Modulation of Rab7a-mediated growth factor receptor trafficking inhibits islet beta cell apoptosis and autophagy under conditions of metabolic stress

Regenerative medicine approaches to enhancing beta cell growth and survival represent potential treatments for diabetes. It is known that growth factors such as insulin, IGF-1 and HGF support beta cell growth and survival, but in people with type 2 diabetes the destructive effects of metabolic stress predominate and beta cell death or dysfunction occurs. In this study we explore the novel hypothesis that regulation of growth factor receptor trafficking can be used to promote islet beta cell survival. Growth factor signalling is dependent on the presence of cell surface receptors. Endosomal trafficking and subsequent recycling or degradation of these receptors is controlled by the Rab GTPase family of proteins. We show that Rab7a siRNA inhibition enhances IGF-1 and HGF signalling in beta cells and increases expression of the growth factor receptors IGF-1R and c-Met. Furthermore, Rab7a inhibition promotes beta cell growth and islet survival, and protects against activation of apoptosis and autophagy pathways under conditions of metabolic stress. This study therefore demonstrates that Rab7a-mediated trafficking of growth factor receptors controls beta cell survival. Pharmaceutical Rab7a inhibition may provide a means to promote beta cell survival in the context of metabolic stress and prevent the onset of type 2 diabetes

Misregulation of Scm3p/HJURP Causes Chromosome Instability in Saccharomyces cerevisiae and Human Cells

The kinetochore (centromeric DNA and associated proteins) is a key determinant for high fidelity chromosome transmission. Evolutionarily conserved Scm3p is an essential component of centromeric chromatin and is required for assembly and function of kinetochores in humans, fission yeast, and budding yeast. Overexpression of HJURP, the mammalian homolog of budding yeast Scm3p, has been observed in lung and breast cancers and is associated with poor prognosis; however, the physiological relevance of these observations is not well understood. We overexpressed SCM3 and HJURP in Saccharomyces cerevisiae and HJURP in human cells and defined domains within Scm3p that mediate its chromosome loss phenotype. Our results showed that the overexpression of SCM3 (GALSCM3) or HJURP (GALHJURP) caused chromosome loss in a wild-type yeast strain, and overexpression of HJURP led to mitotic defects in human cells. GALSCM3 resulted in reduced viability in kinetochore mutants, premature separation of sister chromatids, and reduction in Cse4p and histone H4 at centromeres. Overexpression of CSE4 or histone H4 suppressed chromosome loss and restored levels of Cse4p at centromeres in GALSCM3 strains. Using mutant alleles of scm3, we identified a domain in the N-terminus of Scm3p that mediates its interaction with CEN DNA and determined that the chromosome loss phenotype of GALSCM3 is due to centromeric association of Scm3p devoid of Cse4p/H4. Furthermore, we determined that similar to other systems the centromeric association of Scm3p is cell cycle regulated. Our results show that altered stoichiometry of Scm3p/HJURP, Cse4p, and histone H4 lead to defects in chromosome segregation. We conclude that stringent regulation of HJURP and SCM3 expression are critical for genome stability

Signal transduction underlying the control of urinary bladder smooth muscle tone by muscarinic receptors and β-adrenoceptors

The normal physiological contraction of the urinary bladder, which is required for voiding, is predominantly mediated by muscarinic receptors, primarily the M3 subtype, with the M2 subtype providing a secondary backup role. Bladder relaxation, which is required for urine storage, is mediated by β-adrenoceptors, in most species involving a strong β3-component. An excessive stimulation of contraction or a reduced relaxation of the detrusor smooth muscle during the storage phase of the micturition cycle may contribute to bladder dysfunction known as the overactive bladder. Therefore, interference with the signal transduction of these receptors may be a viable approach to develop drugs for the treatment of overactive bladder. The prototypical signaling pathway of M3 receptors is activation of phospholipase C (PLC), and this pathway is also activated in the bladder. Nevertheless, PLC apparently contributes only in a very minor way to bladder contraction. Rather, muscarinic-receptor-mediated bladder contraction involves voltage-operated Ca2+ channels and Rho kinase. The prototypical signaling pathway of β-adrenoceptors is an activation of adenylyl cyclase with the subsequent formation of cAMP. Nevertheless, cAMP apparently contributes in a minor way only to β-adrenoceptor-mediated bladder relaxation. BKCa channels may play a greater role in β-adrenoceptor-mediated bladder relaxation. We conclude that apart from muscarinic receptor antagonists and β-adrenoceptor agonists, inhibitors of Rho kinase and activators of BKCa channels may have potential to treat an overactive bladder

