Search results for: complex genetic disorder

Authors: Kay-Anne Haykal, Issack Biyong

Abstract:

The post-traumatic stress disorder (PTSD) rises from exposure to a traumatic event and appears by a persistent experience of this event. Several psychiatric co-morbidities are associated with PTSD and include mood disorders, anxiety disorders, and substance abuse. The main objective was to compare the criteria for PTSD according to the literature to those used to diagnose a patient in a francophone hospital and to check the correspondence of these two criteria. 700 medical charts of admitted patients on the medicine or psychiatric unit at the Montfort Hospital were identified with the following diagnoses: major depressive disorder, bipolar disorder, anxiety disorder, substance abuse, and PTSD for the period of time between April 2005 and March 2006. Multiple demographic criteria were assembled. Also, for every chart analyzed, the PTSD criteria, according to the Manual of Mental Disorders (DSM) IV were found, identified, and grouped according to pre-established codes. An analysis using the receiver operating characteristic (ROC) method was elaborated for the study of data. A sample of 57 women and 50 men was studied. Age was varying between 18 and 88 years with a median age of 48. According to the PTSD criteria in the DSM IV, 12 patients should have the diagnosis of PTSD in opposition to only two identified in the medical charts. The ROC method establishes that with the combination of data from PTSD and depression, the sensitivity varies between 0,127 and 0,282, and the specificity varies between 0,889 and 0,917. Otherwise, if we examine the PTSD data alone, the sensibility jumps to 0.50, and the specificity varies between 0,781 and 0,895. This study confirms the presence of an underdiagnosed and treated PTSD that causes severe perturbations for the affected individual.

Keywords: post-traumatic stress disorder, co-morbidities, diagnosis, mental health disorders

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Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Annu Panghal, Bimla Dhanda

Abstract:

This research paper aims to determine the genetic-environment influences on the cognitive abilities of twins. Using the 100 pairs of twins from two districts, namely: Bhiwani (N = 90) and Hisar (N = 110) of Haryana State, genetic and environmental influences were assessed in twin study design. The cognitive abilities of twins were measured using the Wechsler Intelligence Scale for Children (WISC-R). Home Observation for Measurement of the Environment (HOME) Inventory was taken to examine the home environment of twins. Heritability estimate was used to analyze the genes contributing to shape the cognitive abilities of twins. The heritability estimates for cognitive abilities of 6-7 years old twins in Hisar district were 74% and in Bhiwani District 76%. Further the heritability estimates were 64% in the twins of Hisar district and 60 in Bhiwani district % in the age group of 7-8 years. The remaining variations in the cognitive abilities of twins were due to environmental factors namely: provision for Active Stimulation, paternal involvement, safe physical environment. The findings provide robust evidence that the cognitive abilities were more influenced by genes than the environmental factors and also revealed that the influence of genetic was more in the age group 6-7 years than the age group 7-8 years. The conclusion of the heritability estimates indicates that the genetic influence was more in the age group of 6-7 years than the age group of 7-8 years. As the age increases the genetic influence decreases and environment influence increases. Mother education was strongly associated with the cognitive abilities of twins.

Keywords: genetics, heritability, twins, environment, cognitive abilities

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Authors: Aspasia Simpsi

Abstract:

The aim of this study was to translate into Greek and then validate the psychometric properties of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) (Pontes & Griffiths, 2015). This is the first short standardized psychometric tool to assess Internet Gaming Disorder (IGD) according to the DSM-V nine clinical criteria and among the most frequently examined. The translation of the test was done through the process of back-translation. To gain a better insight into the psychometric properties of this test, the questionnaire included demographic questions and the Greek version of the Internet Addiction Test (Young, 1998). The participants of the study were 241 adolescents aged between 12 to 18. They were nationally recruited in Greece through an online survey that was hosted on the platform of Qualtrics. Analysis revealed excellent reliability with Cronbach’s alpha coefficients α = .939 for IGDS9-SF and α = .940 for IAT. The use of Pearson product-moment correlation revealed a significant positive relationship between IGDS9-SF and IAT r (241) =.45, p < .001. Due to inconsistencies in terminology and tests in the field of IGD, what is recommended for future research is a consensus regarding IGD testing and research.

Keywords: internet gaming disorder, IGDS9-SF, psychometric properties, internet addiction

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Authors: Dragos Dragomir-Stanciu, Leon Marsh

Abstract:

Background As a response to the gaps identified in recent research in the provision of residential care to address co-occurring health needs, including mental health problems and complexities Gamble Aware has facilitated the possibility to provide a new service which would extend the NGTS provision of residential rehabilitation for gambling disorder with complex and co-morbid presentation. Gordon Moody, together with Adferiad have been successful in securing the tender for this service and this presentation aims to introduce FOLD, the resulting model of treatment developed for the delivery of the service. Setting As a partnership, we have come together to coproduce a model which allows us to share our clinical and industry knowledge and build on our reputations as trusted treatment providers. The presentation will outline our expertise share in development of a unified approach to recovery-oriented models of care, clinical governance, risk assessment and management and aftercare and continuous recovery. We will also introduce our innovative specialist referral portal which will offer referring partners the ability to include the service user in planning their own recovery journey. Outcomes Our collaboration has resulted in the development of the FOLD model which includes three agile and flexible treatment packages aimed at offering the most enhanced and comprehensive treatment in UK, to date, for those most affected by gambling harm. The paper will offer insight into each treatment package and all recovery model stages involved, as well as into the partnership work with NGST providers, local mental health and social care providers and lived experience organisation that will enable us to offer support to more 100 people a year who would otherwise get “lost in the system”. Conclusion FOLD offers a great opportunity to develop, implement and evaluate a new, much needed, whole-person and whole-system approach to counter gambling related harms.

Keywords: gambling treatment, partnership working, integrated care pathways, NGTS, complex needs

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Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

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Authors: Latifa Sabri, Mohammed Benzirar, Mimoun Zazoui

Abstract:

The installation of photovoltaic systems is one of future sources to generate electricity without emitting pollutants. The photovoltaic cells used in these systems have demonstrated enormous efficiencies and advantages. Several researches have discussed the maximum efficiency of these technologies, but only a few experiences have succeeded to right weather conditions to get these results. In this paper, two types of cells were selected: crystalline and amorphous silicon. Using the method of genetic algorithm, the results show that for an ambient temperature of 25°C and direct irradiation of 625 W/m², the efficiency of crystalline silicon is 12% and 5% for amorphous silicon.

Keywords: PV, maximum efficiency, solar cell, genetic algorithm

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Authors: Renata Silva-Mann, Sheila Valéria Álvares Carvalho, Robério Anastácio Ferreira, Laura Jane Gomes

Abstract:

There is growing interest in defining indicators of sustainability, which are important for monitoring the conservation of native forests, particularly in areas of permanent protection. These indicators are references for assessing the state of the forest and the status of the depredated area and its ability to maintain species populations. The aim of the present study was to select genetic parameters as indicators of sustainability for Schinus terebinthifolius Raddi. Fragments located in riparian areas between the Sergipe and Alagoas States in Brazil. This species has been exploited for traditional communities, which represent 20% of the incoming. This study was carried out using the indicators suggested by the Organization for Economic Cooperation and Development, which were identified as Driving-Pressure-State-Impact-Response (DPSIR) factors. The genetic parameters were obtained in five populations located on the shores and islands of the São Francisco River, one of the most important rivers in Brazil. The framework for Schinus conservation suggests seventeen indicators of sustainability. In accordance with genetic parameters, the populations are isolated, and these genetic parameters can be used to monitor the sustainability of those populations in riparian area with the aim of defining strategies for forest restoration.

