Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3948

Search results for: metabolic network

3948 Exploring Research Trends and Topics in Intervention on Metabolic Syndrome Using Network Analysis

Authors: Lee Soo-Kyoung, Kim Young-Su


This study established a network related to metabolic syndrome intervention by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. It visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in metabolic syndrome intervention measures used in studies conducted over 38 years (1979–2017). It examined a collection of keywords from 8,285 studies using text rank analyzer, NetMiner 4.0. The analysis revealed 5 groups of newly emerging keywords in the research. By examining the relationship between keywords with reference to their betweenness centrality, the following clusters were identified. Thus if new researchers refer to existing trends to establish the subject of their study and the direction of the development of future research on metabolic syndrome intervention can be predicted.

Keywords: intervention, metabolic syndrome, network analysis, research, the trend

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3947 Effect of Variable Fluxes on Optimal Flux Distribution in a Metabolic Network

Authors: Ehsan Motamedian


Finding all optimal flux distributions of a metabolic model is an important challenge in systems biology. In this paper, a new algorithm is introduced to identify all alternate optimal solutions of a large scale metabolic network. The algorithm reduces the model to decrease computations for finding optimal solutions. The algorithm was implemented on the Escherichia coli metabolic model to find all optimal solutions for lactate and acetate production. There were more optimal flux distributions when acetate production was optimized. The model was reduced from 1076 to 80 variable fluxes for lactate while it was reduced to 91 variable fluxes for acetate. These 11 more variable fluxes resulted in about three times more optimal flux distributions. Variable fluxes were from 12 various metabolic pathways and most of them belonged to nucleotide salvage and extra cellular transport pathways.

Keywords: flux variability, metabolic network, mixed-integer linear programming, multiple optimal solutions

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3946 Integration of Microarray Data into a Genome-Scale Metabolic Model to Study Flux Distribution after Gene Knockout

Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati


Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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3945 Hypergraph Models of Metabolism

Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova


In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterize a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: complexity, hypergraphs, reciprocity, metabolism

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3944 Microbial Bioproduction with Design of Metabolism and Enzyme Engineering

Authors: Tomokazu Shirai, Akihiko Kondo


Technologies of metabolic engineering or synthetic biology are essential for effective microbial bioproduction. It is especially important to develop an in silico tool for designing a metabolic pathway producing an unnatural and valuable chemical such as fossil materials of fuel or plastics. We here demonstrated two in silico tools for designing novel metabolic pathways: BioProV and HyMeP. Furthermore, we succeeded in creating an artificial metabolic pathway by enzyme engineering.

Keywords: bioinformatics, metabolic engineering, synthetic biology, genome scale model

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3943 Identifying Metabolic Pathways Associated with Neuroprotection Mediated by Tibolone in Human Astrocytes under an Induced Inflammatory Model

Authors: Daniel Osorio, Janneth Gonzalez, Andres Pinzon


In this work, proteins and metabolic pathways associated with the neuroprotective response mediated by the synthetic neurosteroid tibolone under a palmitate-induced inflammatory model were identified by flux balance analysis (FBA). Three different metabolic scenarios (‘healthy’, ‘inflamed’ and ‘medicated’) were modeled over a gene expression data-driven constructed tissue-specific metabolic reconstruction of mature astrocytes. Astrocyte reconstruction was built, validated and constrained using three open source software packages (‘minval’, ‘g2f’ and ‘exp2flux’) released through the Comprehensive R Archive Network repositories during the development of this work. From our analysis, we predict that tibolone executes their neuroprotective effects through a reduction of neurotoxicity mediated by L-glutamate in astrocytes, inducing the activation several metabolic pathways with neuroprotective actions associated such as taurine metabolism, gluconeogenesis, calcium and the Peroxisome Proliferator Activated Receptor signaling pathways. Also, we found a tibolone associated increase in growth rate probably in concordance with previously reported side effects of steroid compounds in other human cell types.

