Perceived organizational support, employee engagement and organizational commitment among millennials
Millennials (born between 1981-2000) are drastically different from any other generational cohorts, with their high education level, technological skills, social networking, self-confidence and always teeming with energy, which makes them excellent team players, unlike the previous generations who preferred to work on their own for long hours. Millennials, having grown to constitute a considerable proportion of the workforce and will continue to grow to represent more over the next 20 years, desire for immediate result and speedy advancement, which has led to perceiving them to be impatient and inconsistent. Hence, retaining them has become one of the top managerial priorities. Millennials are prone to frequent switching of jobs which is why they are attributed with the character of job-hopping. Of all the generations in the work force, Millennials are found to be less consistent in their workplace relationships which calls for the purposeful need for cultivating positive relationships with them at workplace. Organizational commitment is evidently one such gesture of an employee, towards positive and long-term relationship with the organization, as a committed employee stays with the organization and this can be brought about if the employees realize that they are being supported well by the organization. Hence, the perceived organizational support plays a pivotal role in work place relations. Another construct in the employeeorganization relationship is, which has a decisive role to play, is Employee engagement. Thus, this study intents to examine how perceived organizational support is related to organizational commitment where employee engagement mediates the relation between the two variables. An empirical study has been done, whereby carrying out a survey among 402 millennial employees across various companies in the information technology sector, as this sector experiences the rush of millennials more, compared to other traditional industries. And it was found that there is a vi significant relation that existed among perceived organization support and organizational commitment and employee engagement and organizational commitment as well. Employee engagement also turned out to be partially mediating the relationship between POS and OC. This study, done to find the relation between the three important constructs in organizational behavior and human resource management, and also to find out the difference in the variation of these three constructs based on the demographical factors, is the first of its kind to be done, among Millennials
Experimental evaluation of image segmentation for heart images
Cardiac mr images; Cardiac photo; Dual inverse thresholding; Fcm; Fuzzy c-means; Gaussian function; Morphological functions; Otsu thresholding; Segmentation
The cardiac death is the principal reason of the death in the world.The research work focuses on finding an efficient image segmentation technique for the computer aided detection and also to decrease the noise in the image.The segmentation is implemented with the help of fuzzy C-means clustering along with dual inverse thresholding function and Otsu thresholding.Experimental proof is evaluated with the help of morphological functions and with Gaussian function.The result of the work provides an accurate segmentation for myocardial ischemia in the human heart photo image as well as magnetic resonance imaging. Copyright 2021 Inderscience Enterprises Ltd.
International Journal of Computer Aided Engineering and Technology, Vol-15, No. 45718, pp. 269-280.
https://doi.org/10.1504/ijcaet.2021.117137 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113300555&doi=10.1504%2fijcaet.2021.117137&partnerID=40&md5=f866b08141acfaddfe615621685da9ce
Merjulah R., CHRIST (Deemed to Be University), Hosur Road, Bangalore, 560029, India; Chandra J., CHRIST (Deemed to Be University), Hosur Road, Bangalore, 560029, India
An Integrated Segmentation Techniques for Myocardial Ischemia
fuzzy C-means; magnetic resonance imaging; median filtering; morphological operations; myocardial infarction; segmentation
Abstract: Myocardial Ischemia segmentation is a challenging task for basic and translational research on cardiovascular, as it provides ultimately realistic in heart muscle model. The main objective of the research work is to find an efficient segmentation technique for the myocardial ischemia based on the myocardial infarcted MRI data set for the accurate classification of scar volume. The paper will give an insight about the segmentation technique based on myocardial ischemia and discusses essential cellular components. The paper provides an integrated approach which comprises of fuzzy c-means and morphological operations along with median filtering enhancement technique help in detecting the myocardial ischemia. The developed model is tested with 2D and 3D enhanced myocardial ischemia MRI and also with normal heart. The purpose of segmentation in myocardial ischemia is to identify the scar region in the heart. The integrated model is evaluated based on statistical measures and validated based on manual segmentation done by clinical expert. The scar classification is done based on the myocardial ischemia segmentation which leads to better prediction of arrhythmia in heart patient. The integrated model is considered as one of the best model for segmenting myocardial ischemia. 2020, Pleiades Publishing, Ltd.
Pattern Recognition and Image Analysis, Vol-30, No. 3, pp. 530-540.
