Assembly, trafficking and function of gamma-secretase

gamma-Secretase catalyzes the final cleavage of the beta-amyloid precursor protein to generate amyloid-beta peptide, the principal component of amyloid plaques in the brains of patients suffering from Alzheimer's disease. Here, we review the identification of gamma-secretase as a protease complex and its assembly and trafficking to its site(s) of cellular function. In reconstitution experiments, gamma-secretase was found to be composed of four integral membrane proteins, presenilin (PS), nicastrin (NCT), PEN-2 and APH-1 that are essential and sufficient for gamma-secretase activity. PS, which serves as a catalytic subunit of gamma-secretase, was identified as a prototypic member of novel aspartyl proteases of the GxGD type. In human cells, gamma-secretase could be further defined as a heterogeneous activity consisting of distinct complexes that are composed of PS1 or PS2 and APH-1a or APH-1b homologues together with NCT and PEN-2. Using green fluorescent protein as a reporter we localized PS and gamma-secretase activity at the plasma membrane and endosomes. Investigation of gamma-secretase complex assembly in knockdown and knockout cells of the individual subunits allowed us to develop a model of complex assembly in which NCT and APH-1 first stabilize PS before PEN-2 assembles as the last component. Furthermore, we could map domains in PS and PEN-2 that govern assembly and trafficking of the complex. Finally, Rer1 was identified as a PEN-2-binding protein that serves a role as an auxiliary factor for gamma-secretase complex assembly. Copyright (c) 2006 S. Karger AG, Basel

Associations between SNPs and immune-related circulating proteins in schizophrenia

Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered

Evaluating three decades of the European Capital of Culture programme: a difference-in-differences approach

We measure the regional impact of the European Capital of Culture programme using a difference-in-differences approach. We compare the regions of cities that hosted the event with the regions of cities that tried to host it but did not succeed. GDP per capita in hosting regions is 4.5 percent higher compared to non-hosting regions during the event and the effect persists more than 5 years after it. This result suggests that the economic dimension of the event is important and supports claims that the event serves as catalyst for urban regeneration and development

Issues in the management of simple and complex meconium ileus

Various surgical methods are used to treat meconium ileus (MI), including resection with enterostomy (RES), primary anastomosis (RPA), and purse-string enterotomy with intra-operative lavage (PSI). The aim of this study is to discuss the surgical treatment of MI, based on our experience. Of the 41 MI patients treated at our institution between 1984 and 2007, 18 had simple MI and 23 had complex MI. These groups were analyzed according to treatment modality, concentrating on length of hospital stay, complications [peritonitis, septicemia, adhesive small bowel obstruction (ASBO), and malabsorption/diarrhea], need for additional surgical procedures, mortality. Of the 18 patients with simple MI, 7 (39%) were successfully treated with diluted Gastrografin® enema. The remaining 11 patients were treated surgically: two underwent RPA, of whom one died; five had RES, of whom one developed ASBO; four underwent PSI, of whom two developed peritonitis. In the complex MI group, 14 patients underwent RPA, with peritonitis occurring in three (one died); nine underwent RES, of whom two developed ASBO. In patients with simple MI, conservative treatment with diluted Gastrografin® enema is an effective initial treatment in our hands. In case of failure, RES is advisable. Patients with complex MI are candidates for RES. RPA and PSI seem to have higher complication rate

Search for time-dependent B0s - B0s-bar oscillations using a vertex charge dipole technique

We report a search for B0s - B0s-bar oscillations using a sample of 400,000 hadronic Z0 decays collected by the SLD experiment. The analysis takes advantage of the electron beam polarization as well as information from the hemisphere opposite that of the reconstructed B decay to tag the B production flavor. The excellent resolution provided by the pixel CCD vertex detector is exploited to cleanly reconstruct both B and cascade D decay vertices, and tag the B decay flavor from the charge difference between them. We exclude the following values of the B0s - B0s-bar oscillation frequency: Delta m_s < 4.9 ps-1 and 7.9 < Delta m_s < 10.3 ps-1 at the 95% confidence level.Comment: 18 pages, 3 figures, replaced by version accepted for publication in Phys.Rev.D; results differ slightly from first versio

Mutant INS-Gene Induced Diabetes of Youth: Proinsulin Cysteine Residues Impose Dominant-Negative Inhibition on Wild-Type Proinsulin Transport

Recently, a syndrome of Mutant INS-gene-induced Diabetes of Youth (MIDY, derived from one of 26 distinct mutations) has been identified as a cause of insulin-deficient diabetes, resulting from expression of a misfolded mutant proinsulin protein in the endoplasmic reticulum (ER) of insulin-producing pancreatic beta cells. Genetic deletion of one, two, or even three alleles encoding insulin in mice does not necessarily lead to diabetes. Yet MIDY patients are INS-gene heterozygotes; inheritance of even one MIDY allele, causes diabetes. Although a favored explanation for the onset of diabetes is that insurmountable ER stress and ER stress response from the mutant proinsulin causes a net loss of beta cells, in this report we present three surprising and interlinked discoveries. First, in the presence of MIDY mutants, an increased fraction of wild-type proinsulin becomes recruited into nonnative disulfide-linked protein complexes. Second, regardless of whether MIDY mutations result in the loss, or creation, of an extra unpaired cysteine within proinsulin, Cys residues in the mutant protein are nevertheless essential in causing intracellular entrapment of co-expressed wild-type proinsulin, blocking insulin production. Third, while each of the MIDY mutants induces ER stress and ER stress response; ER stress and ER stress response alone appear insufficient to account for blockade of wild-type proinsulin. While there is general agreement that ultimately, as diabetes progresses, a significant loss of beta cell mass occurs, the early events described herein precede cell death and loss of beta cell mass. We conclude that the molecular pathogenesis of MIDY is initiated by perturbation of the disulfide-coupled folding pathway of wild-type proinsulin

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets