Animal models and clinical studies have linked the innate and adaptive immune system to the pathology of Parkinson’s disease (PD). Despite such progress, the specific immune responses that influence disease progression have eluded investigators. Herein, we assessed relationships between T cell phenotype and function with PD progression. Peripheral blood lymphocytes from two separate cohorts, a discovery cohort and a validation cohort, totaling 113 PD patients and 96 age- and environment-matched caregivers were examined by flow cytometric analysis and T cell proliferation assays. Increased effector/memory T cells (Tem), defined as CD45RO+ and FAS+ CD4+ T cells and decreased CD31+ and α4β7+ CD4+ T cells were associated with progressive Unified Parkinson’s Disease Rating Scale III scores. However, no associations were seen between immune biomarkers and increased age or disease duration. Impaired abilities of regulatory T cells (Treg) from PD patients to suppress effector T cell function was observed. These data support the concept that chronic immune stimulation, notably Tem activation and Treg dysfunction is linked to PD pathobiology and disease severity, but not disease duration. The association of T cell phenotypes with motor symptoms provides fresh avenues for novel biomarkers and therapeutic designs.

Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote locations. A large number of sensor nodes are deployed in the monitoring area. Therefore, deploying the minimum number of nodes that maintain full coverage and connectivity is of immense importance for research. Hence, coverage and connectivity issues, besides maximizing the network lifetime, represented the main concern to be considered in this survey. The key point of this paper is to classify different coverage techniques in WSNs into three main parts; coverage based on classical deployment techniques, coverage based on meta-heuristic techniques, and coverage based on self-scheduling techniques. Moreover, multiple comparisons among these techniques are provided considering their advantages and disadvantages. Additionally, performance metrics that must be considered in WSNs and comparison among different WSNs simulators are provided. In conclusion, open research issues are discussed as well as recommendations for researchers.

Natural killer (NK)-cell malignancies are among the most aggressive lymphoid neoplasms with very poor prognosis. We performed array comparative genomic hybridization analysis on a number of NK cell lines and primary tumors to gain better understanding of the pathogenesis and tumor biology of these malignancies. We also obtained transcriptional profiles of genes residing in these regions and compared them with normal and activated NK cells. Only 30–50% of the genes residing in the gained or deleted regions showed corresponding increased or decreased expression. However, many of the upregulated genes in regions of gain are functionally important for the proliferation and growth of the neoplastic population. Genes downregulated in regions of loss included many transcription factors or repressors, tumor suppressors or negative regulators of the cell cycle. The minimal common region of deletion in 6q21 included three known genes (PRDM1, ATG5 and AIM1) showing generally low expression. Mutations resulting in truncated PRDM1 and changes in conserved amino-acid sequences of AIM1 were detected. Highly methylated CpG islands 5′ of PRDM1 and AIM1 correlated with low expression of the transcripts. Reversal of methylation by Decitabine induced expression of PRDM1 and cell death. In conclusion, we have shown a general tumor-promoting effect of genetic alterations and have identified PRDM1 as the most likely target gene in del6q21. ATG5, an essential gene for autophagy and AIM1, a gene implicated in melanoma, may also participate in the functional abnormalities.

By comparing sequences of human, mouse and rat orthologous genes, we show that in 5'-untranslated regions (5'-UTRs) of mammalian cDNAs but not in 3'-UTRs or coding sequences, AUG is conserved to a significantly greater extent than any of the other 63 nt triplets. This effect is likely to reflect, primarily, bona fide evolutionary conservation, rather than cDNA annotation artifacts, because the excess of conserved upstream AUGs (uAUGs) is seen in 5'-UTRs containing stop codons in-frame with the start AUG and many of the conserved AUGs are found in different frames, consistent with the location in authentic non-coding sequences. Altogether, conserved uAUGs are present in at least 20-30% of mammalian genes. Qualitatively similar results were obtained by comparison of orthologous genes from different species of the yeast genus Saccharomyces. Together with the observation that mammalian and yeast 5'-UTRs are significantly depleted in overall AUG content, these findings suggest that AUG triplets in 5'-UTRs are subject to the pressure of purifying selection in two opposite directions: the uAUGs that have no specific function tend to be deleterious and get eliminated during evolution, whereas those uAUGs that do serve a function are conserved. Most probably, the principal role of the conserved uAUGs is attenuation of translation at the initiation stage, which is often additionally regulated by alternative splicing in the mammalian 5'-UTRs. Consistent with this hypothesis, we found that open reading frames starting from conserved uAUGs are significantly shorter than those starting from non-conserved uAUGs, possibly, owing to selection for optimization of the level of attenuation.

With the widespread usage of cloud computing to benefit from its services, cloud service providers have invested in constructing large scale data centers. Consequently, a tremendous increase in energy consumption has arisen in conjunction with its results, including a remarkable rise in costs of operating and cooling servers. Besides, increasing energy consumption has a significant impact on the environment due to emissions of carbon dioxide. Dynamic consolidation of Virtual Machines (VMs) into the minimal number of Physical Machines (PMs) is considered as one of the magic solutions to manage power consumption. The virtual machine placement problem is a critical issue for good VM consolidation. This paper proposes a Power-Aware technique depending on Particle Swarm Optimization (PAPSO) to determine the near-optimal placement for the migrated VMs. A discrete version of Particle Swarm Optimization (PSO) is adopted based on a decimal encoding to map the migrated VMs to the best appropriate PMs. Furthermore, an effective minimization fitness function is employed to reduce power consumption without violating the Service Level Agreement (SLA). Specifically, PAPSO consolidates the migrated VMs into the minimum number of PMs with a major constraint to decrease the number of overloaded hosts as much as possible. Therefore, the number of VM migrations can be reduced drastically by taking into consideration the main sources for VM migrations; overloaded hosts and underloaded ones. PAPSO is implemented in CloudSim and the experimental results on random workloads with different sizes of VMs and PMs show that PAPSO does not violate SLA and outperforms the Power-Aware Best Fit Decreasing algorithm (PABFD). It can reduce about 8.01%, 39.65%, 66.33%, and 11.87% on average in terms of consumed energy, number of VM migrations, number of host shutdowns and the combined metric Energy SLA Violation (ESV), respectively.