Keywords: astrocytes, flux balance analysis, genome scale metabolic reconstruction, inflammation, neuroprotection, tibolone

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3942 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation

Authors: Vishwesh Kulkarni, Nikhil Bellarykar


Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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3941 Metabolic Syndrome among Some Originates of Mbo Ethnic Group Living in Yaounde-Cameroon

Authors: Mandob Enyegue Damaris, Oko Ndjollo Viviane


The prevalence of Metabolic Syndrome is increasing throughout the world. The etiology of the metabolic syndrome is dependent on different factors such as ethnic group. This study aimed to evaluate the metabolic syndrome among Mbo ethnic group people leaving in Yaounde, Cameroon. The study conducted on the hundred and thirty two people 40 men and 92 women aged between 18-60 years who were referred to the Andre Fouda Medical Fundation in Yaounde. Metabolic syndrome was diagnosed using Adult Treatment Panel-III (A.T.P-III) 2001 guidelines. The mean of age, high fasting blood glucose, triglycerides levels and total cholesterol levels were significantly (P<0.05) higher in women with metabolic syndrome. High blood pressure level (56.80%), high fasting glucose (20.45%) and high waist circumference (10.60%) were respectively the most frequent characteristics in comparison to others metabolic components. The overall prevalence of MetS was (4.55%) and higher in women (3.03%) than in men (1.52%). The prevalence of MetS is low in originates of Mbo ethnic group of Yaounde. High blood pressure is the most common abnormality.

Keywords: individual components, metabolic syndrome, Mbo ethnic group, Yaounde-Cameroon

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3940 Metagenomics Features of The Gut Microbiota in Metabolic Syndrome

Authors: Anna D. Kotrova, Alexandr N. Shishkin, Elena I. Ermolenko


The aim. To study the quantitative and qualitative colon bacteria ratio from patients with metabolic syndrome. Materials and methods. Fecal samples from patients of 2 groups were identified and analyzed: the first group was formed by patients with metabolic syndrome, the second one - by healthy individuals. The metagenomics method was used with the analysis of 16S rRNA gene sequences. The libraries of the variable sites (V3 and V4) gene 16S RNA were analyzed using the MiSeq device (Illumina). To prepare the libraries was used the standard recommended by Illumina, a method based on two rounds of PCR. Results. At the phylum level in the microbiota of patients with metabolic syndrome compared to healthy individuals, the proportion of Tenericutes was reduced, the proportion of Actinobacteria was increased. At the genus level, in the group with metabolic syndrome, relative to the second group was increased the proportion of Lachnospira. Conclusion. Changes in the colon bacteria ratio in the gut microbiota of patients with metabolic syndrome were found both at the type and the genus level. In the metabolic syndrome group, there is a decrease in the proportion of bacteria that do not have a cell wall. To confirm the revealed microbiota features in patients with metabolic syndrome, further study with a larger number of samples is required.

Keywords: gut microbiota, metabolic syndrome, metagenomics, tenericutes

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3939 Reduction in the Metabolic Cost of Human Walking Gaits Using Quasi-Passive Upper Body Exoskeleton

Authors: Nafiseh Ebrahimi, Gautham Muthukumaran, Amir Jafari


Human walking gait is considered to be the most efficient biped walking gait. There are various types of gait human follows during locomotion and arm swing is one of the most important factors which controls and differentiates human gaits. Earlier studies declared a 7% reduction in the metabolic cost due to the arm swing. In this research, we compared different types of arm swings in terms of metabolic cost reduction and then suggested, designed, fabricated and tested a quasi-passive upper body exoskeleton to study the metabolic cost reduction in the folded arm walking gate scenarios. Our experimental results validate a 10% reduction in the metabolic cost of walking aided by the application of the proposed exoskeleton.

Keywords: arm swing, MET (metabolic equivalent of a task), calorimeter, oxygen consumption, upper body quasi-passive exoskeleton

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3938 Quantified Metabolomics for the Determination of Phenotypes and Biomarkers across Species in Health and Disease

Authors: Miroslava Cuperlovic-Culf, Lipu Wang, Ketty Boyle, Nadine Makley, Ian Burton, Anissa Belkaid, Mohamed Touaibia, Marc E. Surrette


