Search results for: disease prediction

Authors: Peter David Reiss

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The concept of the psychosis prodrome has allowed for the identification of adolescent and young adult patients who have a significantly elevated risk of developing schizophrenia spectrum disorders. A number of different interventions have been tested in order to prevent or delay progression of symptoms. To date, there has been no consistent meta-analytical evidence to support efficacy of antipsychotic treatment for patients in the prodromal state, and their use remains therefore inconclusive. Although antipsychotics may manage symptoms transiently, they have not been found to prevent or delay onset of psychotic disorders. Furthermore, pharmacological intervention in high-risk individuals remains controversial, because of the antipsychotic side effect profile in a population in which only about 20 to 35 percent will eventually convert to psychosis over a two-year period, with even after two years conversion rates not exceeding 30 to 40 percent. This general estimate is additionally problematic, in that it ignores the fact that there is significant variation in individual risk among clinical high-risk cases. The current lack of reliable tests for at-risk patients makes it difficult to justify individual treatment decisions. Preventive treatment should ideally be dictated by an individual’s risk while minimizing potentially harmful medication exposure. This requires more accurate predictive assessments by using valid and accessible prognostic markers. The following will compare prediction and risk modification potential of behavioral biomarkers such as disturbances of basic sense of self and emotion awareness, neurocognitive biomarkers such as attention, working and declarative memory, and neurophysiological biomarkers such as glutamatergic abnormalities and NMDA receptor dysfunction. Identification of robust biomarkers could therefore not only provide more reliable means of psychosis prediction, but also help test and develop new clinical interventions targeted at the prodromal state.

Keywords: at-risk mental state, biomarkers, glutamatergic system, NMDA receptor, psychosis prodrome, schizophrenia

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Authors: Ankan Roy, Niharika, Samir Kumar Patra

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Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

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Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, Ahmad Albaqsami, Al Warith Al Rushaidi, Masoud Al Rawahi

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Predicting the interaction between drugs and their molecular targets is pivotal for advancing drug development processes. Due to the time and cost limitations, computational approaches have emerged as an effective approach to drug-target interaction (DTI) prediction. Most of the introduced computational based approaches utilize the drug molecule and protein sequence as input. This study does not only utilize these inputs, it also introduces a protein representation developed using a masked protein language model. In this representation, for every individual amino acid residue within the protein sequence, there exists a corresponding probability distribution that indicates the likelihood of each amino acid being present at that particular position. Then, the similarity between each pair of amino-acids is computed to create similarity matrix. To encode the knowledge of the similarity matrix, Bi-Level Routing Attention (BiFormer) is utilized, which combines aspects of transformer-based models with protein sequence analysis and represents a significant advancement in the field of drug-protein interaction prediction. BiFormer has the ability to pinpoint the most effective regions of the protein sequence that are responsible for facilitating interactions between the protein and drugs, thereby enhancing the understanding of these critical interactions. Thus, it appears promising in its ability to capture the local structural relationship of the proteins by enhancing the understanding of how it contributes to drug protein interactions, thereby facilitating more accurate predictions. To evaluate the proposed method, it was tested on two widely recognized datasets: Davis and KIBA. A comprehensive series of experiments was conducted to illustrate its effectiveness in comparison to cuttingedge techniques.

Keywords: BiFormer, transformer, protein language processing, self-attention mechanism, binding affinity, drug target interaction, similarity matrix, protein masked representation, protein language model

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Authors: Jean-Philippe Amat, Timothée Vergne, Aymeric Hans, Bénédicte Ferry, Pascal Hendrikx, Jackie Tapprest, Barbara Dufour, Agnès Leblond

