Sex chromosome complement affects social interactions in mice

Sex differences in behavior can be attributed to differences in steroid hormones. Sex chromosome complement can also influence behavior, independent of gonadal differentiation. The mice used for this work combined a spontaneous mutation of the Sry gene with a transgene for Sry that is incorporated into an autosome thus disassociating gonad differentiation from sex chromosome complement. The resulting genotypes are XX and XY⁻ females (ovary-bearing) along with XXSry and XY⁻Sry males (testes-bearing). Here we report results of basic behavioral phenotyping conducted with these mice. Motor coordination, use of olfactory cues to find a food item, general activity, foot shock threshold, and behavior in an elevated plus maze were not affected by gonadal sex or sex chromosome complement. In a one-way active avoidance learning task females were faster to escape an electric shock than males. In addition, sex chromosome complement differences were noted during social interactions with submissive intruders. Female XY⁻ mice were faster to follow an intruder than XX female mice. All XY⁻ mice spent more time sniffing and grooming the intruder than the XX mice, with XY⁻ females spending the most amount of time in this activity. Finally, XX females were faster to display an asocial behavior, digging, and engaged in more digging than XXSry male mice. All of these behaviors were tested in gonadectomized adults, thus, differences in circulating levels of gonadal steroids cannot account for these effects. Taken together, these data show that sex chromosome complement affects social interaction style in mice.     

DNA芯片在0-1规划问题中的应用

生物芯片技术和DNA计算分别是近年来生命科学与信息科学的新兴研究领域,对信息高度并行的获取与处理是二者的本质特性.而0-1规划问题作为运筹学中一个重要的问题,到目前为止还没有好的算法.在DNA计算和DNA芯片基础上,提出了基于DNA芯片解决0-1规划问题的DNA计算新模型,与以往DNA计算模型相比,该模型具有高信息量和操作易自动化的优点.同时指出DNA芯片技术有望作为新型生物计算的芯片.     

Key Message Approach to Optimize Communication of Parallel Applications on Clusters

Over the past few years, cluster/distributed computing has been gaining popularity. The proliferation of the cluster/distributed computing is due to the improved performance and increased reliability of these systems. Many parallel programming languages and related parallel programming models have become widely accepted. However, one of the major shortcomings of running parallel applications on cluster/distributed computing environments is the high communication overhead incurred. To reduce the communication overhead, and thus the completion time of a parallel application, this paper describes a simple, efficient and portable Key Message (KM) approach to support parallel computing on cluster/distributed computing environments. To demonstrate the advantage of the KM approach, a prototype runtime system has been implemented and evaluated. Our preliminary experimental results show that the KM approach has better improvement on communication of a parallel application when network background load increases or the computation to communication ratio of the application decreases.     

Experimental Analysis of a Gossip-Based Service for Scalable, Distributed Failure Detection and Consensus

Gossip protocols and services provide a means by which failures can be detected in large, distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. Extending the gossip protocol such that a system reaches consensus on detected faults can be performed via a flat structure, or it can be hierarchically distributed across cooperating layers of nodes. In this paper, the performance of gossip services employing flat and hierarchical schemes is analyzed on an experimental testbed in terms of consensus time, resource utilization and scalability. Performance associated with a hierarchically arranged gossip scheme is analyzed with varying group sizes and is shown to scale well. Resource utilization of the gossip-style failure detection and consensus service is measured in terms of network bandwidth utilization and CPU utilization. Analytical models are developed for resource utilization and performance projections are made for large system sizes.     

Condor-G: A Computation Management Agent for Multi-Institutional Grids

In recent years, there has been a dramatic increase in the number of available computing and storage resources. Yet few tools exist that allow these resources to be exploited effectively in an aggregated form. We present the Condor-G system, which leverages software from Globus and Condor to enable users to harness multi-domain resources as if they all belong to one personal domain. We describe the structure of Condor-G and how it handles job management, resource selection, security, and fault tolerance. We also present results from application experiments with the Condor-G system. We assert that Condor-G can serve as a general-purpose interface to Grid resources, for use by both end users and higher-level program development tools.     

Stress Upregulates TPH1 but not TPH2 mRNA in the Rat Dorsal Raphe Nucleus: Identification of Two TPH2 mRNA Splice Variants

Serotonin is implicated in stress-related psychopathologies. Two isoforms of the rate-limiting enzyme of serotonin biosynthesis, tryptophan hydroxylase, TPH1 and TPH2, are known. We show here that in the rat dorsal raphe nucleus (DRN), the nucleus that contains the highest number of 5-HT neurons in the brain, TPH1 mRNA reveals a low level of expression but is detectable both by quantitative real-time PCR and in situ hybridization whereas in the pineal gland (PiG), TPH1 mRNA is strongly expressed. To examine effects of stress on TPH expression we exposed male Wistar rats to daily restraint stress for 1 week. As shown by quantitative real-time PCR, TPH1 mRNA is 2.5-fold upregulated by the stress in DRN but not in PiG. Using 3′-RACE, we identified two TPH2 mRNA splice variants in the rat DRN which differ in the length of their 3′-untranslated regions (UTRs). TPH2b (with a short 3′-UTR) is the predominant variant in the DRN, whereas TPH2a (with a longer 3′-UTR) shows a low abundance in this nucleus. In the PiG, only TPH2b is detectable revealing a low level of expression. Expression of both TPH2 splice variants is not affected by stress, neither in DRN nor in the PiG. These data indicate that TPH1 in the serotonergic neurons of the DRN might be relevant for stress-induced psychopathologies.     

An evolutionary Monte Carlo algorithm for predicting DNA hybridization

Many DNA-based technologies, such as DNA computing, DNA nanoassembly and DNA biochips, rely on DNA hybridization reactions. Previous hybridization models have focused on macroscopic reactions between two DNA strands at the sequence level. Here, we propose a novel population-based Monte Carlo algorithm that simulates a microscopic model of reacting DNA molecules. The algorithm uses two essential thermodynamic quantities of DNA molecules: the binding energy of bound DNA strands and the entropy of unbound strands. Using this evolutionary Monte Carlo method, we obtain a minimum free energy configuration in the equilibrium state. We applied this method to a logical reasoning problem and compared the simulation results with the experimental results of the wet-lab DNA experiments performed subsequently. Our simulation predicted the experimental results quantitatively.     

与非门(NAND)的DNA计算模型

近年来,随着DNA计算研究的深入,基于DNA的布尔电路的模拟成为其中一个热门的研究方向.分子信标是一种特殊的探针分子,广泛应用于各种生物技术的检测方面,具有结果稳定,特异性强的优点,本文提出了一种基于诱导"发夹"形式的DNA与非门模型,和已有的模型相比,该模型具有简单,可靠性更高且可以重复使用等优点.     

Computing by polymerase chain reaction

A mathematical notation is introduced to represent, at a symbolic level, different mechanisms of DNA recombination, and a 'PCR lemma' is proven by analytically describing the combinatorial properties of the polymerase chain reaction process. This approach led to the discovery of novel techniques, based on a form of PCR which we called cross pairing PCR (briefly XPCR). They were mathematically analyzed and already experimentally proven in different contexts, such as DNA extraction and recombination. Thus, a mathematical analysis of standard methodologies may highlight novel mechanisms of DNA recombination and this can provide new technologies for DNA manipulation.