Merjulah R., CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, Karnataka, India; Chandra J., CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, Karnataka, India
Classification of myocardial ischemia in delayed contrast enhancement using machine learning
Computer aided design (cad); Feature extraction and classification; Feed forward neural network (ffnn); Fuzzy c-means; Levenberg-marquardt back propagation (lmbp); Machine learning (ml); Magnetic resonance imaging (mri); Morphological filtering; Myocardial ischemia; Scaled conjugate gradient (scg); Segmentation
This chapter addresses the classification of myocardial ischemia in delayed contrast enhancement using machine-learning techniques for magnetic resonance imaging which solves the social issue of a sudden cardiac death. To automate the classification of myocardial ischemia, the computer-aided design has a crucial path on the mixture ensemble of machine learning. The mixture ensemble of machine learning can partition a high-dimensional image in a simultaneous and competitive way. The detection and the segmentation processes are carried out through Fuzzy C-Means multispectral and single-channel algorithms along with a morphological filtering technique for feature extraction. Furthermore, the feed forward neural network (FFNN) technique is trained through the Levenberg-Marquardt Back Propagation algorithm for the classification of myocardial ischemia in delayed contrast enhancement. The proposed classification model performs well for the classification of myocardial ischemia. The rigorous process of the proposed result reveals that the FFNN classifier produces 99.9% accuracy on the classification of myocardial ischemia and also shows that the given classifier is considered one of the best methods in classifying medical myocardial ischemia. 2019 Elsevier Inc. All rights reserved.
Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions, pp. 209-235.
Merjulah R., Christ University, Bangalore, India; Chandra J., Christ University, Bangalore, India
Medical image classification using MRI: An investigation
Artificial neural network (ANN); Discrete wavelet transform (DWT); Magnetic resonance imaging (MRI); Principal component analysis (PCA); Support vector machine (SVM)
The main objective of the paper is to review the performance of various machine learning classification technique currently used for magnetic resonance imaging. The prerequisite for the best classification technique is the main drive for the paper. In magnetic resonance imaging, detection of various diseases might be simple but the physicians need quantification for further treatment. So, the machine learning along with digital image processing aids for the diagnosis of the diseases and synergizes between the computer and the radiologist. The review of machine learning classification based on the support vector machine, discrete wavelet transform, artificial neural network, and principal component analysis reveals that discrete wavelet transform combined with other highly used method like PCA, ANN, etc., will bring high accuracy rate of 100%. The hybrid technique provides the second opinion to the radiologist on taking the decision. Springer Nature Switzerland AG 2019.
Lecture Notes in Computational Vision and Biomechanics, Vol-30, pp. 1135-1146.
Segmentation technique for medical image processing: A survey
Computer Tomography (CT); Convolutional neural Network (CNN); Deep learning (DL); Machine learning (ML); Magnetic Resonance Imaging (MRI); Positron Emission Tomography (PET)
Segmentation is one of the popular and efficient technique in context to medical image analysis. The purpose of the segmentation is to clearly extract the Region of Interest from the medical images. The main focus of this paper is to review and summarize an efficient segmentation method. While doing the comparison study on segmentation methods using the Support Vector Machine, K-Nearest Neighbors, Random Forest and the Convolutional Neural Network for medical image analysis identifies that Convolutional Neural Network works efficiently for doing in-depth analysis. The Convolutional Neural Network can be used as segmentation technique for achieving the high accuracy on medical image analysis. 2017 IEEE.
Proceedings of the International Conference on Inventive Computing and Informatics, ICICI 2017, pp. 1055-1061.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICICI.2017.8365301 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048350440&doi=10.1109%2fICICI.2017.8365301&partnerID=40&md5=e89bcca8048381346c04f4793ea30a99
Merjulah R., Computer Science, Christ University, Bangalore, India; Chandra J., Computer Science, Christ University, Bangalore, India
Predictive analytics for cardiac arrhythmia using machine intelligence
Myocardial Infarction (MI) is the primary cause of death worldwide. MI occurs when a plaque buildup in the inner surface of the coronary artery suddenly ruptures and prevents the blood flow. A heart attack is medically termed as MI. It is the irreversible damage caused by the prolonged ischemia. Ischemia is nothing but the heart organ doesn’t get enough blood and oxygen which is also termed as coronary artery disease or coronary heart disease. The heart gets damaged if it has not received enough blood or oxygen. In connection to the damage of the heart, arrhythmia would occur. Arrhythmia is the problem based on the heart rhythm or rate of the heartbeat. Tachycardia, when there is a fast beat in the heart. Bradycardia, when the heart beats too slow. The common type of arrhythmia is atrial fibrillation. The great concern is that the patient who has arrhythmia has to be treated immediately. They lose consciousness in a few minutes when the heart is not pumping enough blood mainly to the brain. Death occurs when the patient is not given emergency treatment.
