The impact of point mutations in the human androgen receptor : classification of mutations on the basis of transcriptional activity

Peer reviewedPublisher PD

Engineering live cell surfaces with functional polymers via cytocompatible controlled radical polymerization

The capability to graft synthetic polymers onto the surfaces of live cells offers the potential to manipulate and control their phenotype and underlying cellular processes. Conventional grafting-to strategies for conjugating preformed polymers to cell surfaces are limited by low polymer grafting efficiency. Here we report an alternative grafting-from strategy for directly engineering the surfaces of live yeast and mammalian cells through cell surface-initiated controlled radical polymerization. By developing cytocompatible PET-RAFT (photoinduced electron transfer-reversible addition-fragmentation chain-transfer polymerization), synthetic polymers with narrow polydispersity (M w /M n < 1.3) could be obtained at room temperature in 5.minutes. This polymerization strategy enables chain growth to be initiated directly from chain-transfer agents anchored on the surface of live cells using either covalent attachment or non-covalent insertion, while maintaining high cell viability. Compared with conventional grafting-to approaches, these methods significantly improve the efficiency of grafting polymer chains and enable the active manipulation of cellular phenotypes

Neurobiology of social behavior abnormalities in autism and Williams syndrome

Social behavior is a basic behavior mediated by multiple brain regions and neural circuits, and is crucial for the survival and development of animals and humans. Two neuropsychiatric disorders that have prominent social behavior abnormalities are autism spectrum disorders (ASD), which is characterized mainly by hyposociability, and Williams syndrome (WS), whose subjects exhibit hypersociability. Here we review the unique properties of social behavior in ASD and WS, and discuss the major theories in social behavior in the context of these disorders. We conclude with a discussion of the research questions needing further exploration to enhance our understanding of social behavior abnormalities

Haplotype-based quantitative trait mapping using a clustering algorithm

BACKGROUND: With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention. RESULTS: We recently developed an association mapping method for complex diseases by mining the sharing of haplotype segments (i.e., phased genotype pairs) in affected individuals that are rarely present in normal individuals. In this paper, we extend our previous work to address the problem of quantitative trait mapping from unrelated individuals. The method is non-parametric in nature, and statistical significance can be obtained by a permutation test. It can also be incorporated into the one-way ANCOVA (analysis of covariance) framework so that other factors and covariates can be easily incorporated. The effectiveness of the approach is demonstrated by extensive experimental studies using both simulated and real data sets. The results show that our haplotype-based approach is more robust than two statistical methods based on single markers: a single SNP association test (SSA) and the Mann-Whitney U-test (MWU). The algorithm has been incorporated into our existing software package called HapMiner, which is available from our website at . CONCLUSION: For QTL (quantitative trait loci) fine mapping, to identify QTNs (quantitative trait nucleotides) with realistic effects (the contribution of each QTN less than 10% of total variance of the trait), large samples sizes (≥ 500) are needed for all the methods. The overall performance of HapMiner is better than that of the other two methods. Its effectiveness further depends on other factors such as recombination rates and the density of typed SNPs. Haplotype-based methods might provide higher power than methods based on a single SNP when using tag SNPs selected from a small number of samples or some other sources (such as HapMap data). Rank-based statistics usually have much lower power, as shown in our study

Quantitative Modeling of Currents from a Voltage Gated Ion Channel Undergoing Fast Inactivation

Ion channels play a central role in setting gradients of ion concentration and electrostatic potentials, which in turn regulate sensory systems and other functions. Based on the structure of the open configuration of the Kv1.2 channel and the suggestion that the two ends of the N-terminal inactivating peptide form a bivalent complex that simultaneously blocks the channel pore and binds to the cytoplasmic T1 domain, we propose a six state kinetic model that for the first time reproduces the kinetics of recovery of the Drosophila Shaker over the full range of time scales and hyperpolarization potentials, including tail currents. The model is motivated by a normal mode analysis of the inactivated channel that suggests that a displacement consistent with models of the closed state propagates to the T1 domain via the S1-T1 linker. This motion stretches the bound (inactivating) peptide, hastening the unblocking of the pore. This pulling force is incorporated into the rates of the open to blocked states, capturing the fast recovery phase of the current for repolarization events shorter than 1 ms. If the membrane potential is hyperpolarized, essential dynamics further suggests that the T1 domain returns to a configuration where the peptide is unstretched and the S1-T1 linker is extended. Coupling this novel hyperpolarized substate to the closed, open and blocked pore states is enough to quantitatively estimate the number of open channels as a function of time and membrane potential. A straightforward prediction of the model is that a slow ramping of the potential leads to very small currents

A vision-based system to support tactical and physical analyses in futsal

This paper presents a vision-based system to support tactical and physical analyses of futsal teams. Most part of the current analyses in this sport are manually performed, while the existing solutions based on automatic approaches are frequently composed of costly and complex tools, developed for other kind of team sports, making it difficult their adoption by futsal teams. Our system, on the other hand, represents a simple yet efficient dedicated solution, which is based on the analyses of image sequences captured by a single stationary camera used to obtain top-view images of the entire court. We use adaptive background subtraction and blob analysis to detect players, as well as particle filters to track them in every video frame. The system determines the distance traveled by each player, his/her mean and maximum speeds, as well as generates heat maps that describe players’ occupancy during the match. To present the collected data, our system uses a specially developed mobile application. Experimental results with image sequences of an official match and a training match show that our system provides data with global mean tracking errors below 40 cm, demanding on 25 ms to process each frame and, thus, demonstrating its high application potential