Modulation of human cardiac function through 4 beta-adrenoceptor populations

In human heart there is now evidence for the involvement of four beta-adrenoceptor populations, three identical to the recombinant beta(1)-, beta(2)- and beta(3)-adrenoceptors, and a fourth as yet uncloned putative beta-adrenoceptor population, which we designate provisionally as the cardiac putative beta(4)-adrenoceptor. This review described novel features of beta-adrenoceptors as modulators of cardiac systolic and diastolic function. We also discuss evidence for modulation by unoccupied beta(1)- and beta(2)-adrenoceptors. Human cardiac and recombinant beta(1)- and beta(2)-adrenoceptors are both mainly coupled to adenylyl cyclase through Gs protein, the latter more tightly than the former. Activation of both human beta(1)- and beta(2)-adrenoceptors not only increases cardiac force during systole but also hastens relaxation through cyclic AMP-dependent phosphorylation of phospholamban and troponin I, thereby facilitating diastolic function. Furthermore, both beta(1) and beta(2)-adrenoceptors can mediate experimental arrhythmias in human cardiac preparations elicited by noradrenaline and adrenaline. Human ventricular beta(3)-adrenoceptors appear to be coupled to a pertussis toxin-sensitive protein (Gi?). beta(3)-Adrenoceptor-selective agonists shorten the action potential and cause cardiodepression, suggesting direct coupling of a Gi protein to a K+ channel. In a variety of species, including man, cardiac putative beta(4)-adrenoceptors mediate cardiostimulant effects of non-conventional partial agonists, i.e. high affinity beta(1)- and beta(2)-adrenoceptor blockers that cause agonist effects at concentrations considerably higher than those that block these receptors. Putative beta(4)-adrenoceptors appear to be coupled positively to a cyclic AMP-dependent cascade and can undergo some desensitisation.

A stochastic frontier production function with flexible risk properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures, An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.

Nuclear localization of RelB is associated with effective antigen-presenting cell function

Dendritic cells (DC) are potent APCs that enter resting tissues as precursors and, after Ag exposure, differentiate and migrate to draining lymph nodes. The phenotype of RelB knockout mice implicates this member of the NF kappa B/Rel family in DC differentiation. To further elucidate the role of RelB in DC differentiation, mRNA, intracellular protein expression, and DNA binding activity of RelB were examined in immature and differentiated human DC, as well as other PB mononuclear cell populations. RelB protein and mRNA were detected constitutively in lymphocytes and in activated monocytes, differentiated DC, and monocyte-derived DC. Immunohistochemical staining demonstrated RelB within the differentiated lymph node interdigitating DC and follicular DC, but not undifferentiated DC in normal skin. Active nuclear RelB was detected by supershift assay only in differentiated DC derived from either PB precursors or monocytes and in activated B cells. These RelB(+) APC were potent stimulators of the MLR. The data indicate that RelB expression is regulated both transcriptionally and post-translationally in myeloid cells. Within the nucleus, RelB may specifically transactivate genes that are critical for APC function.

Genetic association and cellular function of MC1R variant alleles in human pigmentation

We have examined MC1R variant allele frequencies in the general population of South East Queensland and in a collection of adolescent dizygotic and monozygotic twins and family members to define statistical associations with hair and skin color, freckling, and mole count. Results of these studies are consistent with a linear recessive allelic model with multiplicative penetrance in the inheritance of red hair. Four alleles, D84E, R151C, R160W, and D294H, are strongly associated with red hair and fair skin with multinomial regression analysis showing odds ratios of 63, 118, 50, and 94, respectively. An additional three low-penetrance alleles V60L, V92M, and R163Q have odds ratios 6, 5, and 2 relative to the wild-type allele. To address the cellular effects of MC1R variant alleles in signal transduction, we expressed these receptors in permanently transfected HEK293 cells. Measurement of receptor activity via induction of a cAMP-responsive luciferase reporter gene found that the R151C and R160W receptors were active in the presence of NDP-MSH ligand, but at much reduced levels compared with that seen with the wild-type receptor. The ability to stimulate phosphorylation of the cAMP response element binding protein (CREB) transcription factor was also apparent in all stimulated MC1R variant allele-expressing HEK293 cell extracts as assessed by immunoblotting. In contrast, human melanoma cell lines showed wide variation in the their ability to undergo cAMP-mediated CREB phosphorylation. Culture of human melanocytes of known MC1R genotype may provide the best experimental approach to examine the functional consequences for each MC1R variant allele. With this objective, we have established more than 300 melanocyte cell strains of defined MC1R genotype.

Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.