Myocardial Infarction (MI) is the primary cause of death worldwide. MI occurs when a plaque buildup in the inner surface of the coronary artery suddenly ruptures and prevents the blood flow. A heart attack is medically termed as MI. It is the irreversible damage caused by the prolonged ischemia. Ischemia is nothing but the heart organ doesn t get enough blood and oxygen which is also termed as coronary artery disease or coronary heart disease. The heart gets damaged if it has not received enough blood or oxygen. In connection to the damage of the heart, arrhythmia would occur. Arrhythmia is the problem based on the heart rhythm or rate of the heartbeat. Tachycardia, when there is a fast beat in the heart. Bradycardia, when the heart beats too slow. The common type of arrhythmia is atrial fibrillation. The great concern is that the patient who has arrhythmia has to be treated immediately. They lose consciousness in a few minutes when the heart is not pumping enough blood mainly to the brain. Death occurs when the patient is not given emergency treatment. newline Treatment which is included in the emergency is defibrillation and Cardiopulmonary Resuscitation (CPR). CPR is an emergency procedure which is combined with the chest compressions. It is through artificial ventilation which gives manual effort, preserves the brain functions until further treatment for the restoration of spontaneous blood circulation. The common symptoms of sudden cardiac death are chest pain, shortness of breath, severe wheezing, irregular heartbeats, fainting etc. newlineHeart Scar tissue which is not like heart muscle. It doesn t contrast like the normal heart muscle. Heart muscles get damaged for the heart attack patient based on the time of the treatment. The damage of the heart is based on the blockage of the artery. Arrhythmia can be predicted based on the volume of the scar region in the heart. Arrhythmia patients are treated by fixing Implantable Cardioverter Defibrillator (ICD).
A Study on defective colouring of graphs
If different technology represents distinct colours that are to be located on some geographical region which can be represented as vertices of a graph, then the proper colouring is obtained when no two technology of same type share a common edge between the vertices they are placed on. The minimum number of technology required for such a colouring of a graph is the chromatic number of the graph. However, if the available technology are less than that of the minimum required, then the question arises on how to place the technology on the vertices of a graph in such a way that there is a minimum adjacency between the technology of same type. The solution for this problem can be attained by defining certain rules for the properness of colouring in which a few thresholds are tolerated. We know that, in a proper colouring every colour class is an independent set. If the available colours to colour a graph is less than that of the chromatic number of graphs, then a threshold that can be tolerated is permitting few colour classes to be non-independent set. An edge uv is said to be a monochromatic edge or bad edge if the colours assigned to both u and v are the same. A near proper colouring of graphs is a colouring that minimises the number of monochromatic edges by permitting few colour classes to have adjacency between the elements in it. The minimum number of monochromatic edges obtained from near proper colouring is called near defect number, denoted by B_k (G). A and#948;^((k))-colouring of graph G is a near proper colouring of G consisting of k given colours, where 1and#8804;kand#8804;and#967;(G)-1, which minimises the number of monochromatic edges by permitting at most one colour class to have adjacency among the vertices in it. The and#948;^((k))-defect number is the minimum number of monochromatic edges obtained from a and#948;^((k))-colouring of graphs and it is denoted by b_k(G). The study concerned is the further work on a near proper colouring and a and#948;^((k))-colouring of graphs.
Harnessing transition metal oxide?carbon heterostructures: Pioneering electrocatalysts for energy systems and other applications
Batteries; Composites; HER; OER; Supercapacitors; Transition metal oxides
Exponential demand for energy resources and fossil fuel substitution with green alternatives are essential to bringing sustainable development and a solution to the energy crisis. Transition metal oxides (TMOs) and their composites (TMOCs) as promising electrocatalysts to develop potential energy conversion and storage devices contribute to the solution to this crisis. The productivity of green fuels such as hydrogen from water-splitting reactions, the efficiency of energy storage and harvesting devices including supercapacitors and batteries, and the performance of electrochemical sensors can be remarkably enhanced with TMOs and their composites. Excellent electrochemical attributes, stability, abundant reserves, low cost, environment-friendly, and low toxicity make TMOs and their composites an excellent choice. The tunability of the physical and chemical properties of TMOs makes them attractive for research in designing different energy storage devices. This review presents a concise overview of the unique physical and electrochemical aspects of various TMOs and TMOCs, such as spinels, perovskites, and TMO-integrated carbon-based compounds, and their relevance for specific applications, emphasizing energy-related fields. The recent research advancements of TMOs-based functional materials for emerging applications, such as water splitting, fuel cells, supercapacitors, batteries, and sensing, are discussed. This review also highlights the advantageous properties and pertinent fabrication methods of TMOs and TMOCs for electrocatalysis, along with the methods to enhance their electrocatalytic abilities, which improve the overall efficiency of the desired applications. 2024
Merlin V S M.; Sariga; Jose S.; Varghese A.
