 kg/ha, while NCRIBEN 03 recorded the highest yield of 834 kg/ha-¹. For the concentrations, 2g recorded a higher yield of 843 kg/ha-¹ followed by 0g, which recorded 765 kg/ha-¹. Conclusively, Cercospora leaf spot of sesame was found to be prevalent. E8 has a higher resistance to the disease, while NCRIBEN 03 tends to be more susceptible. It is therefore recommended that further trials should be carried out using different varieties in different locations.

Keywords: disease, evaluation, prevalence, treatment, resistance

Procedia PDF Downloads 96

Authors: Duanghathai Saipinta, Tanittian Panyamongkol, Witaya Suriyasathaporn

Abstract:

Animal management aims to provide a suitable environment for animals allowing maximal productivity in those animals. Prevention of disease is an important part of animal management. Foot-and-mouth disease (FMD) is a highly contagious viral disease in cattle and is an economically important animal disease worldwide. Monitoring the FMD virus in farms is useful management for the prevention of the FMD outbreak. A recent publication indicated collection samples from nasal swabs can be used for monitoring FMD in symptomatic cows. Therefore, the objectives of this study were to determine the FMD virus in asymptomatic dairy cattle using nasal swab samples during the absence of an FMD outbreak. The study was conducted from December 2020 to June 2021 using 185 asymptomatic signs of FMD dairy cattle in Chiang Mai Province, Thailand. By random cow selection, nasal mucosal swabs were used to collect samples from the selected cows and then were to evaluate the presence of FMD viruses using the real-time rt-PCR assay. In total, 4.9% of dairy cattle detected FMD virus, including 2 dairy farms in Mae-on (8 samples; 9.6%) and 1 farm in the Chai-Prakan district (1 sample; 1.2%). Interestingly, both farms in Mae-on were the outbreak of the FMD after this detection for 6 months. This indicated that the FMD virus presented in asymptomatic cattle might relate to the subsequent outbreak of FMD. The outbreak demonstrates the presence of the virus in the environment. In conclusion, monitoring of FMD can be performed by nasal swab collection. Further investigation is needed to show whether the FMD virus presented in asymptomatic FMD cattle could be the cause of the subsequent FMD outbreak or not.

Keywords: cattle, foot-and-mouth disease, nasal swab, real-time rt-PCR assay

Procedia PDF Downloads 232

Authors: Manisha, Manisha Mathur, Jay K. Desai, Shesh Asopa, Manisha Mehra

Abstract:

The present study was carried out for the comprehensive analysis of lumpy skin disease (LSD) in cattle and to elucidate the histopathology of vital organs in natural outbreaks. Lumpy skin disease (LSD) is a viral infection that primarily affects cattle. It is caused by a Capri pox virus and is characterized by the formation of skin nodules or lesions. For this study, a postmortem of 20 cows who died of Lumpy skin disease in different regions of Rajasthan was conducted. This study aimed to examine a cow's external and internal organs to confirm if lumpy skin disease was the cause of death. Accurate diagnosis is essential for improving disease surveillance, understanding the disease's progression, and informing control measures. Pathological examinations reveal virus-induced changes across organs, while histopathological analyses provide crucial insights into the disease's pathogenesis, aiding in the development of advanced diagnostics and effective prevention strategies. Histopathological examination of nodular skin lesions revealed edema, hyperemia, acanthosis, severe hydropic degeneration/ballooning degeneration, and hyperkeratosis in the epidermis. In the lungs, congestion, oedema, emphysema, and atelectasis were observed grossly. Microscopically changes were suggestive of interstitial pneumonia, suppurative pneumonia, bronchopneumonia post pneumonic fibrosis, and stage of resolution. Grossely liver showed congestion and necrotic foci microscopically in most of the cases, and the liver showed acute viral hepatitis. Microscopically in kidneys, multifocal interstitial nephritis was observed. There was marked interstitial inflammation and zonal fibrosis with cystically dilated tubules and bowman's capsules. Microscopically, most of the heart tissue section showed normal histology with few sarcocysts in between cardiac muscles. In some cases, loss of cross striation, sarcoplasmic vacuolation, fregmentation, and disintegration of cardiac fibres were observed. The present study revealed the characteristic gross and histopathological changes in different organs in natural cases of lumpy skin disease. Further, the disease was confirmed based on the molecular diagnosis and transmission electron microscopy of capripox infection in the affected cattle in the study area.