Keywords: alleles, molecular markers, genetic diversity, biodiversity

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Authors: Anthony John Walker, Glen Bright

Abstract:

The challenge faced by manufactures, when producing custom products, is that each product needs exact components. This can cause work-in-process instability due to component matching constraints imposed on assembly cells. Clearing type flow control policies have been used extensively in mediating server access between multiple arrival processes. Although the stability and performance of clearing policies has been well formulated and studied in the literature, the growth in arrival to departure sequence disorder for each arriving job, across a serving resource, is still an area for further analysis. In this paper, a closed form industrial model has been formulated that characterizes arrival-to-departure sequence disorder through stable manufacturing systems under clearing type flow control policy. Specifically addressed are the effects of sequence disorder imposed on a downstream assembly cell in terms of work-in-process instability induced through component matching constraints. Results from a simulated manufacturing system show that steady state average sequence disorder in parallel upstream processing cells can be balanced in order to decrease downstream assembly system instability. Simulation results also show that the closed form model accurately describes the growth and limiting behavior of average sequence disorder between parts arriving and departing from a manufacturing system flow controlled via clearing policy.

Keywords: assembly system constraint, custom products, discrete sequence disorder, flow control

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Authors: Mehrdad Rezaei, Reza Haghmaram, Nima Amjadi

Abstract:

This paper proposes an operating and cost optimization model for micro-grid (MG). This model takes into account emission costs of NOx, SO2, and CO2, together with the operation and maintenance costs. Wind turbines (WT), photovoltaic (PV) arrays, micro turbines (MT), fuel cells (FC), diesel engine generators (DEG) with different capacities are considered in this model. The aim of the optimization is minimizing operation cost according to constraints, supply demand and safety of the system. The proposed genetic algorithm (GA), with the ability to fine-tune its own settings, is used to optimize the micro-grid operation.

Keywords: micro-grid, optimization, genetic algorithm, MG

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Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

Abstract:

Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: J. G. Batista, K. N. Sousa, ¬J. L. Nunes, R. L. S. Sousa, G. A. P. Thé

Abstract:

This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Laura Rodrigues Carmona, Maria José Chambel, Vânia Sofia Carvalho

Abstract:

Background: In peacekeeping operations, military personnel are often exposed to the same traumatic stress factors found during conventional war and may also be subject to the physical risks and psychological stressors associated with posttraumatic stress disorder (PTSD). Objectives: To discuss the prevalence of PTSD among peacekeepers as well as the risks of and protective factors against this disorder and its comorbidities and/or consequences. Methods: A systematic literature search was performed with relevant keywords, and 53 articles were identified for this review. Results and conclusions: Military personnel deployed in peacekeeping operations have a higher prevalence of PTSD than nonmilitary personnel, a prevalence similar to that of military personnel deployed in war situations. Concerning the salient risk factors, the contextual factors are highlighted, and in regard to the protective factors, the individual factors are highlighted. This study thus demonstrates that there are factors in which the role of the military is essential, via both its selection and monitoring of peacekeepers during and after their deployment, to protect deployed personnel’s mental health.

Keywords: peacekeepers, peacekeeping, military, PTSD, post-traumatic stress disorder, posttraumatic stress disorder

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Authors: Mohammad Jalali Varnamkhasti

Abstract:

The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Boris Ershov

Abstract:

Depression is the most common mood disorder experienced by patients who have sustained a traumatic brain injury (TBI) and is associated with poorer cognitive functional outcomes. However, in some cases, similar cognitive impairments can also be observed in depression. There is not enough information about the features of the cognitive deficit in patients with TBI in relation to patients with depression. TBI patients without depressive symptoms (TBInD, n25), TBI patients with depressive symptoms (TBID, n31), and 28 patients with bipolar II disorder (BP) were included in the study. There were no significant differences in participants in respect to age, handedness and educational level. The patients clinical status was determined by using Montgomery–Asberg Depression Rating Scale (MADRS). All participants completed a cognitive battery (The Brief Assessment of Cognition in Affective Disorders (BAC-A)). Additionally, the Rey–Osterrieth Complex Figure (ROCF) was used to assess visuospatial construction abilities and visual memory, as well as planning and organizational skills. Compared to BP, TBInD and TBID showed a significant impairments in visuomotor abilities, verbal and visual memory. There were no significant differences between BP and TBID groups in working memory, speed of information processing, problem solving. Interference effect (cognitive inhibition) was significantly greater in TBInD and TBID compared to BP. Memory bias towards mood-related information in BP and TBID was greater in comparison with TBInD. These results suggest that depressive symptoms are associated with impairments some executive functions in combination at decrease of speed of information processing.

Keywords: bipolar II disorder, depression, neurocognitive deficits, traumatic brain injury

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Authors: Yunita Kurniawati

Abstract:

The aim of the research is to understand the influence of self concept on the tendency for body dysmorphic disorder among beauty salon and fitness centre customers in Malang. Subjects in this study amounted to 200 of beauty salon and fitness centre customers in Malang. Subjects completed a self-concept scale and the tendency of body dysmorphic scale. This study was analyzed using simple linear regression. The result shows that there are 14% influence of self concept on the tendency of body dysmorphic disorder among customers of beauty salon and fitness centre in Malang.

Keywords: self concept, tendency of body dysmorphic disorder, beauty salon and fitness centre customers, Malang

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Authors: Damaris Estrella Castillo, Zacil ha Vilchis Zapata, Leydi Peraza Gómez

Abstract:

Hearing loss is an etiologically heterogeneous condition, where almost 60% is genetic in origin, 20% is due to environmental factors, and 20% have unknown causes. However, it is now known that the gene, GJB2, which encodes the connexin 26 protein, accounts for a large percentage of non-syndromic genetic hearing loss, and variants in this gene have been identified to be a common cause of hereditary hearing loss in many populations. The literature reports that the etiology in deafness helps improve family functioning but low-income countries this is difficult. Therefore, it is difficult to contribute the right of families to know about the genetic risk in future pregnancies as well as determining the certainty of being a carrier or affected. In order to assess the impact of genetic counseling and the functionality, 100 families with at least one child with profound hearing loss, were evaluated by specialists in audiology, clinical genetics and psychology. Targeted mutation analysis for one of the two known large deletions of upstream of GJB2/GJB6 gene (35delG; and including GJB2 regulatory sequences and GJB6) were performed in patients with diagnosis of non-syndromic hearing loss. Genetic counseling was given to all parents and primary caregivers, and APGAR family test was applied before and after the counseling. We analyzed a total of 300 members (children, parents) to determine the presence of the GJB2 gene mutation. Twelve patients (carriers and affected) were positive for the mutation, from 5 different families. The subsequent family APGAR testing and genetic counseling, showed that 14% perceived their families as functional, 62 % and 24 % moderately functional dysfunctional. This shows the importance of genetic counseling in the perception of family function that can directly impact the quality of life of these families.

Keywords: family dynamics, deafness, APGAR, counseling

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Authors: I. Boroňová, J. Bernasovská, J. Kmec, E. Petrejčíková

Abstract:

Dilated cardiomyopathy (DCM) is a severe cardiovascular disorder characterized by progressive systolic dysfunction due to cardiac chamber dilatation and inefficient myocardial contractility often leading to chronic heart failure. Recently, a genome-wide association studies (GWASs) on DCM indicate that the ZBTB17 gene rs10927875 single nucleotide polymorphism is associated with DCM. The aim of the study was to identify the distribution of ZBTB17 gene rs10927875 polymorphism in 50 Slovak patients with DCM and 80 healthy control subjects using the Custom Taqman®SNP Genotyping assays. Risk factors detected at baseline in each group included age, sex, body mass index, smoking status, diabetes and blood pressure. The mean age of patients with DCM was 52.9±6.3 years; the mean age of individuals in control group was 50.3±8.9 years. The distribution of investigated genotypes of rs10927875 polymorphism within ZBTB17 gene in the cohort of Slovak patients with DCM was as follows: CC (38.8%), CT (55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT (5.0%). The risk allele T was more common among the patients with dilated cardiomyopathy than in normal controls (33.7% versus 30.6%). The differences in genotype or allele frequencies of ZBTB17 gene rs10927875 polymorphism were not statistically significant (p=0.6908; p=0.6098). The results of this study suggest that ZBTB17 gene rs10927875 polymorphism may be a risk factor for susceptibility to DCM in Slovak patients with DCM. Studies of numerous files and additional functional investigations are needed to fully understand the roles of genetic associations.