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The surveillance of infectious diseases is necessary to describe their occurrence and help the planning, implementation and evaluation of risk mitigation activities. However, the exact number of detected cases may remain unknown whether surveillance is based on serological tests because identifying seroconversion may be difficult. Moreover, incomplete detection of cases or outbreaks is a recurrent issue in the field of disease surveillance. This study addresses these two issues. Using a viral animal disease as an example (equine viral arteritis), the goals were to establish suitable rules for identifying seroconversion in order to estimate the number of cases and outbreaks detected by a surveillance system in France between 2006 and 2013, and to assess the sensitivity of this system by estimating the total number of outbreaks that occurred during this period (including unreported outbreaks) using a capture-recapture model. Data from horses which exhibited at least one positive result in serology using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of the annual antibody titers and the location of the subjects (towns). A consensus among multidisciplinary experts (specialists in the disease and its laboratory diagnosis, epidemiologists) was reached to consider seroconversion as a change in antibody titer from negative to at least 32 or as a three-fold or greater increase. The number of seroconversions was counted for each town and modeled using a unilist zero-truncated binomial (ZTB) capture-recapture model with R software. The binomial denominator was the number of horses tested in each infected town. Using the defined rules, 239 cases located in 177 towns (outbreaks) were identified from 2006 to 2013. Subsequently, the sensitivity of the surveillance system was estimated as the ratio of the number of detected outbreaks to the total number of outbreaks that occurred (including unreported outbreaks) estimated using the ZTB model. The total number of outbreaks was estimated at 215 (95% credible interval CrI95%: 195-249) and the surveillance sensitivity at 82% (CrI95%: 71-91). The rules proposed for identifying seroconversion may serve future research. Such rules, adjusted to the local environment, could conceivably be applied in other countries with surveillance programs dedicated to this disease. More generally, defining ad hoc algorithms for interpreting the antibody titer could be useful regarding other human and animal diseases and zoonosis when there is a lack of accurate information in the literature about the serological response in naturally infected subjects. This study shows how capture-recapture methods may help to estimate the sensitivity of an imperfect surveillance system and to valorize surveillance data. The sensitivity of the surveillance system of equine viral arteritis is relatively high and supports its relevance to prevent the disease spreading.

Keywords: Bayesian inference, capture-recapture, epidemiology, equine viral arteritis, infectious disease, seroconversion, surveillance

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Authors: Nattapong Techarattanased, Paweena Sribunrueng

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The objective of this study is to investigate strategies in customer relationship management and customers’ behavior in making decision on buying car insurance of Southeast Insurance Co. Ltd. in Bangkok. Subjects in this study included 400 customers with the age over 20 years old to complete questionnaires. The data were analyzed by arithmetic mean and multiple regressions. The results revealed that the customers’ opinions on the strategies in customer relationship management, i.e. customer relationship, customer feedback, customer follow-up, useful service suggestions, customer communication, and service channels were in moderate level but on the customer retention was in high level. Moreover, the strategy in customer relationship management, i.e. customer relationship, and customer feedback had an influence on customers’ buying decision on buying car insurance. The two factors above can be used for the prediction at the rate of 34%. In addition, the strategy in customer relationship management, i.e. customer retention, customer feedback, and useful service suggestions had an influence on the customers’ buying decision on period of being customers. The three factors could be used for the prediction at the rate of 45%.

Keywords: strategies, customer relationship management, behavior in buying decision, car insurance

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Authors: Kobus-Cisowska Joanna, Flaczyk Ewa, Gramza-Michalowska Anna, Kmiecik Dominik, Przeor Monika, Marcinkowska Agata

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In recent years, proceed to the attractiveness of typical bakery products. Expanding the education and nutrition knowledge society will develop the production of functional foods, which has a positive impact on human health. Therefore, the aim of the present study was to evaluate the effect of the addition of white mulberry fruit on the content of biologically active compounds in the new designed functional bread premixes designed for selected disease: anemia, diabetes, obesity and cardiovascular disease. For flavonols and phenolic acids content UPLC was conducted, using an NovaPack C18 column and a gradient elution system. It was found that all attempts bread characterized by a high content of biologically active compounds: polyphenols, phenolic acids, and flavonoids. The highest total content of polyphenolic compounds found in the samples of bread for anemia, diabetes and cardiovascular disease both before and after storage. The analyzed sample differed in content of phenolic acids. The highest content of these compounds were found in samples of bread for anemia and diabetes. It was found that the analyzed sample contained phenolic acids that are derivatives of hydroxybenzoic and hydroxycinnamic acid. The new designed bread contained significant amounts of flavonols, of which the dominant was routine.

Keywords: mulberry, antioxidant, polyphenols, phenolic acids, flavonols

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Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

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Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Rhodine Hickman, Craig Wylie, Michael G. McCaul

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Introduction: The World Health Organisation has called on governments around the world to recognise emergency conditions as a global public health problem and respond with appropriate steps for effective preventative strategies. However, to understand the magnitude of the problem, good quality epidemiological data is required. This is especially challenging in low and middle-income countries, where routine data is scarce, specifically within the prehospital setting. Methods: We conducted a retrospective cross-sectional study of a national prehospital private sector EMS database. The database being the property of ER24 (private Emergency Medical Services (EMS) company in South Africa) contains claims submitted by the majority of ambulance services in South Africa during the period between 1 January 2008 to 28 March 2017. We used descriptive statistics and control charts to describe the data using STATA 14. Results: 299,257 calls were included in the analysis. The top clinical conditions requiring ambulance transport were transport accidents (10% of total call volume) and ischaemic heart disease (4.4%). The number of transport accidents consistently increased between 2009 and 2014 and reached beyond the limit for normal variation in 2015. Victims of transport accidents required basic life support services 60% of the time with 80% of injuries being minor to moderate. The frequency of ischaemic heart disease had a steady incline from 2011 to 2016. Advanced life support services were required about 50% of the time, with 60% of patients needing urgent care. Conclusion: Transport accidents, followed by ischaemic heart disease, are the most prevalent conditions in South African private EMS. There is a potential to address these conditions by developing the capacity of low and mid-level providers in trauma and advanced EMS providers in ischaemic heart disease.

Keywords: emergency care, emergency medicine, prehospital providers, South Africa

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

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Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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Authors: Amna Abdalla Mohammed Khalid, Pietro Parisse, Silvia Onesti, Loredana Casalis

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Basic cellular processes as DNA replication are crucial to cell life. Understanding at the molecular level the mechanisms that govern DNA replication in proliferating cells is fundamental to understand disease connected to genomic instabilities, as a genetic disease and cancer. A key step for DNA replication to take place, is unwinding the DNA double helix and this carried out by proteins called helicases. The archaeal MCM (minichromosome maintenance) complex from Methanothermobacter thermautotrophicus have being studied using Atomic Force Microscopy (AFM), imaging in air and liquid (Physiological environment). The accurate analysis of AFM topographic images allowed to understand the static conformations as well the interaction dynamic of MCM and DNA double helix in the present of ATP.

Keywords: DNA, protein-DNA interaction, MCM (mini chromosome manteinance) complex, atomic force microscopy (AFM)

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Authors: Priyanka Jain, Sushila Pareek

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Skin disease is often considered to be ‘only cosmetic’ by many medical professionals and lay-people alike but unlike most internal illnesses, skin disease is often immediately visible to others and therefore people suffering from dermatological conditions may suffer serious social and emotional consequences. The purpose of this research was to compare patients suffering from acne, alopecia areata (AA) and melanosis on perceived stress, social appearance anxiety and coping. The study included 120 patients (acne = 40 AA = 40 melanosis = 40) ages ranged from 15 to 25 years. Perceived Stress Scale (PSS), Social Appearance Anxiety Scale (SAAS), and The Brief COPE were administered to the patients. Analytical evaluation was done by Kruskal Wallis and ANOVA-tests. The results of the present study clearly revealed that perceived stress and social appearance anxiety were highest in patients with AA followed by acne patients and found least in patients with melanosis. With regard to coping, self-distraction as a coping technique was found highest in patients suffering from AA followed by acne and then melanosis. Denial was highest in acne patients followed by AA and experienced least by patients with melanosis. Behavioural disengagement was almost equal in patients with melanosis and acne and a little less in patients suffering from AA Acceptance was highest in patients with melanosis, followed by AA and least in acne patients. Self-blame was found highest in patients with acne, followed by AA patients further followed by patients suffering from melanosis. This study is an attempt to stimulate professionals working in the field of dermatology and mental health to explore their supportive communication and increase awareness regarding the difficulties that patients with skin disease can face.