Merlin V S M., Department of Chemistry, Christ University, Bengaluru, 560029, India; Sariga, Department of Chemistry, Christ University, Bengaluru, 560029, India; Jose S., Department of Chemistry, Christ University, Bengaluru, 560029, India; Varghese A., Department of Chemistry, Christ University, Bengaluru, 560029, India
Discovery of inverse-Compton X-ray emission and estimate of the volume-averaged magnetic field in a galaxy group
galaxies: clusters: individual: MRC 0116+111; galaxies: clusters: intracluster medium; magnetic fields; X-rays: galaxies: clusters
Observed in a significant fraction of clusters and groups of galaxies, diffuse radio synchrotron emission reveals the presence of relativistic electrons and magnetic fields permeating large scale systems of galaxies. Although, these non-thermal electrons are expected to upscatter cosmic microwave background photons up to hard X-ray energies, such inverse-Compton (IC) X-ray emission has so far not been unambiguously detected on cluster/group scales. Using deep, new proprietary XMM-Newton observations (?200 ks of clean exposure), we report a 4.6 ? detection of extended IC X-ray emission in MRC 0116 +111, an extraordinary group of galaxies at z = 0.131. Assuming a spectral slope derived from low frequency radio data, the detection remains robust to systematic uncertainties. Together with low frequency radio data from the Giant Metrewave Radio Telescope (GMRT), this detection provides an estimate for the volume-averaged magnetic field of (1.9 0.3) ?G within the central part of the group. This value can serve as an anchor for studies of magnetic fields in the largest gravitationally bound systems in the Universe. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.
Mernier F.; Werner N.; Bagchi J.; Gendron-Marsolais M.-L.; Gopal-Krishna; Guainazzi M.; Richard-Laferrie A.; Shimwell T.W.; Simionescu A.
Monthly Notices of the Royal Astronomical Society, Vol-524, No. 4, pp. 4939-4949.
https://doi.org/10.1093/mnras/stad2093 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168486459&doi=10.1093%2fmnras%2fstad2093&partnerID=40&md5=986b6d4418d9da69bc0fadfd45d54045
Mernier F., NASA Goddard Space Flight Center, Code 662, Greenbelt, 20771, MD, United States, Department of Astronomy, University of Maryland, College Park, 20742-2421, MD, United States, European Space Agency (ESA), European Space Research and Technology Centre (ESTEC), Keplerlaan 1, Noordwijk, NL-2201 AZ, Netherlands, SRON Netherlands Institute for Space Research, Niels Bohrweg 4, Leiden, NL-2333 CA, Netherlands; Werner N., Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlsk2, Brno, CZ-611 37, Czech Republic; Bagchi J., Department of Physics & Electronics, Christ (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Gendron-Marsolais M.-L., European Southern Observatory, Alonso de Cdova 3107, Vitacura, Casilla, Santiago de Chile, 19001, Chile, Instituto de Astrofica de Andaluc (IAA-CSIC), Glorieta de la Astronom, Granada, E-18008, Spain; Gopal-Krishna, UM-DAE Centre for Excellence in Basic Sciences (CEBS), Vidyanagari, Mumbai, 400098, India; Guainazzi M., European Space Agency (ESA), European Space Research and Technology Centre (ESTEC), Keplerlaan 1, Noordwijk, NL-2201 AZ, Netherlands; Richard-Laferrie A., Institute of Astronomy, Madingley Road, Cambridge, CB3 0HA, United Kingdom; Shimwell T.W., ASTRON, Netherlands Institute for Radio Astronomy, Oude Hoogeveensedijk 4, Dwingeloo, NL-7991 PD, Netherlands; Simionescu A., SRON Netherlands Institute for Space Research, Niels Bohrweg 4, Leiden, NL-2333 CA, Netherlands, Leiden Observatory, Leiden University, P.O. Box 9513, Leiden, NL-2300 RA, Netherlands, Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan
FSDA: Framework for Secure Data Aggregation in wireless sensor network for enhancing key management
Encryption; Key management; Security; Wireless Sensor Network
An effective key management plays a crucial role in imposing a resilient security technique in Wireless Sensor Network (WSN). After reviewing the existing approaches of key management, it is confirmed that existing approachs does not offer good coverage on all potential security breaches in WSN. With WSN being essential part of Internet-of-Things (IoT), the existing approaches of key management can definitely not address such security breaches. Therefore, this paper introduces a Framework for Secure Data Aggregation (FSDA) that hybridizes the public key encryption mechanism in order to obtain a novel key management system. The proposed system does not target any specific attacks but is widely applicable for both internal and external attacks in WSN owing to its design principle. The study outcome exhibits that proposed FSDA offers highly reduced computational burden, minimal delay, less energy consumption, and higher data transmission perforance in contrast to frequency used encryption schemes in WSN. Copyright 2018 Institute of Advanced Engineering and Science. All rights reserved.