Metabolic changes are one of the major factors in the development of a variety of diseases in various species. Metabolism of agricultural plants is altered the following infection with pathogens sometimes contributing to resistance. At the same time, pathogens use metabolites for infection and progression. In humans, metabolism is a hallmark of cancer development for example. Quantified metabolomics data combined with other omics or clinical data and analyzed using various unsupervised and supervised methods can lead to better diagnosis and prognosis. It can also provide information about resistance as well as contribute knowledge of compounds significant for disease progression or prevention. In this work, different methods for metabolomics quantification and analysis from Nuclear Magnetic Resonance (NMR) measurements that are used for investigation of disease development in wheat and human cells will be presented. One-dimensional 1H NMR spectra are used extensively for metabolic profiling due to their high reliability, wide range of applicability, speed, trivial sample preparation and low cost. This presentation will describe a new method for metabolite quantification from NMR data that combines alignment of spectra of standards to sample spectra followed by multivariate linear regression optimization of spectra of assigned metabolites to samples’ spectra. Several different alignment methods were tested and multivariate linear regression result has been compared with other quantification methods. Quantified metabolomics data can be analyzed in the variety of ways and we will present different clustering methods used for phenotype determination, network analysis providing knowledge about the relationships between metabolites through metabolic network as well as biomarker selection providing novel markers. These analysis methods have been utilized for the investigation of fusarium head blight resistance in wheat cultivars as well as analysis of the effect of estrogen receptor and carbonic anhydrase activation and inhibition on breast cancer cell metabolism. Metabolic changes in spikelet’s of wheat cultivars FL62R1, Stettler, MuchMore and Sumai3 following fusarium graminearum infection were explored. Extensive 1D 1H and 2D NMR measurements provided information for detailed metabolite assignment and quantification leading to possible metabolic markers discriminating resistance level in wheat subtypes. Quantification data is compared to results obtained using other published methods. Fusarium infection induced metabolic changes in different wheat varieties are discussed in the context of metabolic network and resistance. Quantitative metabolomics has been used for the investigation of the effect of targeted enzyme inhibition in cancer. In this work, the effect of 17 β -estradiol and ferulic acid on metabolism of ER+ breast cancer cells has been compared to their effect on ER- control cells. The effect of the inhibitors of carbonic anhydrase on the observed metabolic changes resulting from ER activation has also been determined. Metabolic profiles were studied using 1D and 2D metabolomic NMR experiments, combined with the identification and quantification of metabolites, and the annotation of the results is provided in the context of biochemical pathways.

Keywords: metabolic biomarkers, metabolic network, metabolomics, multivariate linear regression, NMR quantification, quantified metabolomics, spectral alignment

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3937 Elucidation of the Sequential Transcriptional Activity in Escherichia coli Using Time-Series RNA-Seq Data

Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani


Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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3936 Flux Balance Network Expansion Predicts Stage-Specific Human Preimplantation Embryo Metabolism

Authors: Andisheh Dadashi, Derek Martinez


Metabolism is an essential cellular process for the growth and maintenance of organisms. A better understanding of metabolism during embryogenesis may shed light on the developmental origins of human disease. Metabolic networks, however, are vastly complex with many redundant pathways and interconnected circuits. Thus, computational approaches serve as a practical solution for unraveling the genetic basis of embryo metabolism to help guide future experimental investigations. To our knowledge, this study presents the first model of human peri-implantation embryo metabolism via flux balance network expansion. The model accounts for 8 separate reaction compartments (extracellular, peroxisome, mitochondria, cytosol, lysosome, endoplasmic reticulum, Golgi apparatus, nucleus) including transport and exchange reactions between compartments. We found that modulating oxygen uptake promotes lactate diffusion across the outer mitochondrial layer, providing in silico support for a proposed lactate-malate-aspartate shuttle. While RNA-sequencing and other profiling technologies make it possible to elucidate metabolic genotype-phenotype relationships; yet, our understanding of metabolism during early mammalian development is currently limited. Very few studies have examined the temporal or spatial metabolomics of the human embryo, and prohibitively small sample sizes traditionally observed in human embryo research have presented logistical challenges for metabolic flux studies, hindering progress towards the reconstruction of the human embryonic metabolome. Thus, we developed a stage-specific model to serve as a proof-of-concept for the reconstruction of future metabolic developmental models. Our work shows that it is feasible to model human metabolism with respect to time-dependent changes characteristic of peri-implantation development.

Keywords: human peri-implantation embryo metabolism, flux balance analysis, network expansion, pathway analysis.