Keywords: ZBTB17 gene, rs10927875 polymorphism, dilated cardiomyopathy, cardiovascular disorder

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Authors: Kesavan Markkandan, Ha Young Park, Seung-Il Yoo, Sin-Gi Park, Junhyung Park

Abstract:

For genetic identification of crop cultivars, insertions/deletions (InDel) markers have been preferred currently because they are easy to use, PCR based, co-dominant and relatively abundant. However, new InDels need to be developed for genetic studies of new varieties due to the difference of allele frequencies in InDels among the population groups. These new varieties are evolved with low levels of genetic diversity in specific genome loci with high recombination rate. In this study, we described soybean barcode system approach based on InDel makers, each of which is specific to a variation block (VB), where the genomes split by all assumed recombination sites. Firstly, VBs in crop cultivars were mined for transferability to VB-specific InDel markers. Secondly, putative InDels in the VB regions were identified for the development of barcode system by analyzing particular cultivar’s whole genome data. Thirdly, common VB-specific InDels from all cultivars were selected by gel electrophoresis, which were converted as 2D barcode types according to comparing amplicon polymorphisms in the five cultivars to the reference cultivar. Finally, the polymorphism of the selected markers was assessed with other cultivars, and the barcode system that allows a clear distinction among those cultivars is described. The same approach can be applicable for other commercial crops. Hence, VB-based genetic identification not only minimize the molecular markers but also useful for assessing cultivars and for marker-assisted breeding in other crop species.

Keywords: variation block, polymorphism, InDel marker, genetic identification

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Authors: Ankush Kalra, Mirza Masroor, Usha Manaktala, B. C. Koner, T. K. Mishra

Abstract:

Introduction: Pre-eclampsia affects 3-5% of pregnancies worldwide and increases maternal-fetal morbidity and mortality. Reduced placental perfusion induces the release of biomolecules by the placenta into maternal circulation causing endothelial dysfunction. Zinc dependent matrix metalloproteinase-2 (MMP-2) may be up-regulated and interact with circulating factors of oxidative stress and inflammation to produce endothelial dysfunction in pre-eclampsia. Aim: To study the functional genetic polymorphism of MMP-2 gene (g-1306 C>T) in pre-eclampsia and its effect on serum MMP-2 levels in these patients. Method: Hundred pre-eclampsia patients and hundred age and gestation period matched healthy pregnant women with their consent were recruited in the study. Serum MMP-2 levels in all subjects were estimated using standard ELISA kits. MMP-2 gene (g.- 1306 C>T) SNPs were genotyped using whole blood by ASO-PCR. Result: The pre-eclampsia patients had higher serum levels of MMP-2 compared to the healthy pregnant (p < 0.05). Also the MMP-2 genotype was associated with significant alteration in the serum MMP-2 concentration in these patients (p < 0.05). Conclusion: This study results suggest an association of MMP-2 genetic polymorphism and serum levels of MMP-2 to the path physiology of hypertensive disorder of pregnancy.