Keywords: coping, dermatology, perceived stress, psychosocial impact, social appearance anxiety

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: Triveni Gogoi, Rima Chatterjee

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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

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Authors: Paul Han, Jun-Geol Baek

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In the flat panel display industry, the scheduler and dispatching system to meet production target quantities and the deadline of production are the major production management system which controls each facility production order and distribution of WIP (Work in Process). In dispatching system, delivery time is a key factor for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors and a forecasting model of delivery time. Of survival analysis techniques to select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the Accelerated Failure Time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the Mean Square Error (MSE) criteria, the AFT model decreased by 33.8% compared to the existing prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing a delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

Keywords: delivery time, survival analysis, Cox PH model, accelerated failure time model

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Authors: F. J. Ma, A. K. H. Kwan

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Crack caused by shrinkage movement of concrete is a serious problem especially when restraint is provided. It may cause severe serviceability and durability problems. The existing prediction methods for crack width of concrete due to shrinkage movement are mainly numerical methods under simplified circumstances, which do not agree with each other. To get a more unified prediction method applicable to more sophisticated circumstances, finite element crack width analysis for shrinkage effect should be developed. However, no existing finite element analysis can be carried out to predict the crack width of concrete due to shrinkage movement because of unsolved reasons of conventional finite element analysis. In this paper, crack width analysis implemented by finite element analysis is presented with pseudo-discrete crack model, which combines traditional smeared crack model and newly proposed crack queuing algorithm. The proposed pseudo-discrete crack model is capable of simulating separate and single crack without adopting discrete crack element. And the improved finite element analysis can successfully simulate the stress redistribution when concrete is cracked, which is crucial for predicting crack width, crack spacing and crack number.

Keywords: crack queuing algorithm, crack width analysis, finite element analysis, shrinkage effect

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Authors: Aliyu Maje Bello, Yaowaluck Maprang Roshorm

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Hand, foot, and mouth disease (HFMD) is a highly contagious viral infection affecting mostly infants and children. Although the Enterovirus A71 (EV71) is usually the major causative agent of HFMD, other enteroviruses such as coxsackievirus A16, A10, and A6 are also found in some of the recent outbreaks. The commercially available vaccines have demonstrated their effectiveness against only EV71 infection but no protection against other enteroviruses. To address the limitation of the monovalent EV71 vaccine, the present study thus designed a tetravalent vaccine against the four major enteroviruses causing HFMD and primarily evaluated the designed vaccine using an immunoinformatics approach. The immunogen was designed to contain the EV71 VP1 protein and multiple reported epitopes from all four distinct enteroviruses and thus designated a tetravalent vaccine. The 3D structure of the designed tetravalent vaccine was modeled, refined, and validated. Epitope screening showed the presence of B-cell, CTL, CD4 T cell, and IFN epitopes with vast application among the Asian population. Docking analysis confirmed the stable and strong binding interactions between the immunogen and immune receptor B-cell receptor (BCR). In silico cloning and immune simulation analyses guaranteed high efficiency and sufficient expression of the vaccine candidate in humans. Overall, the promising results obtained from the in-silico studies of the proposed tetravalent vaccine make it a potential candidate worth further experimental validation.

Keywords: enteroviruses, coxsackieviruses, hand foot and mouth disease, immunoinformatics, tetravalent vaccine

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Authors: Maria Cristina B. Cabanag, Elijinese Marie S. Culangen

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Pregnancy is a period in a woman's life wherein the body may undergo different physiological changes. These changes can be attributed to the interplay of hormones in the body but can mask a more sinister type of disease such as malignancy on rare occasions. Colorectal cancer (CRC) in pregnancy is an epidemiologically rare disease worldwide. To our knowledge, no available studies were reported in the Philippines at the time of this writing, posing a dilemma for its appropriate diagnosis and management. Signs and symptoms of colorectal malignancy may camouflage a normal pregnancy and, when overlooked, impedes an appropriate approach. This case of a 38-year-old elderly primigravid who presented with hematochezia on her 25th week of gestation. She was diagnosed with rectal adenocarcinoma later in pregnancy which warranted a predicament regarding her appropriate care and management. This paper explores the repertoire of the different diagnostic and treatment approaches to colorectal cancer in the second trimester of pregnancy, with the least possible maternal and fetal hazards.