International Journal of Electrical and Computer Engineering, Vol-8, No. 6, pp. 4684-4692.
Institute of Advanced Engineering and Science
All Open Access; Green Open Access; Hybrid Gold Open Access
https://doi.org/10.11591/ijece.v8i6.pp4684-4692 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057210559&doi=10.11591%2fijece.v8i6.pp4684-4692&partnerID=40&md5=52e7e813b802c3ccc6d82e1594c705be
Metan J., Department of Computer Science and Enggineering, ACS College of Engineering, Bangalore, India; Murthy K.N.N., Faculty of Engineering, Christ University, Banglore, India
N-tier modelling of robust key management for secure data aggregation in wireless sensor network
Adversary; Attack; Cryptography; Public key encryption; Wireless sensor network
Security problems in Wireless Sensor Network (WSN) have been researched from more than a decade. There are various security approaches being evolving towards resisting various forms of attack using different methodologies. After reviewing the existing security approaches, it can be concluded that such security approaches are highly attack-specific and doesnt address various associated issues in WSN. It is essential for security approach to be computationally lightweight. Therefore, this paper presents a novel analytical modelling that is based on n-tier approach with a target to generate an optimized secret key that could ensure higher degree of security during the process of data aggregation in WSN. The study outcome shows that proposed system is computationally lightweight with good performance on reduced delay and reduced energy consumption. It also exhibits enhanced response time and good data delivery performance to balance the need of security and data forwarding performance in WSN. 2019 Institute of Advanced Engineering and Science.
International Journal of Electrical and Computer Engineering, Vol-9, No. 4, pp. 2682-2690.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.11591/ijece.v9i4.pp2682-2690 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066233139&doi=10.11591%2fijece.v9i4.pp2682-2690&partnerID=40&md5=cc5a1b14b292893e38bcbf77debc167e
Metan J., Department of Computer Science and Enggineering, ACS College of Engineering, Bangalore, India; Narashinha Murthy K.N., Faculty of Engineering, Christ University, India
RASK: Request authentication using shared keys for secured data aggregation in sensor network
Cryptography; Data aggregation; Energy; Key management; Security; Wireless sensor network
Accomplishing a robust security features to resists lethal attacks is still an open research area in wireless sensor network. The present paper review existing security techniques to find that there is still a trade-off between cryptographic-based security incorporations and communication performance. Moreover, we have identified that majority of the existing system has not emphasized on first line of defense i.e. security the route discovery process that can act as a firewall for all forms of illegitimate nodes existing in the network. The proposed study introduced RASK i.e. Request Authentication using Shared Key, which is a novel concept developed using simple quadratic formulation of generating keys for encrypting the message during data aggregation. The study outcome has been significantly benchmarked with recent studies and existing cryptographic standards to find RASK outperform existing techniques. Springer International Publishing AG 2017.
Advances in Intelligent Systems and Computing, Vol-575, pp. 23-35.
Metan J., Visvesvaraya Technological University, Belagavi, India; Narasimha Murthy K.N., Faculty of Engineering, Christ University, Bangalore, India
A genome wide association study of fast beta EEG in families of European ancestry
Electrophysiology; Endophenotype; Genome-Wide Association Study (GWAS); Resting EEG
Background Differences in fast beta (2028Hz) electroencephalogram (EEG) oscillatory activity distinguish some individuals with psychiatric and substance use disorders, suggesting that it may be a useful endophenotype for studying the genetics of disorders characterized by neural hyper-excitability. Despite the high heritability estimates provided by twin and family studies, there have been relatively few genetic studies of beta EEG, and to date only one genetic association finding has replicated (i.e., GABRA2). Method In a sample of 1564 individuals from 117 families of European Ancestry (EA) drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Genome-Wide Association Study (GWAS) on resting-state fronto-central fast beta EEG power, adjusting regression models for family relatedness, age, sex, and ancestry. To further characterize genetic findings, we examined the functional and behavioral significance of GWAS findings. Results Three intronic variants located within DSE (dermatan sulfate epimerase) on 6q22 were associated with fast beta EEG at a genome wide significant level (p<5נ10?8). The most significant SNP was rs2252790 (p<2.6נ10?8; MAF=0.36; ?=0.135). rs2252790 is an eQTL for ROS1 expressed most robustly in the temporal cortex (p=1.2נ10?6) and for DSE/TSPYL4 expressed most robustly in the hippocampus (p=7.3נ10?4; ?=0.29). Previous studies have indicated that DSE is involved in a network of genes integral to membrane organization; gene-based tests indicated that several variants within this network (i.e., DSE, ZEB2, RND3, MCTP1, and CTBP2) were also associated with beta EEG (empirical p<0.05), and of these genes, ZEB2 and CTBP2 were associated with DSM-V Alcohol Use Disorder (AUD; empirical p<0.05). Discussion In this sample of EA families enriched for AUDs, fast beta EEG is associated with variants within DSE on 6q22; the most significant SNP influences the mRNA expression of DSE and ROS1 in hippocampus and temporal cortex, brain regions important for beta EEG activity. Gene-based tests suggest evidence of association with related genes, ZEB2, RND3, MCTP1, CTBP2, and beta EEG. Converging data from GWAS, gene expression, and gene-networks presented in this study provide support for the role of genetic variants within DSE and related genes in neural hyperexcitability, and has highlighted two potential candidate genes for AUD and/or related neurological conditions: ZEB2 and CTBP2. However, results must be replicated in large, independent samples. 2016 Elsevier B.V.