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3935 Gender Difference in the Association between Different Components of the Metabolic Syndrome and Vitamin D Levels in Saudi Patients

Authors: Amal Baalash, Shazia Mukaddam, M. Adel El-Sayed


Background: Several studies have suggested non-skeletal effects of vitamin D and linked its deficiency with features of many chronic conditions. In this study, We aimed to investigate the relationship between vitamin D levels and different components of the metabolic syndrome in male and female Saudi patients. Methods: the study population consisted of 111 patients with metabolic syndrome (71 females and 40 males) aged 37-63 years enrolled from patients attending the internal medicine outpatient clinics of King Fahad Medical City. The parameters for diagnosis of the metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) were measured, which included waist circumference, TG, HDL-C, Blood pressure and fasting blood glucose (FBS). The association between each parameter and serum 25-hydroxyvitamin D (25(OH) D) was studied in both male and female patients separately. Results: in male patients, 25(OH) D levels were inversely associated with FBS and TG and positively associated with HDL-C and diastolic blood pressure, With highest association with the HDL-C levels. On the other hand 25(OH) D, Showed no significant association with any of the measured metabolic syndrome parameters in female patients. Conclusion: in Saudi patients with metabolic syndrome, the association between the parameters of metabolic syndrome and the levels of 25 (OH) D is more pronounced in males rather than females.

Keywords: gender, metabolic syndrome, Saudi patients, vitamin D

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3934 Comparing of Hypogonadism Frequency between Metabolic Syndrome Men with Normal Men

Authors: Armaghan Moravej Aleali, Seyed Bahman Ghaderian, Homeira Rashidi, Mahmoud Mapar


Background and Objective The metabolic syndrome (MetS) is considered the most important public health threat of the 21st century. This syndrome is characterized by a cluster of cardiovascular risk factors including increased central abdominal obesity, elevated triglycerides, reduced high-density lipoprotein, high blood pressure, increased fasting glucose, and hyperinsulinemia. MetS has been associated with hypogonadism and erectile dysfunction (ED), and MetS may be considered a risk factor for ED. The aim of this study was finding an association between metabolic syndrome and hypogonadism in Khouzestan, Iran. Subjects and Methods: In this study, 60 patients divided into two groups consisted of 30 cases (with metabolic syndrome) and 30 controls. Total and free Serum Testosterone and FBS in all of them were measured. Data was analyzed with SPSS20 program. Results: There was a significant difference between two groups about free Testosterone (P=0.01), FBS (P=0.002) and LH (P=0.03). Conclusion: According to this finding, it is thought the prevalence of hypogonadism in men with metabolic syndrome is more than the general population.

Keywords: metabolic syndrome, fasting blood sugar, hypogonadism, testosterone

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3933 Prevalence of Metabolic Syndrome According to Different Criteria in Population over 20 Years Old in Ahvaz

Authors: Armaghan Moravej Aleali, Hajieh Shahbazian, Seyed Mahmoud Latifi, Leila Yazdanpanah


Objective: Metabolic syndrome or insulin resistance syndrome or syndrome X is a collection of abdominal obesity, hypertension, glucose intolerance and lipid abnormalities (elevated triglycerides, elevated LDL, and decrease the amount of HDL). That increases the incidence of diabetes and risk of cardiovascular disease. The aim of this study is to investigate the prevalence of metabolic syndrome in people over 20 years of Ahvaz according to IDF, ATPIII, Harmonized I and Harmonized II. Material & Methods: A cross-sectional study with a random cluster sampling in six health centers in Ahvaz was done. After obtaining informed consent, questionnaire for each person filled up including demographic data and examinations, including blood pressure in sitting position, weight, height, waist circumference, and waist circumference measurement. Results: From all participating 912 people, (434 (2/47%) male and 478 (2/52%) female) were evaluated. Mean age was 42/27± 14years (44/2±14/26 for male and 40/5±13/5 for female). Prevalence of metabolic syndrome was 22/8%, 28/4%, 30/9% and 16/9% according to ATPIII, IDF, Harmonized I and Harmonized II criteria respectively and increased with age in both sexes. IDF and Harmonized I had most kappa coordination (0/94). Conclusion: The results show a high prevalence of metabolic syndrome in Ahvaz. So, identification of the risk factors should be attempted to prevent metabolic syndrome.