Keywords: cancer in pregnancy, chemotherapy in pregnancy, colorectal cancer, hematochezia in pregnancy

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: R. Bužgová, R. Kozáková, M. Škutová, M. Bar, P. Ressner, P. Bártová

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Introduction: Currently, there has been an increasing concern about the provision of palliative care in non-oncological patients in both professional literature and clinical practice. However, there is not much scientific information on how to provide neurological and palliative care together. The main objective of the project is to create and to verify a concept of neuro-palliative and rehabilitative care for patients with selected neurological diseases in an advanced stage of the disease and also to evaluate bio-psychosocial and spiritual needs of these patients and their caregivers related to the quality of life using created standardized tools. Methodology: Triangulation of research methods (qualitative and quantitative) will be used. A concept of care and assessment tools will be developed by analyzing interviews and focus groups. Qualitative data will be analyzed using grounded theory. The concept of care will be tested in the context of the intervention study. Using quantitative analysis, we will assess the effect of an intervention provided on the saturation of needs, quality of life, and quality of care. A research sample will be made up of the patients with selected neurological diseases (Parkinson´s syndrome, motor neuron disease, multiple sclerosis, Huntington’s disease), together with patients´ family members. Based on the results, educational materials and a certified course for health care professionals will be created. Findings: Based on qualitative data analysis, we will propose the concept of integrated care model combining neurological, rehabilitative and specialist palliative care for patients with selected neurological diseases in different settings of care and services. Patients´ needs related to quality of life will be described by newly created and validated measuring tools before the start of intervention (application of neuro-palliative and palliative approach) and then in the time interval. Conclusion: Based on the results, educational materials and a certified course for doctors and health care professionals will be created.

Keywords: multidisciplinary approach, neuropalliative care, research, quality of life

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Eva Kirzner

Abstract:

Based on outcome studies published over the past two decades, in 2018, the ACC/AHA published new guidelines for the management of hypercholesterolemia that incorporate the use of coronary artery calcium (CAC) scanning as a decision tool for ascertaining which patients may benefit from statin therapy. This use is based on the recognition that the absence of calcium on CAC scanning (i.e., a CAC score of zero) usually signifies the absence of significant atherosclerotic deposits in the coronary arteries. Specifically, in patients with a high risk for atherosclerotic cardiovascular disease (ASCVD), initiation of statin therapy is generally recommended to decrease ASCVD risk. However, among patients with intermediate ASCVD risk, the need for statin therapy is less certain. However, there is a need for new outcome studies that provide evidence that the management of hypercholesterolemia based on these new ACC/AHA recommendations is safe for patients. Based on a Pub-Med and Google Scholar literature search, four relevant population-based or patient-based cohort studies that studied the relationship between CAC scanning, risk assessment or mortality, and statin therapy that were published between 2017 and 2021 were identified (see references). In each of these studies, patients were assessed for their baseline risk for atherosclerotic cardiovascular disease (ASCVD) using the Pooled Cohorts Equation (PCE), an ACC/AHA calculator for determining patient risk based on assessment of patient age, gender, ethnicity, and coronary artery disease risk factors. The combined findings of these four studies provided concordant evidence that a zero CAC score defines patients who remain at low clinical risk despite the non-use of statin therapy. Thus, these new studies confirm the use of CAC scanning as a safe tool for reducing the potential overuse of statin therapy among patients with zero CAC scores. Incorporating these new data suggest the following best practice: (1) ascertain ASCVD risk according to the PCE in all patients; (2) following an initial attempt trial to lower ASCVD risk with optimal diet among patients with elevated ASCVD risk, initiate statin therapy for patients who have a high ASCVD risk score; (3) if the ASCVD score is intermediate, refer patients for CAC scanning; and (4) and if the CAC score is zero among the intermediate risk ASCVD patients, statin therapy can be safely withheld despite the presence of an elevated serum cholesterol level.