Meyers J.L.; Zhang J.; Manz N.; Rangaswamy M.; Kamarajan C.; Wetherill L.; Chorlian D.B.; Kang S.J.; Bauer L.; Hesselbrock V.; Kramer J.; Kuperman S.; Nurnberger J.I., Jr.; Tischfield J.; Wang J.C.; Edenberg H.J.; Goate A.; Foroud T.; Porjesz B.
International Journal of Psychophysiology, Vol-115, pp. 74-85.
ISSN: 1678760; PubMed ID: 28040410; CODEN: IJPSE
https://doi.org/10.1016/j.ijpsycho.2016.12.008 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010953537&doi=10.1016%2fj.ijpsycho.2016.12.008&partnerID=40&md5=d461f8607df9968ee93ec10d0fdd4749
Meyers J.L., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States; Zhang J., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States; Manz N., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States, Department of Physics, College of Wooster, Wooster, OH, United States; Rangaswamy M., Department of Psychology, Christ University, Bangalore, India; Kamarajan C., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States; Wetherill L., Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States; Chorlian D.B., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States; Kang S.J., Albany Stratton VA Medical Center, Albany, NY, United States; Bauer L., University of Connecticut School of Medicine, Farmington, CT, United States; Hesselbrock V., University of Connecticut School of Medicine, Farmington, CT, United States; Kramer J., Department of Psychiatry, University of Iowa, Iowa City, IA, United States; Kuperman S., Department of Psychiatry, University of Iowa, Iowa City, IA, United States; Nurnberger J.I., Jr., Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States; Tischfield J., Rutgers University, Piscataway, NJ, United States; Wang J.C., Icahn School of Medicine at Mt. Sinai, New York, NY, United States; Edenberg H.J., Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, United States; Goate A., Icahn School of Medicine at Mt. Sinai, New York, NY, United States; Foroud T., Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States; Porjesz B., Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, United States
Genetic and cytogenetic screening of autistic spectrum disorder: Genotype-phenotype profiles
Autism; DSM IV-TR; FISH analysis; Karyotyping; NRXN1gene
Autism, a pervasive developmental disorder typically characterized by repetitive behaviour, social skills deficit (or a deficit in social communication), speech and language impairments. Our prime focus is to analyze the clinical features and phenotypical behavioural changes using the diagnostic and statistical manual of mental disorders, fourth edition, text revision (DSM IV-TR), and locating the biomarkers associated with specific autistic characters using karyotyping and fluorescence in situ hybridization (FISH) techniques. The prevalence rate of the neurexin 1 (NRXN1) gene polymorphism was also assessed in the current study. The study group involved 196 samples with 98 autistics, and equal age-matched (2) controls based on their birth order and carrier. The participants include 35.2% males (n = 69) and 14.8% females (n = 29). The autistic and control participants were categorized based on their ages as group I (<12 yrs) with n = 62; males n = 41 (20.9%); females n = 21 (10.7%) and group II (?12 yrs)-n = 36; males n = 28 (14.2%); females n = 08 (4.08%). Karyotyping was done for autism participants (n = 98) and the results showed that 90% of autistic participants were either the only child or the first child with a low perception and frequency in both the groups. Subsequently, we carried out the FISH assay on participants (n = 37) with higher DSM-IV TR score (?30). Only 30 FISH tests were negative for subtelomeric deletions with NRXN1 polymorphism genotypic frequency as 62.50%, 25% and 25% for A/A, A/G and G/G genotype respectively. Our study suggests the link between a haplotype with clinical signs of autism for the single nucleotide sequence (SNP rs9636391) and links autistic characters and gene among autistic children according to their birth order, age and gender in India. 2021 Elsevier B.V.