Keywords: metabolic syndrome, IDF, ATP III, prevalence

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3932 Nutrition Intervention for Spinal Cord Injury in Critical Care

Authors: Dina Muharib


Specific metabolic challenges are present following spinal cord injury. The acute stage is characterized by a reduction in metabolic activity, as well as a negative nitrogen balance that cannot be corrected, even with aggressive nutritional support. Metabolic demands need to be accurately monitored to avoid overfeeding. Enteral feeding is the optimal route following SCI. When oral feeding is not possible, nasogastric, followed by nasojejunal, then by percutaneous endoscopic gastrostomy, if necessary, is suggested.

Keywords: SCI, energy, protein, nutrition assessment, eneral feeding, nitrogen balance

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3931 Metabolic Cost and Perceived Exertion during Progressive and Randomized Walking Protocols

Authors: Simeon E. H. Davies


This study investigated whether selected metabolic responses and the perception of effort varied during four different walk protocols where speed increased progressively 3, 4, 5, 6, and 7 km/hr (progressive treadmill walk (PTW); and progressive land walk (PLW); or where the participant adjusted to random changes of speed e.g. 6, 3, 7, 4, and 5 km/hr during a randomized treadmill walk (RTW); and a randomized land walk (RLW). Mean stature and mass of the seven participants was 1.75m and 70kg respectively, with a mean body fat of 15%. Metabolic measures including heart rate, relative oxygen uptake, ventilation, increased in a linear fashion up to 6 km/hr, however at 7 km/hr there was a significant increase in metabolic response notably during the PLW, and to a similar, although lesser extent in RLW, probably as a consequence of the loss of kinetic energy when turning at each cone in order to maintain the speed during each shuttle. Respiration frequency appeared to be a more sensitive indicator of physical exertion, exhibiting a rapid elevation at 5 km/hr. The perception of effort during each mode and at each speed was largely congruent during each walk protocol.

Keywords: exertion, metabolic, progressive, random, walking

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3930 Prevalence of Metabolic Syndrome among Adult Obese Type 2 Diabetic Subjects

Authors: Mehwish Azam, Muhammad Imran, Humaira Jabeen, Sumreen Begum, Rashida Qasim


Background: Metabolic syndrome is a cluster of metabolic risk factors including obesity, glucose intolerance, insulin resistance, dyslipidemia and hypertension. Metabolic syndrome in obese and type 2 diabetic subjects increases the risk of cardiovascular diseases (CVD). Globally, the prevalence of metabolic syndrome ranges from 10%-50% and in Pakistan ranges from 18%-46%. The objective of the present study is to estimate the prevalence of metabolic syndrome (MS) in obese type 2 diabetic subjects by using International Diabetes Federation (IDF) and National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) definitions. Methods: Obese type 2 diabetic subjects and normal healthy subjects of both genders were selected from diabetic clinics and hospitals of various localities of Karachi, Pakistan. The frequency of metabolic syndrome was estimated by the proposed definitions of IDF and NCEP-ATP III. Results: The prevalence of metabolic syndrome using International Diabetes Federation (IDF) definition in obese type 2 diabetic subjects was 85.7%. It is significantly higher (p<0.05) in females (47.1%) as compared to males (38.6%). While, using National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) definition the overall prevalence of metabolic syndrome in obese type 2 diabetic subjects was 75.7%, the prevalence is significantly higher (p<0.05) in females (45.7%) than males (30.0%). Conclusion: It is concluded that, the overall prevalence of metabolic syndrome is increasing significantly in obese type 2 diabetic subjects by using IDF and NCEP–ATP III definitions. Therefore, it is need to initiate the preventive measures by arranging public awareness programmes to highlight the significance of a healthy lifestyle and emphasis should be given to reduce weight, increase physical activity, and increase intake of healthy low-glycemic-index foods.

Keywords: metabolic syndrome, diabetes mellitus, obesity, IDF, NCEP-ATP III

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3929 Screening of Risk Phenotypes among Metabolic Syndrome Subjects in Adult Pakistani Population

Authors: Muhammad Fiaz, Muhammad Saqlain, Abid Mahmood, S. M. Saqlan Naqvi, Rizwan Aziz Qazi, Ghazala Kaukab Raja