Keywords: cholesterol, cardiovascular disease, statin therapy, coronary calcium

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Authors: Fanniyah Anis, Bram Kilapong

Abstract:

Myocardial reperfusion injury is defined as the cellular damage that results from a period of ischemia, followed by the reestablishment of the blood supply to the infarcted tissue. Ventricular tachycardia is one of the most commonly encountered reperfusion arrhythmia as one of the types of myocardial perfusion injury. Prompt and early treatment can reduce mortality, despite limited resources of the hospital in high risk patients with history of triple vessel disease. Case report, Male 53 years old has been diagnosed with NSTEMI with 3VD and comorbid disease of Hypertension and has undergone revascularization management with Percutaneous coronary intervention. Ventricular tachycardia leading to cardiac arrest occurred right after the stent was inserted. Resuscitation was performed for almost 2 hours until spontaneous circulation returned. Patient admitted in ICU with refractory cardiac shock despite using combination of ionotropic and vasopressor agents under standard non-invasive monitoring due to the limitation of the hospital. Angiography was performed again 5 hours later to exclude other possibilities of blockage of coronary arteries and conclude diagnosis of myocardial reperfusion injury. Patient continually managed with combination of antiplatelet agents and maintenance dose of anti-arrhythmia agents. The handling of the patient was to focus more on supportive and preventive from further deteriorating of the condition. Patient showed clinically improvement and regained consciousness within 24 hours. Patient was successfully discharged from ICU within 3 days without any neurological sequela and was discharge from hospital after 3 days observation in general ward. Limited Resource of hospital did not refrain the physician from attaining a good outcome for this myocardial reperfusion injury case and angiography alone can be used to confirm the diagnosis of myocardial reperfusion injury.

Keywords: limited resources hospital, myocardial reperfusion injury, prolonged resuscitation, refractory cardiogenic shock, reperfusion arrhythmia, revascularization, triple-vessel disease

Procedia PDF Downloads 304

Authors: Shreya Saxena

Abstract:

Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

Procedia PDF Downloads 98

Authors: Yaiprae Chatree, Tawan Chaiwon, Rodjana Chunhabundit, Kritsana Piriyawatcharakon, Waralai Ratwiset, Sasiwimol Chaiya

Abstract:

The world is facing a serious situation of aging society. Elderly may have many physical health problems due to degenerative diseases including Alzheimer’s disease. Riceberry rice relatively contain high levels of carbohydrate, vitamin E, -oryzanol, and also abundant of bioactive compound of anthocyanin. This study aimed to determine the inhibitory effect of Riceberry rice crude extract on acetylcholinesterase activity. The active compound was extracted by using 70% ethanol (v/v). The inhibitory effect of Riceberry rice on acetylcholinesterase was evaluated by using slightly modified method of Ellman’s method. The 120 seconds time interval of kinetics measurement showed that Riceberry rice extract at concentrations of 2.5-12.5 mg/ml presented the acetylcholinesterase inhibitory activity at the statistically significant difference at p  0.05 compared to control group over 60 -120 seconds. At the concentrations of 10 and 12.5 mg/ml of Riceberry rice extract expressed the high percentage of inhibitory activity of 50.86 and 71.22%, respectively. The half maximal inhibitory concentration (IC50) of acetylcholinesterase inhibitory activity of Riceberry rice extract; considered to the end point, was found at concentration of 9.34 mg/ml. The physostigmine (positive control); however, showed a higher inhibitory capacity than that of Riceberry rice extract. The inhibitory activity of the positive control group was around at 80.40 – 90.41%. In conclusion, the results of this study indicated that Riceberry rice extract possessed the inhibitory capacity of acetylcholinesterase activity. Moreover, at the concentrations of 12.5 mg/ml it showed the identical inhibitory effect with physostigmine group. The Riceberry rice extract might be able to alleviate the clinical manifestations of Alzheimer’s disease.