Meyyazhagan A.; Balasubramanian B.; Bhotla H.K.; Easwaran M.; Shanmugam S.; Alagamuthu K.K.; Arumugam V.A.; Keshavarao S.; Pappusamy M.
https://doi.org/10.1016/j.mgene.2021.100924 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106518982&doi=10.1016%2fj.mgene.2021.100924&partnerID=40&md5=cd162d5c491763a5480e9f2950132b82
Meyyazhagan A., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India, Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Balasubramanian B., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Bhotla H.K., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Easwaran M., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Shanmugam S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Department of Animal Resource and Science, Dankook University, Cheonan, 31116, South Korea; Alagamuthu K.K., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Science, Nanjing Normal University, Nanjing, 210023, China; Arumugam V.A., Medical Genetics and Epigenetics Laboratory, Department of Human Genetics and Molecular Biology, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India; Keshavarao S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Pappusamy M., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India
Biomarker study of the biological parameter and neurotransmitter levels in autistics
Antioxidant proteins; Autism; Biochemical; Neurotransmitters; Oxidative stress
Autism is a prevalent developmental disorder that combines repetitive behaviours, social deficits and language abnormalities. The present study aims to assess the autistic subjects using DSM IV-TR criteria followed with the analysis of neurotransmitters, biochemical parameters, oxidative stress and its ions in two groups of autistic subjects (group I < 12years; group II ? 12years). Antioxidants show a variation of 10% increase in controls compared to autistic age < 12years. The concentration of pyruvate kinase and hexokinase is elevated in controls approximately 60% and 45%, respectively, with the significance of 95 and 99%. Autistic subjects showed marked variation in levels of neurotransmitters, oxidative stress and its related ions. Cumulative assessment of parameters related to biochemical markers and neurotransmitters paves the way for autism-based research, although these observations draw interest in an integrated approach for autism. 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Meyyazhagan A.; Balasubramanian B.; Easwaran M.; Alagamuthu K.K.; Shanmugam S.; Kuchi Bhotla H.; Pappusamy M.; Arumugam V.A.; Thangaraj A.; Kaul T.; Keshavarao S.; Cacabelos R.
Molecular and Cellular Biochemistry, Vol-474, No. 45689, pp. 277-284.
ISSN: 3008177; PubMed ID: 32740790; CODEN: MCBIB
Meyyazhagan A., EuroEspes Biomedical Research Centre, International Center of Neurosciences and Genomic Medicine, Bergondo, Corunna, 15165, Spain, Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India, Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, Karnataka, India; Balasubramanian B., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India, Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Easwaran M., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Alagamuthu K.K., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India, Jiagsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Science, Nanjing Normal University, Nanjing, 210023, China; Shanmugam S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India, Department of Animal Resource and Science, Dankook University, Cheonan, 31116, South Korea; Kuchi Bhotla H., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India; Pappusamy M., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, Karnataka, India; Arumugam V.A., Medical Genetics and Epigenetics Laboratory, Department of Human Genetics and Molecular Biology, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India; Thangaraj A., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Kaul T., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Keshavarao S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India; Cacabelos R., EuroEspes Biomedical Research Centre, International Center of Neurosciences and Genomic Medicine, Bergondo, Corunna, 15165, Spain
Crux role of neurocomputing in teaching learning pedagogy
Adolescence; Brain; Cognition; Developmental disorders; Educational neuroscience; Emotions
The advent of brain-based learning in the early 1990s has limelighted the syndication between the educational learning process and neurosciences. Through educational learning ability, an individual can gather and assimilate anecdotes or come up with new notions with logical conclusions to form an organizational memory. Supreme level of knowledge assimilation ability results in developing new crucial knowledge for strategic renewal for the betterment of the learning process. Earlier efforts to link neuroscience and learning mode were controversial. However, continuous researches imply the significant role of neurosciences in the field of education and its deep-rooted involvement in building reformed educational pedagogy related to curriculum and general teaching-learning practices. Educational neurosciences help in interpreting brain-behaviour intricacy to provide latest teaching-learning strategies. Education is the most robust cognitive skill developer, and it must be provided to all irrespective of age and gender as it makes the person flexible and provides strength to cope with the adversities. Through this report, we would like to covey the deep association between the teaching-learning process with neurological sciences along with providing measures to be taken for holistic development in the educational setups. Learning is a by-product of human behaviour towards the external environment. Recent advanced tools of neuroimaging aid in more in-depth insight linked to adaptive neural mechanics, knowledge attainment, new skill acquisition and building neuroscience network for human learning. The neuroscience research shows intricacy between emotions and cognition as mediators between mind and body that are then followed by the social behaviour and learning, by indulging in subjective interpretations of person's goals, feelings, actions and experiences, ultimately resulting in learning new theories through neurobiological shreds of evidence. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved.
Meyyazhagan A.; Bhotla H.K.; Easwaran M.; Balasubramanian B.; Kureethara J.V.; Pappusamy M.
