Epigenetics: a link between addiction and social environment

The detrimental effects of drug abuse are apparently not limited to individuals but may also impact the vulnerability of their progenies to develop addictive behaviours. Epigenetic signatures, early life experience and environmental factors, converge to influence gene expression patterns in addiction phenotypes and consequently may serve as mediators of behavioural trait transmission between generations. The majority of studies investigating the role of epigenetics in addiction do not consider the influence of social interactions. This shortcoming in current experimental approaches necessitates developing social models that reflect the addictive behaviour in a free-living social environment. Furthermore, this review also reports on the advancement of interventions for drug addiction and takes into account the emerging roles of histone deacetylase (HDAC) inhibitors in the etiology of drug addiction and that HDAC may be a potential therapeutic target at nucleosomal level to improve treatment outcomes.     

Visual perception and memory systems: from cortex to medial temporal lobe

Visual perception and memory are the most important components of vision processing in the brain. It was thought that the perceptual aspect of a visual stimulus occurs in visual cortical areas and that this serves as the substrate for the formation of visual memory in a distinct part of the brain called the medial temporal lobe. However, current evidence indicates that there is no functional separation of areas. Entire visual cortical pathways and connecting medial temporal lobe are important for both perception and visual memory. Though some aspects of this view are debated, evidence from both sides will be explored here. In this review, we will discuss the anatomical and functional architecture of the entire system and the implications of these structures in visual perception and memory.     

Altered expression of securin (Pttg1) and serpina3n in the auditory system of hearing-impaired Tff3-deficient mice

Introduction

Tff3 peptide exerts important functions in cytoprotection and restitution of the gastrointestinal (GI) tract epithelia. Moreover, its presence in the rodent inner ear and involvement in the hearing process was demonstrated recently. However, its role in the auditory system still remains elusive. Our previous results showed a deterioration of hearing with age in Tff3-deficient animals.

Results

Present detailed analysis of auditory brain stem response (ABR) measurements and immunohistochemical study of selected functional proteins indicated a normal function and phenotype of the cochlea in Tff3 mutants. However, a microarray-based screening of tissue derived from the auditory central nervous system revealed an alteration of securin (Pttg1) and serpina3n expression between wild-type and Tff3 knock-out animals. This was confirmed by qRT-PCR, immunostaining and western blots.

Conclusions

We found highly down-regulated Pttg1 and up-regulated serpina3n expression as a consequence of genetically deleting Tff3 in mice, indicating a potential role of these factors during the development of presbyacusis.     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

Regulation of iron homeostasis by microRNAs

Iron homeostasis is maintained at the cellular and systemic levels to assure adequate iron supply while preventing iron overload. The identification of genes mutated in patients with iron-related disorders or animal models with imbalances of iron homeostasis gave insight into the molecular mechanisms underlying processes critical for balancing iron levels, such as iron uptake, storage, export, and monitoring of available iron. MicroRNAs control genes involved in some of these processes adding an additional level of complexity to the regulation of iron metabolism. This review summarizes recent advances how miRNAs regulate iron homeostasis.     

考虑轴颈偏斜时滑动轴承的动力特性

本文建立了同时考虑轴颈径向位移和歪斜时的滑动轴承动力学模型.对于这种模型,油膜力将扩展为四个广义力分量.文章将相应的动力系数矩阵分解为对称和反对称两部分并讨论其物理性质.然后,本文推导得出该模型的正交变换矩阵,在此基础上导得各向同性的动力系数矩阵表达式,并讨论了诸元素的物理意义.文章最后引入动力系数椭圆的概念以分析非对称动力系数矩阵的变换性质.