Background: Metabolic Syndrome is a clustering of multiple risk factors including central obesity, hypertension, dyslipidemia and hyperglycemia. These risk phenotypes of metabolic syndrome (MetS) prevalent world-wide, Therefore we aimed to identify the frequency of risk phenotypes among metabolic syndrome subjects in local adult Pakistani population. Methods: Screening of subjects visiting out-patient department of medicine, Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad was performed to assess the occurrence of risk phenotypes among MetS subjects in Pakistani population. The Metabolic Syndrome was defined based on International Diabetes Federation (IDF) criteria. Anthropometric and biochemical assay results were recorded. Data was analyzed using SPSS software (16.0). Results: Our results showed that dyslipidemia (31.50%) and hyperglycemia (30.50%) was most population specific risk phenotypes of MetS. The results showed the order of association of metabolic risk phenotypes to MetS as follows hyperglycemia>dyslipidemia>obesity >hypertension. Conclusion: The hyperglycemia and dyslipidemia were found be the major risk phenotypes among the MetS subjects and have greater chances of deceloping MetS among Pakistani Population.

Keywords: dyslipidemia, hypertention, metabolic syndrome, obesity

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3928 Prevalence and Risk Factors of Metabolic Syndrome in Adults of Terai Region of Nepal

Authors: Birendra Kumar Jha, Mingma L. Sherpa, Binod Kumar Dahal


Background: The metabolic syndrome is emerging as a major public health concern in the world. Urbanization, surplus energy uptake, compounded by decreased physical activities, and increasing obesity are the major factors contributing to the epidemic of metabolic syndrome worldwide. However, prevalence of metabolic syndrome and its risk factors are little studied in Terai region of Nepal. The objectives of this research were to estimate the prevalence and to identify the risk factors of metabolic syndrome among adults in Terai region of Nepal. Method: We used a community based cross sectional study design. A total of 225 adults (age: 18 to 80 years) were selected from three district of Terai region of Nepal using cluster sampling by camp approach. IDF criteria (central obesity with any two of following four factors: triglycerides ≥ 150 mg/dl or specific treatment for lipid abnormality, reduced HDL, raised blood pressure and raised fasting plasma glucose or previously diagnosed type 2 diabetes) were used to assess metabolic syndrome. Interview, physical and clinical examination, measurement of fasting blood glucose and lipid profile were conducted for all participants. Chi-square test and multivariable logistic regression were employed to explore the risk factors of metabolic syndrome. Result: The overall prevalence of metabolic syndrome was 70.7%. Hypertension, increased fasting blood sugar, increased triglycerides and decreased HDL were observed in 50.7%, 32.4%, 41.8% and 79.1% of the subjects respectively. Socio-economic and behavioral risk factors significantly associated with metabolic syndrome were gender male (OR=2.56, 955 CI: 1.42-4.63; p=0.002), in service or retired from service (OR=3.72, 95% CI: 1.72-8.03; p=0.001) and smoking (OR= 4.10, 95% CI: 1.19-14.07; p=0.016). Conclusion: Higher prevalence of Metabolic syndrome along with presence of behavioral risk factors in Terai region of Nepal likely suggest lack of awareness and health promotion activities for metabolic syndrome and indicate the need to promote public health programs in this region to maintain quality of life.

Keywords: metabolic syndrome, Nepal, prevalence, risk factors, Terai

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3927 Network Security Attacks and Defences

Authors: Ranbir Singh, Deepinder Kaur


Network security is an important aspect in every field like government offices, Educational Institute and any business organization. Network security consists of the policies adopted to prevent and monitor forbidden access, misuse, modification, or denial of a computer network. Network security is very complicated subject and deal by only well trained and experienced people. However, as more and more people become wired, an increasing number of people need to understand the basics of security in a networked world. The history of the network security included an introduction to the TCP/IP and interworking. Network security starts with authenticating, commonly with a username and a password. In this paper, we study about various types of attacks on network security and how to handle or prevent this attack.

Keywords: network security, attacks, denial, authenticating

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3926 Evaluation of the Weight-Based and Fat-Based Indices in Relation to Basal Metabolic Rate-to-Weight Ratio

Authors: Orkide Donma, Mustafa M. Donma


Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit.