Neuro-Systemic Applications in Learning, pp. 445-460.
Meyyazhagan A., Department of Life Sciences, Christ University, Bengaluru, Karnataka, India; Bhotla H.K., Bioknowl Insights Private Limited, Coimbatore, Tamil Nadu, India; Easwaran M., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, India; Balasubramanian B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Kureethara J.V., Department of Mathematics and Statistics, Christ University, Bengaluru, Karnataka, India; Pappusamy M., Department of Life Sciences, Christ University, Bengaluru, Karnataka, India
Clinical implications of chromosomal polymorphisms in congenital disorders
Chromosomal polymorphism; Congenital disorders; DNA; Karyotype
Alterations in the DNA sequence are generally seen in the general population at >1%, and these alterations can be deletions or insertions. Classically, chromosomal polymorphisms (CPMs) are alterations with no significant phenotypic distinctions. However, few studies have shown that the presence of CPM can lead to congenital disabilities, which can be fatal. These variants in the DNA can happen in the form of single nucleotide polymorphisms (SNPs). The human genome is considered full of SNPs, and they are responsible for causing pathological phenotypes and provide insight into pathogenesis, a therapeutic approach to the pathology. About 100 million SNPs are observed in humans for an average of 300 nucleotides. These polymorphisms are detected by using molecular techniques. These polymorphisms are not just restricted to the coding region. The CPMs are first recognized on the chromosomes through molecular techniques, followed by detection of the polymorphism. The CMPs are generally the SNPs, deletions/duplications, and presence of microsatellite DNAs. Here we have summarized the implications of CMPs in a few congenital disorders and the method of diagnosis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Meyyazhagan A.; Bhotla H.K.; Pappuswamy M.; Tsibizov V.; Alagamuth K.K.; Di Renzo G.C.
Prenatal Diagnostic Testing for Genetic Disorders: The revolution of the Non-Invasive Prenatal Test, pp. 57-66.
Meyyazhagan A., Centre for Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, Karnataka, India, PREIS International and European School of Perinatal, Neonatal and Reproductive Medicine, Firenze, Italy; Bhotla H.K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Pappuswamy M., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Tsibizov V., Institute of Perinatology and Pediatrics, Almazov National Medical Research Centre, Saint-Petersburg, Russian Federation; Alagamuth K.K., Department of Biotechnology, Selvamm Arts and Science College (Autonomous), Namakkal, India; Di Renzo G.C., Centre for Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, PREIS International and European School of Perinatal, Neonatal and Reproductive Medicine, Firenze, Italy, Department of Obstetrics and Gynecology, I.M. Sechenov First State University of Moscow, Moscow, Russian Federation
The Puzzle of Hereditary Spastic Paraplegia: From Epidemiology to Treatment
clinical manifestations; drugs; genes; hereditary spastic paraplegia; pathways; therapies
Inherited neurodegenerative pathology characterized by lower muscle tone and increasing spasticity in the lower limbs is termed hereditary spastic paraplegia (HSP). HSP is associated with changes in about 80 genes and their products involved in various biochemical pathways, such as lipid droplet formation, endoplasmic reticulum shaping, axon transport, endosome trafficking, and mitochondrial function. With the inheritance patterns of autosomal dominant, autosomal recessive, X-linked recessive, and mitochondrial inheritance, HSP is prevalent around the globe at a rate of 15 cases in every 100,000 individuals. Recent technology and medical interventions somewhat aid in recognizing and managing the malaise. However, HSP still lacks an appropriate and adequate therapeutic approach. Current therapies are based on the clinical manifestations observed in the patients, for example, smoothing the relaxant spastic muscle and physiotherapies. The limited clinical trial studies contribute to the absence of specific pharmaceuticals for HSPs. Our current work briefly explains the causative genes, epidemiology, underlying mechanism, and the management approach undertaken to date. We have also mentioned the latest approved drugs to summarise the available knowledge on therapeutic strategies for HSP. 2022 by the authors.
Meyyazhagan A.; Kuchi Bhotla H.; Pappuswamy M.; Orlacchio A.
International Journal of Molecular Sciences, Vol-23, No. 14
https://doi.org/10.3390/ijms23147665 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135132487&doi=10.3390%2fijms23147665&partnerID=40&md5=022b1783c1fd4de7ba56856185a678dc
Meyyazhagan A., Dipartimento di Medicina e Chirurgia, Universitdi Perugia, Perugia, 06132, Italy; Kuchi Bhotla H., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Pappuswamy M., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Orlacchio A., Dipartimento di Medicina e Chirurgia, Universitdi Perugia, Perugia, 06132, Italy, Laboratorio di Neurogenetica, Centro Europeo di Ricerca sul Cervello (CERC), Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, 00179, Italy