HIV dynamics and natural history studies: Joint modeling with doubly interval-censored event time and infrequent longitudinal data

Hepatitis C virus (HCV) coinfection has become one of the most challenging clinical situations to manage in HIV-infected patients. Recently the effect of HCV coinfection on HIV dynamics following initiation of highly active antiretroviral therapy (HAART) has drawn considerable attention. Post-HAART HIV dynamics are commonly studied in short-term clinical trials with frequent data collection design. For example, the elimination process of plasma virus during treatment is closely monitored with daily assessments in viral dynamics studies of AIDS clinical trials. In this article instead we use infrequent cohort data from long-term natural history studies and develop a model for characterizing post-HAART HIV dynamics and their associations with HCV coinfection. Specifically, we propose a joint model for doubly interval-censored data for the time between HAART initiation and viral suppression, and the longitudinal CD4 count measurements relative to the viral suppression. Inference is accomplished using a fully Bayesian approach. Doubly interval-censored data are modeled semiparametrically by Dirichlet process priors and Bayesian penalized splines are used for modeling population-level and individual-level mean CD4 count profiles. We use the proposed methods and data from the HIV Epidemiology Research Study (HERS) to investigate the effect of HCV coinfection on the response to HAART.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS391 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Mutations in Mtr4 Structural Domains Reveal Their Important Role in Regulating tRNA\u3csub\u3ei\u3c/sub\u3e \u3csup\u3eMet\u3c/sup\u3e Turnover in \u3cem\u3eSaccharomyces cerevisiae\u3c/em\u3e and Mtr4p Enzymatic Activities \u3cem\u3eIn Vitro\u3c/em\u3e

RNA processing and turnover play important roles in the maturation, metabolism and quality control of a large variety of RNAs thereby contributing to gene expression and cellular health. The TRAMP complex, composed of Air2p, Trf4p and Mtr4p, stimulates nuclear exosome-dependent RNA processing and degradation in Saccharomyces cerevisiae. The Mtr4 protein structure is composed of a helicase core and a novel so-called arch domain, which protrudes from the core. The helicase core contains highly conserved helicase domains RecA-1 and 2, and two structural domains of unclear functions, winged helix domain (WH) and ratchet domain. How the structural domains (arch, WH and ratchet domain) coordinate with the helicase domains and what roles they are playing in regulating Mtr4p helicase activity are unknown. We created a library of Mtr4p structural domain mutants for the first time and screened for those defective in the turnover of TRAMP and exosome substrate, hypomodified tRNAiMet. We found these domains regulate Mtr4p enzymatic activities differently through characterizing the arch domain mutants K700N and P731S, WH mutant K904N, and ratchet domain mutant R1030G. Arch domain mutants greatly reduced Mtr4p RNA binding, which surprisingly did not lead to significant defects on either in vivo tRNAiMet turnover, or in vitro unwinding activities. WH mutant K904N and Ratchet domain mutant R1030G showed decreased tRNAiMet turnover in vivo, as well as reduced RNA binding, ATPase and unwinding activities of Mtr4p in vitro. Particularly, K904 was found to be very important for steady protein levels in vivo. Overall, we conclude that arch domain plays a role in RNA binding but is largely dispensable for Mtr4p enzymatic activities, however the structural domains in the helicase core significantly contribute to Mtr4p ATPase and unwinding activities

Serotonin and motherhood: From molecules to mood

Emerging research points to a valuable role of the monoamine neurotransmitter, serotonin, in the display of maternal behaviors and reproduction-associated plasticity in the maternal brain. Serotonin is also implicated in the pathophysiology of numerous affective disorders and likely plays an important role in the pathophysiology of maternal mental illness. Therefore, the main goals of this review are to detail: 1) how the serotonin system of the female brain changes across pregnancy and postpartum; 2) the role of the central serotonergic system in maternal caregiving and maternal aggression; and 3) how the serotonin system and selective serotonin reuptake inhibitor medications (SSRIs) are involved in the treatment of maternal mental illness. Although there is much work to be done, studying the central serotonin system’s multifaceted role in the maternal brain is vital to our understanding of the processes governing matrescence and the maintenance of motherhood

Ferromagnetism in Fe-doped Ba6Ge25 Chiral Clathrate

We have successfully synthesized a Ba6Ge25 clathrate, substituting 3 Fe per formula unit by Ge. This chiral clathrate has Ge sites forming a framework of closed cages and helical tunnel networks. Fe atoms randomly occupy these sites, and exhibit high-spin magnetic moments. A ferromagnetic transition is observed with Tc = 170 K, the highest observed Tc for a magnetic clathrate. However, the magnetic phase is significantly disordered, and exhibits a transformation to a re-entrant spin glass phase. This system has a number of features in common with other dilute magnetic semiconductors.Comment: Submitted to Applied Physics Letters. Fig. 1 resolution reduced for online archive versio

Are hydrodynamic interactions important in the kinetics of hydrophobic collapse?

We study the kinetics of assembly of two plates of varying hydrophobicity, including cases where drying occurs and water strongly solvates the plate surfaces. The potential of mean force and molecular-scale hydrodynamics are computed from molecular dynamics simulations in explicit solvent as a function of particle separation. In agreement with our recent work on nanospheres [J. Phys. Chem. B 116, 378 (2012)] regions of high friction are found to be engendered by large and slow solvent fluctuations. These slow fluctuations can be due to either drying or confinement. The mean first passage times for assembly are computed by means of molecular dynamics simulations in explicit solvent and by Brownian dynamics simulations along the reaction path. Brownian dynamics makes use of the potential of mean force and hydrodynamic profile that we determined. Surprisingly, we find reasonable agreement between full scale molecular dynamics and Brownian dynamics, despite the role of slow solvent relaxation in the assembly process. We found that molecular scale hydrodynamic interactions are essential in describing the kinetics of assembly.Comment: 6 figures, 13 page

Sparse Matrix-based Random Projection for Classification

As a typical dimensionality reduction technique, random projection can be simply implemented with linear projection, while maintaining the pairwise distances of high-dimensional data with high probability. Considering this technique is mainly exploited for the task of classification, this paper is developed to study the construction of random matrix from the viewpoint of feature selection, rather than of traditional distance preservation. This yields a somewhat surprising theoretical result, that is, the sparse random matrix with exactly one nonzero element per column, can present better feature selection performance than other more dense matrices, if the projection dimension is sufficiently large (namely, not much smaller than the number of feature elements); otherwise, it will perform comparably to others. For random projection, this theoretical result implies considerable improvement on both complexity and performance, which is widely confirmed with the classification experiments on both synthetic data and real data