Keywords: Capripoxvirus, lumpy skin disease, polymerage chain reaction, transmission electron microscopy

Procedia PDF Downloads 29

Authors: Mehrnaz Farzingohar, Mehran Yasemi, Ahmad Savari

Abstract:

The oil products are imported and exported via Rajaee’s tanker terminal. Within loading and discharging in several cases the oil is released into the berths and made oil spills. The spills are distributed within short time and seriously affected Rajaee port’s environment and even extended areas. The trajectory and fate of oil spills investigated by modeling and parted by three risk levels base on the modeling results. First GNOME (General NOAA Operational Modeling Environment) applied to trajectory the liquid oil. Second, ALOHA (Areal Location Of Hazardous Atmosphere) air quality model, is integrated to predict the oil evaporation path within the air. Base on the identified zones the high risk areas are signed by colored dots which their densities calculated and clarified on a map which displayed the harm places. Wind and water circulation moved the pollution to the East of Rajaee Port that accumulated about 12 km of coastline. Approximately 20 km of north east of Qeshm Island shore is covered by the three levels of risky areas. Since the main wind direction is SSW the pollution pushed to the east and the highest risk zones formed on the crests edges hence the low risk appeared on the concavities. This assessment help the management and emergency systems to monitor the exposure places base on the priority factors and find the best approaches to protect the environment.

Keywords: oil spill, modeling, pollution, risk assessment

Procedia PDF Downloads 388

Authors: Ali Fuad Ashour

Abstract:

Introduction: Multiple sclerosis (MS) is a chronic, progressive and degenerative disease that affects the central nervous system (CNS). MS has been described to result in the debilitating symptom of the disease. It is reported to have a negative impact on the patient’s mental activities, brings a lower quality of life, leads to unemployment, causes distress and psychological disorders, generates low levels of motivation and self-esteem, and result in disability and neurological impairment. The aim of this study was to compare the effects of MS on patients from Britain and Kuwait. Methodology: A questionnaire was distributed to 200 individuals with MS (100 Kuwaiti and 100 British). The questionnaire consists of three parts; 1. General demographics, 2. Disease-specific data (symptoms, severity levels, relapse frequency, and support system), and 3. Attitudes towards physical exercise. Results: A response rate of 62% from the British sample and 50% from the Kuwaiti sample was achieved. 84% of the sample (n=52) were 41 years old or over. The duration of the disease was less than 10 years in 43.4% of British and 68% of Kuwaiti respondents. The majority of British respondents (56.5%) reported the disease severity to be moderate, while the majority of Kuwaitis was mild (72%). The annual relapse rates in Kuwait were relatively low, with 82% of the Kuwaiti sample had one relapse per year, compared to the 64.5% of British. The most common symptoms reported by British respondents were balance (75.8%), fatigue (74.2%), and weakness (71%), and by Kuwaiti respondents were fatigue (86%), balance (76%), and weakness (66%). The help and support for MS were by far more diverse for the British than Kuwaiti respondents. Discussion: The results unveiled marked differences between two groups of British and Kuwaiti MS patients in terms of patients’ age and disease duration, and severity. The overwhelming majority of Kuwaiti patients are young individuals who have been with the disease for a relatively short period of time, and their MS in most cases was mild. On the other hand, British patients were relatively older, many have been with the disease for a long period of time, and their average MS condition was more serious than that of their Kuwaiti counterparts. The main support in Kuwait comes from the neurologist, who primarily prescribe medications and advise patients to try to be active. The Kuwaiti respondents thought that lack of encouragement was the main reason for them not to engage in social activities.

