Analysis of Mitochondrial DNA Sequences in Childhood Encephalomyopathies Reveals New Disease-Associated Variants

BACKGROUND: Mitochondrial encephalomyopathies are a heterogeneous group of clinical disorders generally caused due to mutations in either mitochondrial DNA (mtDNA) or nuclear genes encoding oxidative phosphorylation (OXPHOS). We analyzed the mtDNA sequences from a group of 23 pediatric patients with clinical and morphological features of mitochondrial encephalopathies and tried to establish a relationship of identified variants with the disease. METHODOLOGY/PRINCIPLE FINDINGS: Complete mitochondrial genomes were amplified by PCR and sequenced by automated DNA sequencing. Sequencing data was analyzed by SeqScape software and also confirmed by BLASTn program. Nucleotide sequences were compared with the revised Cambridge reference sequence (CRS) and sequences present in mitochondrial databases. The data obtained shows that a number of known and novel mtDNA variants were associated with the disease. Most of the non-synonymous variants were heteroplasmic (A4136G, A9194G and T11916A) suggesting their possibility of being pathogenic in nature. Some of the missense variants although homoplasmic were showing changes in highly conserved amino acids (T3394C, T3866C, and G9804A) and were previously identified with diseased conditions. Similarly, two other variants found in tRNA genes (G5783A and C8309T) could alter the secondary structure of Cys-tRNA and Lys-tRNA. Most of the variants occurred in single cases; however, a few occurred in more than one case (e.g. G5783A and A10149T). CONCLUSIONS AND SIGNIFICANCE: The mtDNA variants identified in this study could be the possible cause of mitochondrial encephalomyopathies with childhood onset in the patient group. Our study further strengthens the pathogenic score of known variants previously reported as provisionally pathogenic in mitochondrial diseases. The novel variants found in the present study can be potential candidates for further investigations to establish the relationship between their incidence and role in expressing the disease phenotype. This study will be useful in genetic diagnosis and counseling of mitochondrial diseases in India as well as worldwide

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node’s remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node’s mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results

Optimized Group Channel Assignment Using Computational Geometry over Wireless Mesh Networks

Wireless Mesh Networks (WMNs) are an evolving division in the field of wireless networks due to their ease of deployment and assured last mile connectivity. It sets out a favorable situation to guarantee the Internet connectivity to all the mobile and static nodes. A wireless environment is dynamic, heterogeneous, and unpredictable as the nodes communicate through the unguided links called channels. The number of nonoverlapping channels available is less than the number of mesh nodes; hence, the same channel will be shared among many nodes. This scarcity of the channels causes interference and degrades the performance of the network. In this paper, we have presented a group based channel assignment method to minimize the interference. We have formulated a mathematical model using Nonlinear Programming (NLP). The objective function defines the channel assignment strategy which eventually reduces the interference. We have adapted the cognitive model of Discrete Particle Swarm Optimization (DPSO), for solving the optimization function. The channel assignment problem is an NP hard problem; hence, we have taken the benefits of a stochastic approach to find a solution that is optimal or near optimal. Finally, we have performed simulations to investigate the efficiency of our proposed work

Rank-Based Report Filtering Scheme (RRFS) for Verifying Phoney Reports in Wireless Sensor Networks

Wireless sensor networks (WSNs) are open to false data injection attack when they are deployed in hostile scenarios. Attackers can easily deceive the sink by compromising sensing nodes or by injecting phoney data into the network. Such attacks can deplete the energy resources of the network by providing wrong information which in turn can affect the proper network functioning or sometimes can shut the network from further functioning. The existing schemes that deal with this problem focus on only a few aspects of the false data injection attack. To resolve this problem, we propose a Rank-based Report Filtering Scheme (RRFS), a holistic and group verification scheme for the identification of compromised nodes and the filtering of false data injected into the network. The proposed scheme verifies report among clusters, en-routers, and sink. Hence, the RRFS, a holistic scheme that is composed of three-tier verifications, successfully rejects the false data before the attackers falsify the whole environment, and this makes the system unique. Reliability Index (RI) is calculated by the nodes for fellow cluster members, and the cluster head (CH) provides the score for a node based on its RI. This, in turn, strengthens the scheme by assisting the en-routers to detect the compromised nodes. The RRFS scheme has been verified and validated by extensive simulation and meticulous performance evaluation of filtering efficiency and energy consumption against various schemes. The scheme gives high filtering efficiency against the multiple compromised nodes and also improves the network’s lifespan. The sustainability of RRFS against numerous attacks that are launched in the sensor environment is thoroughly investigated

Privacy Preserved and Secured Reliable Routing Protocol for Wireless Mesh Networks

Privacy preservation and security provision against internal attacks in wireless mesh networks (WMNs) are more demanding than in wired networks due to the open nature and mobility of certain nodes in the network. Several schemes have been proposed to preserve privacy and provide security in WMNs. To provide complete privacy protection in WMNs, the properties of unobservability, unlinkability, and anonymity are to be ensured during route discovery. These properties can be achieved by implementing group signature and ID-based encryption schemes during route discovery. Due to the characteristics of WMNs, it is more vulnerable to many network layer attacks. Hence, a strong protection is needed to avoid these attacks and this can be achieved by introducing a new Cross-Layer and Subject Logic based Dynamic Reputation (CLSL-DR) mechanism during route discovery. In this paper, we propose a new Privacy preserved and Secured Reliable Routing (PSRR) protocol for WMNs. This protocol incorporates group signature, ID-based encryption schemes, and CLSL-DR mechanism to ensure strong privacy, security, and reliability in WMNs. Simulation results prove this by showing better performance in terms of most of the chosen parameters than the existing protocols