Keywords: basal metabolic rate, body mass index, children, diagnostic obesity notation model assessment index, obesity

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3925 Application of KL Divergence for Estimation of Each Metabolic Pathway Genes

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani


The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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3924 Enhancing the Network Security with Gray Code

Authors: Thomas Adi Purnomo Sidhi


Nowadays, network is an essential need in almost every part of human daily activities. People now can seamlessly connect to others through the Internet. With advanced technology, our personal data now can be more easily accessed. One of many components we are concerned for delivering the best network is a security issue. This paper is proposing a method that provides more options for security. This research aims to improve network security by focusing on the physical layer which is the first layer of the OSI model. The layer consists of the basic networking hardware transmission technologies of a network. With the use of observation method, the research produces a schematic design for enhancing the network security through the gray code converter.

Keywords: network, network security, grey code, physical layer

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3923 Network Functions Virtualization-Based Virtual Routing Function Deployment under Network Delay Constraints

Authors: Kenichiro Hida, Shin-Ichi Kuribayashi


NFV-based network implements a variety of network functions with software on general-purpose servers, and this allows the network operator to select any capabilities and locations of network functions without any physical constraints. In this paper, we evaluate the influence of the maximum tolerable network delay on the virtual routing function deployment guidelines which the authors proposed previously. Our evaluation results have revealed the following: (1) the more the maximum tolerable network delay condition becomes severe, the more the number of areas where the route selection function is installed increases and the total network cost increases, (2) the higher the routing function cost relative to the circuit bandwidth cost, the increase ratio of total network cost becomes larger according to the maximum tolerable network delay condition.

Keywords: NFV (Network Functions Virtualization), resource allocation, virtual routing function, minimum total network cost

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3922 Drug Delivery to Solid Tumor: Effect of Dynamic Capillary Network Induced by Tumor

Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani


The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

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3921 Metabolomics Profile Recognition for Cancer Diagnostics

Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny


Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: cancer, metabolites, metabolic pathway, signaling pathway

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3920 The Comparison between Resistance and Aerobic Exercise Training on Metabolic Syndrome Components in Overweight Sedentary Female

Authors: Marzieh Sayyad, Mohsen Salesi


Metabolic syndrome (MetS), a collection of cardiometabolic risk factors, is linked to the development of cardiovascular disease (CVD) and diabetes. The prevalence of MetS is on the rise with more women affected than men. The goal of this study was to compare the effects of resistance and aerobic exercise training on metabolic syndrome components in non-athlete, middle-aged woman. 51 non-athlete overweight female participated voluntarily in this study. Participants were divided randomly into three groups including resistance, aerobic and control group (number of each group 17). 24 hours before the beginning of training program, the blood sample was taken in fasting state. The two training groups participated in sport activities for eight weeks, three times a week duration 60-90 minutes. Two days following the end of the 8th week, all the measurements were performed similar to the pretest phase. The data was analyzed using one-way analysis of variance. The results showed that aerobic exercise training significantly decreased weight (p=.05), triglyceride (p<0.01) and systolic blood pressure (p<0.02) and HDL-c (p<0.01) was significantly increased. Also in resistance exercise training group TG decreased significantly (p<0.01) and HDL-c (p<0.05) was significantly increased. This study demonstrated that a regular physical activity program improved several metabolic and physiological parameters in healthy, previously sedentary subjects with the metabolic syndrome. In conclusion, it seems that this type of training can be efficient, safe and inexpensive way in order to reduce and prevent metabolic syndrome.

Keywords: aerobic exercise, metabolic syndrome, overweight sedentary female, resistance exercise

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3919 Mathematical Modelling of the Effect of Glucose on Pancreatic Alpha-Cell Activity

Authors: Karen K. Perez-Ramirez, Genevieve Dupont, Virginia Gonzalez-Velez


Pancreatic alpha-cells participate on glucose regulation together with beta cells. They release glucagon hormone when glucose level is low to stimulate gluconeogenesis from the liver. As other excitable cells, alpha cells generate Ca2+ and metabolic oscillations when they are stimulated. It is known that the glucose level can trigger or silence this activity although it is not clear how this occurs in normal and diabetic people. In this work, we propose an electric-metabolic mathematical model implemented in Matlab to study the effect of different glucose levels on the electrical response and Ca2+ oscillations of an alpha cell. Our results show that Ca2+ oscillations appear in opposite phase with metabolic oscillations in a window of glucose values. The model also predicts a direct relationship between the level of glucose and the intracellular adenine nucleotides showing a self-regulating pathway for the alpha cell.

Keywords: Ca2+ oscillations, mathematical model, metabolic oscillations, pancreatic alpha cell

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