Keywords: multiple sclerosis, Kuwait, exercise, demographic

Procedia PDF Downloads 118

Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Yuna Inada, Chihiro Tohda

Abstract:

Intro: Trigonella foenum-graecum (Fenugreek), from Fabaceae family is a well-known plant traditionally used as food and medicine. Many pharmacological effects of Trigonella foenum- graecum seeds extract (TF extract) were evaluated such as anti-diabetic, anti-tumor and anti-dementia effects using in vivo models. Regarding the anti-dementia effects of TF extract, diabetic rats, aluminum chloride-induced amnesia rats and scopolamine-injected mice were used previously for evaluation, which are not well established as Alzheimer’s disease models. In addition, those previous studies, active constituents in TF extract for memory function were not identified. Method: This study aimed to clarify the effect of TF extract on Alzheimer’s disease model, 5XFAD mouse that overexpresses mutated APP and PS1 genes and determine the major active constituent in the brain after oral intake of TF extract. Results: Trigonelline was detected in the cerebral cortex of 5XFAD mice after 24 hours of oral administration of TF extract by LC-MS/MS. Oral administration of TF extract for 17 days improved object location memory in 5XFAD mice. Conclusion: These results suggest that TF extract and its active constituents could be an expected therapeutic candidate for Alzheimer’s disease.

Keywords: Alzheimer's disease, LC-MS/MS, memory recovery, Trigonella foenum-graecum Seeds, 5XFAD mice

Procedia PDF Downloads 148

Authors: Bárbara Durão, Pedro Almeida, David Ramilo, André Meneses, Rute Canejo-Teixeira

Abstract:

The importance of quality of life (QoL) assessment in veterinary medicine is an integral part of patient care. This is especially true in cases of chronic diseases, such as chronic kidney disease (CKD), where the ever more advanced treatment options prolong the patient’s life. Whether this prolongment of life comes with an acceptable quality of life remains has been called into question. The aim of this study was to evaluate the relationship between CKD disease biomarkers and QoL in cats. Thirty-seven cats diagnosed with CKD and with no known concurrent illness were enrolled in an observational study. Through the course of several evaluations, renal biomarkers were assessed in blood and urine samples, and owners retrospectively described their cat’s quality of life using a validated instrument for this disease. Correlations between QoL scores (AWIS) and the biomarkers were assessed using Spearman’s rank test. Statistical significance was set at p-value < 0.05, and every serial sample was considered independent. Thirty-seven cats met the inclusion criteria, and all owners completed the questionnaire every time their pet was evaluated, giving a total of eighty-four questionnaires, and the average-weighted-impact-score was –0.5. Results showed there was a statistically significant correlation between the quality of life and most of 17 the studied biomarkers and confirmed that CKD has a negative impact on QoL in cats especially due to the management of the disease and secondary appetite disorders. To our knowledge, this is the attempt to assess the correlation between renal biomarkers and QoL in cats. Our results reveal a strong potential of this type of approach in clinical management, mainly in situations where it is not possible to measure biomarkers. Whilst health-related QoL is a reliable predictor of mortality and morbidity in humans; our findings can help improve the clinical practice in cats with CKD.

Keywords: chronic kidney disease, biomarkers, quality of life, feline

Procedia PDF Downloads 181

Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

Abstract:

Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

Procedia PDF Downloads 109

Authors: Tarnai Tena, Strinić Dean

Abstract:

Chronic non-communicable diseases are today the leading cause of mortality, morbidity and mortality disability at the world level and in Croatia. Among them are the most represented precisely cardiovascular diseases (CVD), so today we are talking about their global card epidemic. From 2018 to 2021, cardiovascular diseases are the leading cause of death for both women and men in the Dubrovnik- Neretva County. With regard to the COVID-19 pandemic, which has taken over, without forgetting how much these patients are additionally affected, we are still talking about the primary cause of sickness and death in the population of this county and region. In this record, we present collected data processed according to gender and disease classification. We also bring a kind of overview because, for years, we have been following how the population of one of the origins of the Mediterranean diet has been struggling with cardiovascular diseases.

Keywords: cardiovascular disease, burden, COVID-19, epidemiology, ishemic heart disease, cardiovascular medicine

Procedia PDF Downloads 84

Authors: Hadi O. Tohme

Abstract:

This study is a review on the effectiveness of new physiotherapy techniques with external sensory stimulus compared to standard physiotherapy in the daily activities of patients with Parkinson's disease. Twenty studies from 1996 to 2015 were analyzed and discussed in this review, using the rehabilitation strategy with external sensory stimulus evaluating walking, freezing episodes, balance, transfers, and daily activities of parkinsonian patients. The study highlights the effectiveness of the variety of rehabilitation with cueing strategy used in the treatment of Parkinson's disease. Based on the literature review completed, there is a need for more specific trials with better treatment strategies to support the most appropriate choice of physiotherapy intervention using external sensory stimulus to the type and frequency of this stimulus. In addition, no trials examined the long-term benefits of the physiotherapy intervention with the external sensory stimulus. In order to determine if, or how long the improvements due to the external sensory stimulus physiotherapy intervention can last, long-term follow-up should be performed.