Keywords: acetylcholine, acetylcholinesterase, Alzheimer's disease, riceberry rice

Procedia PDF Downloads 216

Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

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A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

Procedia PDF Downloads 49

Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada

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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.

Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation

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Authors: Marziye Hadian, Alireza Jabbari

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Background: The World Health Organization has identified COVID-19 as a public health emergency and is urging governments to stop the virus transmission by adopting appropriate policies. In this regard, authorities have taken different approaches to cut the chain or controlling the spread of the disease. Now, the questions we are facing include what these approaches are? What tools should be used to implement each preventive protocol? In addition, what is the impact of each approach? Objective: The aim of this study was to determine the approaches to biological epidemics and related prevention tools with an emphasis on COVID-19 disease. Data sources: Databases including ISI web of science, PubMed, Scopus, Science Direct, Ovid, and ProQuest were employed for data extraction. Furthermore, authentic sources such as the WHO website, the published reports of relevant countries, as well as the Worldometer website were evaluated for gray studies. The time-frame of the study was from 1 December 2019 to 30 May 2020. Methods: The present study was a systematic study of publications related to the prevention strategies for the COVID-19 disease. The study was carried out based on the PRISMA guidelines and CASP for articles and AACODS for grey literature. Results: The study findings showed that in order to confront the COVID-19 epidemic, in general, there are three approaches of "mitigation", "active control" and "suppression" and four strategies of "quarantine", "isolation", "social distance" and "lockdown" in both individual and social dimensions to deal with epidemics. Selection and implementation of each approach requires specific strategies and has different effects when it comes to controlling and inhibiting the disease. Key finding: One possible approach to control the disease is to change individual behavior and lifestyle. In addition to prevention strategies, use of masks, observance of personal hygiene principles such as regular hand washing and non-contact of contaminated hands with the face, as well as an observance of public health principles such as sneezing and coughing etiquettes, safe extermination of personal protective equipment, must be strictly observed. Have not been included in the category of prevention tools. However, it has a great impact on controlling the epidemic, especially the new coronavirus epidemic. Conclusion: Although the use of different approaches to control and inhibit biological epidemics depends on numerous variables, however, despite these requirements, global experience suggests that some of these approaches are ineffective. The use of previous experiences in the world, along with the current experiences of countries, can be very helpful in choosing the accurate approach for each country in accordance with the characteristics of that country and lead to the reduction of possible costs at the national and international levels.

Keywords: novel corona virus, COVID-19, approaches, prevention tools, prevention strategies

Procedia PDF Downloads 127

Authors: V. A. Adzika, D. Ayim-Aboagye, T. Gordh

Abstract:

Background and aims: Prevalence of Sickle Cell Disease (SCD) is high in Ghana but not much is known in terms of research into non-medical strategies for managing and coping with the pain associated with SCD. This study was carried out to examine effective non-medical related strategies patients use to cope and manage their SCD condition. Methods: SCD patients (387) consisting of 180 males and 204 females between 18-65 years old years participated in the study. A cross-sectional research design was used in which participants completed questionnaires on pain, non-medical coping and management strategies, anxiety, and depression. Results of multiple regression analysis showed that socio-demographic characteristics contributed to the variance in the pain associated with SCD. Results: Over 90% of participants reported that pains associated with SCD were the main reason for seeking treatment in SCD crisis. In terms of non-medical related coping strategies, attending a place of worship and praying were the main coping strategies used in SCD crises, suggesting that patients’ beliefs, particularly in a supernatural being, served as a mitigating factor in the process of coping with the pain associated with SCD crisis. Also, avoidance and withdrawal from people and social activities were reported to be strategies used to cope effectively with the pain associated with SCD crisis. Conclusion: This indicates that it is imperative to incorporate non-medical related coping and management strategies, especially religious beliefs and psychosocial factors, to coping and management of the pain associated with SCD.

Keywords: anxiety, depression, sickle cell disease, quality of life, socio-demographic characteristics, Ghana

Procedia PDF Downloads 410