Stressful situation if CENP-A not front and CENter

The exclusive localization of the histone H3 variant CENP-A to centromeres is essential for accurate chromosome segregation. Ubiquitin-mediated proteolysis helps to ensure that CENP-A does not mislocalize to euchromatin, which can lead to genomic instability. Consistent with this, overexpression of the budding yeast CENP-A(Cse4) is lethal in cells lacking Psh1, the E3 ubiquitin ligase that targets CENP-A(Cse4) for degradation. To identify additional mechanisms that prevent CENP-A(Cse4) misincorporation and lethality, we analyzed the genome-wide mislocalization pattern of overexpressed CENP-A(Cse4) in the presence and absence of Psh1 by chromatin immunoprecipitation followed by high throughput sequencing. We found that ectopic CENP-A(Cse4) is enriched at promoters that contain histone H2A.Z(Htz1) nucleosomes, but that H2A.Z(Htz1) is not required for CENP-A(Cse4) mislocalization. Instead, the INO80 complex, which removes H2A.Z(Htz1) from nucleosomes, promotes the ectopic deposition of CENP-A(Cse4). Transcriptional profiling revealed gene expression changes in the psh1Δ cells overexpressing CENP-A(Cse4). The down-regulated genes are enriched for CENP-A(Cse4) mislocalization to promoters, while the up-regulated genes correlate with those that are also transcriptionally up-regulated in an htz1Δ strain. Together, these data show that regulating centromeric nucleosome localization is not only critical for maintaining centromere function, but also for ensuring accurate promoter function and transcriptional regulation

Rule mining and classification in imperfect databases

A rule-based classifier learns rules from a set of training data instances with assigned class labels and then uses those rules to assign a class label for a new incoming data instance. To accommodate data imperfections, a probabilistic relational model would represent the attributes by probabilistic functions. One extension to this model uses belief functions instead. Such an approach can represent a wider range of data imperfections. However, the task of extracting frequent patterns and rules from such a "belief theoretic" relational database has to overcome a potentially enormous computational burden. In this work, we present a data structure that is an alternate representation of a belief theoretic relational database. We then develop efficient algorithms to query for belief of item sets, extract frequent item sets and generate corresponding association rules from this representation. This set of rules is then used as the basis on which an unknown data instance, whose attributes are represented via belief functions, is classified. These algorithms are tested on a data set collected from a test bed that mimics airport threat detection and classification scenario where both data attributes and threat class labels may possess imperfections

Validation of the Algase Wandering Scale (Version 2) in a cross cultural sample

This study examined the psychometric properties of an expanded version of the Algase Wandering Scale (Version 2) (AWS-V2) in a cross-cultural sample. A cross-sectional survey design was used. Study subjects were 172 English-speaking persons with dementia (PWD) from long-term care facilities in the USA, Canada, and Australia. Two or more facility staff rated each subject on the AWS-V2. Demographic and cognitive data (MMSE) were also obtained. Staff provided information on their own knowledge of the subject and of dementia. Separate factor analyses on data from two samples of raters each explained greater than 66% of the variance in AWS-V2 scores and validated four (persistent walking, navigational deficit, eloping behavior, and shadowing) of five factors in the original scale. Items added to create the AWS-V2 strengthened the shadowing subscale, failed to improve the routinized walking subscale, and added a factor, attention shifting as compared to the original AWS. Evidence for validity was found in significant correlations and ANOVAs between the AWS-V2 and most subscales with a single item indicator of wandering and with the MMSE. Evidence of reliability was shown by internal consistency of the AWS-V2 (0.87, 0.88) and its subscales (range 0.88 to 0.66), with Kappa for individual items (17 of 27 greater than 0.4), and ANOVAs comparing ratings across rater groups (nurses, nurse aids, and other staff). Analyses support validity and reliability of the AWS-V2 overall and for persistent walking, spatial disorientation, and eloping behavior subscales. The AWS-V2 and its subscales are an appropriate way to measure wandering as conceptualized within the Need-driven Dementia-compromised Behavior Model in studies of English-speaking subjects. Suggestions for further strengthening the scale and for extending its use to clinical applications are described

Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method

This chapter introduces a belief theoretic method for classification from databases having class label ambiguities. It uses a set of association rules extracted from such a database. It is assumed that a training data set with an adequate number of pre-classified instances, where each instance is assigned with an integer class label, is available. We use a modified association rule mining (ARM) technique to extract the interesting rules from the training data set and use a belief theoretic classifier based on the extracted rules to classify the incoming feature vectors. The ambiguity modelling capability of belief theory enables our classifier to perform better in the presence of class label ambiguities. It can also address the issue of the training data set being unbalanced or highly skewed by ensuring that an approximately equal number of rules are generated for each class. All these capabilities make our classifier ideally suited for those applications where (1) different experts may have conflicting opinions about the class label to be assigned to a specific training data instance; and (2) the majority of the training data instances are likely to represent a few classes giving rise to highly skewed databases. Therefore, the proposed classifier would be extremely useful in security monitoring and threat classification environments where conflicting expert opinions about the threat level are common and only a few training data instances would be considered to pose a heightened threat level. Several experiments are conducted to evaluate our proposed classifier. These experiments use several databases from the UCI data repository and data sets collected from the airport terminal simulation platform developed at the Distributed Decision Environments (DDE) Laboratory at the Department of Electrical and Computer Engineering, University of Miami. The experimental results show that, while the proposed classifier’s performance is comparable to some existing classifiers when the databases have no class label ambiguities, it provides superior classification accuracy and better efficiency when class label ambiguities are present