Keywords: cueing strategy, external sensory stimulus, parkinson disease, rehabilitation for parkinson, sensory attention focused exercises, sensory strategy reeducation

Procedia PDF Downloads 253

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

Abstract:

We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

Procedia PDF Downloads 371

Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

Procedia PDF Downloads 323

Authors: M. Imran Hamid, Muzammil Hussain, Yunpeng Wu, Meichun Xiang, Xingzhong Liu

Abstract:

The rhizosphere microbiome elucidate multiple functioning in the soil suppressiveness against plant pathogens. Soybean rhizosphere microbial communities may involve in the natural suppression of soybean cyst nematode (SCN) populations in disease suppressive soils. To explore these ecological mechanisms of microbes, a long term monoculture suppressive soil were taken into account for further investigation to test the disease suppressive ability by using different treatments. The designed treatments are as, i) suppressive soil (S), ii) conducive soil (C), iii) conducive soil mixed with 10% (w/w) suppressive soil (CS), iv) suppressive soil treated at 80°C for 1 hr (S80), and v) suppressive soil treated with formalin (SF). By using an ultra-high-throughput sequencing approach, we identified the key bacterial and fungal taxa involved in SCN suppression. The Phylum-level investigation of bacteria revealed that Actinobacteria, Bacteroidetes, and Proteobacteria in the rhizosphere soil of soybean seedlings were more abundant in the suppressive soil than in the conducive soil. The phylum-level analysis of fungi in rhizosphere soil indicated that relative abundance of Ascomycota was higher in suppressive soil than in the conducive soil, where Basidiomycota was more abundant. Transferring suppressive soil to conducive soil increased the population of Ascomycota in the conducive soil by lowering the populations of Basidiomycota. The genera, such as, Pochonia, Purpureocillium, Fusarium, Stachybotrys that have been well documented as bio-control agents of plant nematodes were far more in the disease suppressive soils. Our results suggested that the plants engage a subset of functional microbial groups in the rhizosphere for initial defense upon nematode attack and protect the plant roots later on by nematodes to response for suppression of SCN in disease-suppressive soils.

Keywords: disease suppressive soil, high-throughput sequencing, rhizosphere microbiome, soybean cyst nematode

Procedia PDF Downloads 153

Authors: A. V. Sokolov, S. V. Vorobyev, A. Yu. Efimtcev, V. Yu. Lobzin, I. A. Lupanov, O. A. Cherdakov, V. A. Fokin

Abstract:

Alzheimer’s disease (AD) is the most common form of dementia. Different brain regions are involved to the pathological process of AD. The purpose of this study was to evaluate brain activation by visual memory task in patients with Alzheimer's disease and determine correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. To investigate the organization of memory and localize cortical areas activated by visual memory task we used functional magnetic resonance imaging and to evaluate brain atrophy of patients with Alzheimer's disease we used voxel-based morphometry. FMRI was performed on 1.5 T MR-scanner Siemens Magnetom Symphony with BOLD (Blood Oxygenation Level Dependent) technique, based on distinctions of magnetic properties of hemoglobin. For test stimuli we used series of 12 not related images for "Baseline" and 12 images with 6 presented before for "Active". Stimuli were presented 3 times with reduction of repeated images to 4 and 2. Patients with Alzheimer's disease showed less activation in hippocampal formation (HF) region and parahippocampal gyrus then healthy persons of control group (p<0.05). The study also showed reduced activation in posterior cingulate cortex (p<0.001). Voxel-based morphometry showed significant atrophy of grey matter in Alzheimer’s disease patients, especially of both temporal lobes (fusiform and parahippocampal gyri); frontal lobes (posterior cingulate and superior frontal gyri). The study showed correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. Thus, reduced activation in hippocampal formation and parahippocampal gyri, in posterior cingulate gyrus in patients with Alzheimer's disease correlates to significant atrophy of these regions, detected by voxel-based morphometry, and to deterioration of specific cognitive functions.

Keywords: Alzheimer’s disease, functional MRI, voxel-based morphometry

Procedia PDF Downloads 320

Authors: Kelly E. Tow, Peter Caputi, Claudia Rogge, Thomas Lee, Simon R. Knowles

Abstract:

Inflammatory Bowel Disease (IBD) is a serious chronic health condition, characterised by inflammation of the gastrointestinal tract. Individuals with active IBD experience severe abdominal symptoms, which can adversely impact their physical and mental health, as well as their quality of life (QoL). Given that stress may exacerbate IBD symptoms and is frequently highlighted as a contributing factor for the development of psychological difficulties and poorer QoL, it is vital to investigate stress-management strategies aimed at improving the lives of those with IBD. The present study extends on the limited research in IBD cohorts by exploring the role of dispositional mindfulness and its impact on psychological well-being and QoL. The study examined how disease activity and dispositional mindfulness were related to psychological distress and QoL in a cohort of IBD patients. The potential role of dispositional mindfulness as a moderator between stress and anxiety, depression and QoL in these individuals was also examined. Participants included 47 patients with a clinical diagnosis of IBD. Each patient completed a series of psychological questionnaires and was assessed by a gastroenterologist to determine their disease activity levels. Correlation analyses indicated that disease activity was not significantly related to psychological distress or QoL in the sample of IBD patients. However, dispositional mindfulness was inversely related to psychological distress and positively related to QoL. Furthermore, moderation analyses demonstrated a significant interaction between stress and dispositional mindfulness on anxiety. These findings demonstrate that increased levels of dispositional mindfulness may be beneficial for individuals with IBD. Specifically, the results indicate positive links between dispositional mindfulness, general psychological well-being and QoL, and suggest that dispositional mindfulness may attenuate the negative impacts of stress on levels of anxiety in IBD patients. While further research is required to validate and expand on these findings, the current study highlights the importance of addressing psychological factors in IBD and indicates support for the use of mindfulness-based interventions for patients with the disease.

Keywords: anxiety, depression, dispositional mindfulness, inflammatory bowel disease, quality of life, stress

Procedia PDF Downloads 160

Authors: Sally Shepherd, Richard De Boer, Craig Murphy

Abstract:

Background: Invasive lobular carcinoma (ILC) can metastasize to atypical sites within the peritoneal cavity, gastrointestinal, or genitourinary tract. Management varies depending on the symptom presentation, extent of disease burden, particularly if the primary disease is occult, and patient wishes. Case Series: 6 patients presented with general surgical presentations of ILC, including incomplete large bowel obstruction, cholecystitis, persistent lower abdominal pain, and faecal incontinence. 3 were diagnosed with their primary and metastatic disease in the same presentation, whilst 3 patients developed metastasis from 5 to 8 years post primary diagnosis of ILC. Management included resection of the metastasis (laparoscopic cholecystectomy), excision of the primary (mastectomy and axillary clearance), followed by a combination of aromatase inhibitors, biologic therapy, and chemotherapy. Survival post diagnosis of metastasis ranged from 3 weeks to 7 years. Conclusion: Metastatic ILC must be considered with any gastrointestinal or genitourinary symptoms in patients with a current or past history of ILC. Management may not be straightforward to chemotherapy if the acute pathology is resulting in a surgically resectable disease.

Keywords: breast cancer, gastrointestinal metastasis, invasive lobular carcinoma, metastasis

Procedia PDF Downloads 148

Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka

Abstract:

Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.

Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory

Procedia PDF Downloads 220

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

Abstract:

Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

Procedia PDF Downloads 65

Authors: Xinyuan Y. Song, Kai Kang

Abstract:

Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

Procedia PDF Downloads 145

Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

Abstract:

Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

Procedia PDF Downloads 404

Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

Procedia PDF Downloads 408

Authors: G. Tamilpavai, C. Vishnuppriya

Abstract:

Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

Procedia PDF Downloads 267

Authors: Ilirian Laçi, Alketa Spahiu

Abstract:

Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

Procedia PDF Downloads 98