A novel 223 kb deletion in the beta-globin gene cluster was identified in a Chinese thalassemia major patient
INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY
Authors: Zhu, Fei; Wei, Xiaofeng; Cai, Decheng; Pang, Dejian; Zhong, Jianmei; Liang, Min; Zuo, Yangjin; Xu, Xiangmin; Shang, Xuan
Abstract
Introduction Although mutations in the human beta-globin gene cluster are essentially point mutations, several large deletions have been described in recent years. Methods We have identified a novel 223 kb deletion in a Chinese patient by multiplex ligation-dependent probe amplification and characterized it by next-generation sequencing, Gap-PCR, and DNA sequence analysis. Results The deletion extends from the 3 ' UTR of the delta globin gene (HBD) to 215 kb downstream of the HBB. Compound heterozygous with the typical beta-thalassemia-CD41-42(-CTTT) mutation, the proband presented with microcytosis and hypochromic red cells, and required regulate transfusion. The patient was clinically diagnosed with thalassemia major. Conclusion Our study widens the mutation spectrum of beta-thalassemia. In addition, this case may spark future studies of the regulatory regions of the beta-globin gene cluster.
Dragonfly optimization and constraint measure-based load balancing in cloud computing
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Authors: Polepally, Vijayakumar; Chatrapati, K. Shahu
Abstract
Load balancing is the significant task in the cloud computing because the cloud servers need to store avast amount of information which increases the load on the servers. The objective of the load balancing technique is that it maintains a trade-off on servers by distributing equal load with less power. Accordingly, this paper presents the load balancing technique based on the constraint measure. Initially, the capacity and load of each virtual machine are calculated. If the load of the virtual machine is greater than the balanced threshold value then,the load balancing algorithm is used for allocating the tasks. The load balancing algorithm calculates the deciding factor of each virtual machine and checks the load of the virtual machine. Then, it calculates the selection factor of each task. Then, the task which has better selection factor is allocated to the virtual machine. The performance of the proposed load balancing method is evaluated with the existing load balancing methods, such as HBB-LB, DLB, and HDLB for the evaluation metrics load and capacity. The experimental results show that the proposed method migrate only three tasks while the existing method HDLB migrates seven tasks.