Keywords: allele specific oligonucleotide polymerase chain reaction (ASO-PCR), enzyme linked immunosorbent assay (ELISA), matrix metalloproteinase-2 (MMP-2), pre-eclampsia

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Rita Alfattal, Maryam Alfarhan, Adeeb M. Algaith, Buthaina Albash, Reem M. Elshafie, Asma Alshammari, Ahmad Alahmad, Fatima Dashti, Rasha Alsafi, Hind Alsharhan

Abstract:

Defects of respiratory chain complex III (CIII) result in characteristic but rare mitochondrial disorders associated with distinct neuroradiological findings. The underlying molecular defects affecting mitochondrial CIII assembly factors are few and yet to be identified. LYRM7 assembly factor is required for proper CIII assembly where it acts as a chaperone for the Rieske iron‐sulfur (UQCRFS1) protein in the mitochondrial matrix and stabilizing it. We present here the seventeenth individual with LYRM7-associated mitochondrial leukoencephalopathy harboring a previously reported rare pathogenic homozygous LYRM 7 variant, c.2T>C, (p.Met1?). Like previously reported individuals, our 4-year-old male proband presented with recurrent metabolic and lactic acidosis, encephalopathy, and myopathy. Further, he has additional, previously unreported features, including an acute stroke like episode with bilateral central blindness and optic neuropathy, recurrent hyperglycemia and hypertension associated with metabolic crisis. However, he has no signs of psychomotor regression. He has been stable clinically with residual left-sided reduced visual acuity and amblyopia, and no more metabolic crises for 2-year-period while on the mitochondrial cocktail. Although the reported brain MRI findings in other affected individuals are homogenous, it is slightly different in our index, revealing evidence of bilateral almost symmetric multifocal periventricular T2 hyperintensities with hyperintensities of the optic nerves, optic chiasm, and corona radiata but with no cavitation or cystic changes. This report describes new clinical and radiological findings of LYRM7-associated disease. The report also summarizes the clinical and molecular data of previously reported individuals describing the full phenotypic spectrum.

Keywords: LYRM7 gene defect, mitochondrial disease, , lactic acidosis, , genetic disorder

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Authors: Annabel Burnley, Michelle St. Clair, Charlotte Dack, Yvonne Wren

Abstract:

Children with Developmental Language Disorder (DLD) are well documented to experience social and emotional difficulties. Despite this, there is little consensus as to how these difficulties manifest, without which the ability to develop prevention initiatives is limited. An online survey was completed by 107 parents of either child with DLD (‘DLD sample’; n=57), or typically developing children (‘typical sample’; n=50), all aged 6-12 years old. Psychosocial symptom measures were used, alongside 11 psychosocial statements generated from previous qualitative work. Qualitative interviews were then held to understand the manifestation of key difficulties in more depth (n=4). The DLD sample scored significantly higher on all psychosocial statements than the typical sample. Experiencing anxiety (80.7%), requiring routine and sameness (75.4%) and struggling to regulate their emotions (75.4%) were the most common difficulties for a majority of children with DLD. For this DLD sample, family communication and coping styles were found not to contribute to the manifestation of these difficulties. Two separate mediation models were run to understand the role of other psychosocial difficulties in the manifestation of (1) anxiety and (2) social frustration. ‘Intolerance of uncertainty was found to strongly mediate the relationship between DLD diagnosis and symptoms of anxiety. Emotion regulation was found to moderately mediate the relationship between DLD diagnosis and social frustration. Parents appear to cope well with their children’s complex psychosocial needs, but further external intervention is needed. Intervention focussing on intolerance of uncertainty and emotion dysregulation may help the management of anxiety and social frustration. Further research is needed to understand the children’s routined behaviors.

Keywords: psychosocial difficulties, developmental language disorder, specific language impairment, parent, anxiety

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Authors: Stephanie Zuba-Bates

Abstract:

Purpose: This qualitative research study explored the lived experience of people with functional movement disorder (FMD) including how it impacts their quality of life and participation in life activities. It aims to educate health care professionals about FMD from the perspective of those living with the disorder. Background: Functional movement disorder is characterized by abnormal motor movements including tremors, abnormal gait, paresis, and dystonia with no known underlying pathophysiological cause. Current research estimates that FMD may account for 2-20% of clients seen by neurologists. Getting a diagnosis of FMD is typically long and difficult. In addition, many healthcare professionals are unfamiliar with the disorder which may delay treatment. People living with FMD face great disruption in major areas of life including activities of daily living (ADLs), work, leisure, and community participation. OT practitioners have expertise in working with people with both physical disabilities as well as mental illness and this expertise has the potential to guide treatment and become part of the standard of care. In order for occupational therapists to provide these services, they must be aware of the disorder and must advocate for clients to be referred to OT services. In addition, referring physicians and other health professionals need to understand how having FMD impacts the daily functioning of people living with the disorder and how OT services can intervene to improve their quality of life. This study aimed to answer the following research questions: 1) What is the lived experience of individuals with FMD?; 2) How has FMD impacted their participation in major areas of life?; and, 3) What treatment have they found to be effective in improving their quality of life? Method: A naturalistic approach was used to collect qualitative data through semi-structured telephone interviews of five individuals living with FMD. Subjects were recruited from social media websites and resources for people with FMD. Data was analyzed for common themes among participants. Results: Common themes including the variability of symptoms of the disorder; challenges to receiving a diagnosis; frustrations with and distrust of health care professionals; the impact of FMD on the participant’s ability to perform daily activities; and, strategies for living with the symptoms of FMD. Conclusion: All of the participants in the study had to modify their daily activities, roles and routines as a result of the disorder. This is an area where occupational therapists may intervene to improve the quality of life of these individuals. Additionally, participants reported frustration with the medical community regarding the awareness of the disorder and how they were treated by medical professionals. Much more research and awareness of the disorder is in order.

Keywords: functional movement disorder, occupational therapy, participation, quality of life

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Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Parsa Sheikhzadeh

Abstract:

Polar bodies are cells that form by oogenesis in meiosis which differentiate and develop from oocytes. Although in many animals, these cells often die following meiotic maturation of the oocyte. Oocyte activation is during mammalian fertilization, sperm is fused with the oocyte's membrane, triggering the resumption of meiosis from the metaphase II arrest, the extrusion of the second polar body, and the exocytosis of cortical granules. The origin recognition complex proteins 4 (ORC4) forms a cage around the set of chromosomes that will be extruded during polar body formation before it binds to the chromatin shortly before zygotic DNA replication. One unique feature of the female gamete is that the polar bodies can provide beneficial information about the genetic background of the oocyte without potentially destroying it. Testing at the polar body (PB) stage was the least accurate, mainly due to the high incidence of post-zygotic events. On the other hand, the results from PB1-MII oocyte pair validated that PB1 contains nearly the same methylome (average Pearson correlation is 0.92) with sibling MII oocyte. In this article, we comprehensively examine the role of polar bodies in female human gametes.

Keywords: polar bodies, ORC4, oocyte, genetic, methylome, gamete, female

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Authors: M. D. Antoine

Abstract:

When a child is diagnosed with an illness, condition, or developmental disorder, the process involved in understanding and accepting this diagnosis can be a very stressful and isolating experience for parents and families. The healthcare providers’ ability to effectively communicate in such situations represents a vital lifeline for parents. In this context, communication becomes a crucial element not only for getting through the period of grief but also for the future. We mobilized the five stages of grief model to summarize existing literature regarding the ways in which the experience ofan autism spectrum disorder diagnosis disclosurealigns with the experience of grief to explore how this can inform best practices for effective communication with parents through the diagnosis disclosure. Fifteen publications met inclusion criteria. Findings from the scoping review of empirical studies show that parents/families experience grief-like emotions during the diagnosis disclosure. However, grief is not an outcome of the encounter itself. In fact, the experience of the encounter can help mitigate the grief experience. The way parents/families receive and react to the ‘news’ depends on their preparedness, knowledge, and the support received through the experience. Individual communication skills, as well as policies and regulations, should be examined to alleviate adverse reactions in this context. These findings highlight the importance of further research into effective parent-provider communication strategies and their place in supporting quality autism care.

Keywords: autism spectrum disorder, autism spectrum disorder diagnosis, diagnosis disclosure, parent-provider communication, parental grief

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

Abstract:

This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Mehdi Rostamzadeh

Abstract:

Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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