Straightening out the concept of direct and indirect input requirements

Gim & Kim (1998) proposed a generalization of Jeong (1982, 1984) reinterpretation of the Hawkins-Simon condition for macroeconomic stability to off-diagonal matrix elements. This generalization is conceptually relevant for it offers a complementary view of interindustry linkages beyond final or net output influence. The extension is completely similar to the 'total flow' idea introduced by Szyrmer (1992) or the 'output-to-output' multiplier of Miller & Blair (2009). However the practical implementation of Gim & Kim is actually faulty since it confuses the appropriate order of output normalization. We provide a new and elementary solution for the correct formalization using standard interindustry accounting concepts.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Analysis of angiotensin II- and ACTH-driven mineralocorticoid functions and omental adiposity in a non-genetic, hyperadipose female rat phenotype

The hypothalamic damage induced by neonatal treatment with monosodium l-glutamate (MSG) induces several metabolic abnormalities, resulting in a rat hyperleptinemic-hyperadipose phenotype. This study was conducted to explore the impact of the neonatal MSG treatment, in the adult (120 days old) female rat on: (a) the in vivo and in vitro mineralocorticoid responses to ACTH and angiotensin II (AII); (b) the effect of leptin on ACTH- and AII-stimulated mineralocorticoid secretions by isolated corticoadrenal cells; and (c) abdominal adiposity characteristics. Our data indicate that, compared with age-matched controls, MSG rats displayed: (1) enhanced and reduced mineralocorticoid responses to ACTH and AII treatments, respectively, effects observed in both in vivo and in vitro conditions; (2) adrenal refractoriness to the inhibitory effect of exogenous leptin on ACTH-stimulated aldosterone output by isolated adrenocortical cells; and (3) distorted omental adiposity morphology and function. This study supports that the adult hyperleptinemic MSG female rat is characterized by enhanced ACTH-driven mineralocorticoid function, impaired adrenal leptin sensitivity, and disrupted abdominal adiposity function. MSG rats could counteract undesirable effects of glucocorticoid excess, by developing a reduced AII-driven mineralocorticoid function. Thus, chronic hyperleptinemia could play a protective role against ACTH-mediated allostatic loads in the adrenal leptin resistant, MSG female rat phenotype.

Influence of epidermal growth factor on the maturation of fetal rat brain cells in aggregate culture. An immunocytochemical study.

Maturation of astrocytes, neurons, and oligodendrocytes was studied in serum-free aggregating cell cultures of fetal rat telencephalon by an immunocytochemical approach. Cell type-specific immunofluorescence staining was examined by using antibodies directed against glial fibrillary acidic protein (GFAP) and vimentin, two astroglial markers; neuron-specific enolase (NSE) and neurofilament (NF), two neuronal markers, and galactocerebroside (GC), an oligodendroglial marker. It was found that the cellular maturation in aggregates is characterized by distinct developmental increases in immunoreactivity for GFAP, vimentin, NSE, NF, and GC, and by a subsequent decrease of vimentin-positive structures in more differentiated cultures. These findings are in agreement with observations in vivo, and they corroborate previous biochemical studies of this histotypic culture system. Treatment of very immature cultures with a low dose of epidermal growth factor (EGF, 5 ng/ml) enhanced the developmental increase in GFAP, NSE, NF and GC immunoreactivity, suggesting an acceleration of neuronal and glial maturation. In addition, EGF was found to alter the cellular organization within the aggregates, presumably by influencing cell migration.

Diseño e implementación de un framework de persistencia

Los Frameworks constituyen el nuevo paradigma en cuanto al desarrollo de software se refiere. Entre sus principales características se encuentran la facilidad para la reutilización de código. En este marco específico proporcionados por la tecnología usaremos la tecnología JAVA y su extensión en cuanto a la persistencia de datos. El Framework de persistencia es el responsable de gestionar la lógica de acceso a los datos en un SGBD (Sistema de Gestión de Bases de Datos), ya sea de entrada o salida, y ocultando los detalles más pesados relativos a la estructura propia de la Base de Datos utilizada, de manera completa y transparentemente. En conclusión, este proyecto se basa en un análisis del los Frameworks existentes, analizando sus características y profundizando en los detalles concretos de su actividad y manejo en cuanto a la persistencia.

CODAPACK3D. A new version of Compositional Data Package

The statistical analysis of compositional data should be treated using logratios of parts,which are difficult to use correctly in standard statistical packages. For this reason afreeware package, named CoDaPack was created. This software implements most of thebasic statistical methods suitable for compositional data.In this paper we describe the new version of the package that now is calledCoDaPack3D. It is developed in Visual Basic for applications (associated with Excel©),Visual Basic and Open GL, and it is oriented towards users with a minimum knowledgeof computers with the aim at being simple and easy to use.This new version includes new graphical output in 2D and 3D. These outputs could bezoomed and, in 3D, rotated. Also a customization menu is included and outputs couldbe saved in jpeg format. Also this new version includes an interactive help and alldialog windows have been improved in order to facilitate its use.To use CoDaPack one has to access Excel© and introduce the data in a standardspreadsheet. These should be organized as a matrix where Excel© rows correspond tothe observations and columns to the parts. The user executes macros that returnnumerical or graphical results. There are two kinds of numerical results: new variablesand descriptive statistics, and both appear on the same sheet. Graphical output appearsin independent windows. In the present version there are 8 menus, with a total of 38submenus which, after some dialogue, directly call the corresponding macro. Thedialogues ask the user to input variables and further parameters needed, as well aswhere to put these results. The web site http://ima.udg.es/CoDaPack contains thisfreeware package and only Microsoft Excel© under Microsoft Windows© is required torun the software.Kew words: Compositional data Analysis, Software

Analysis of GPCR properties of Frizzled receptors and establishment of the "in vitro" platform for screening of Frizzled agonists/antagonists as potential therapeutic agents

Morphogens of the Wnt protein family are the secreted lipoglycoprotein ligands which initiate several pathways heavily involved in the coordination of various developmental stages of organisms in the majority of animal species. Deregulation of these pathways in the adult leads to formation and sustaining of multiple types of cancer. The latter notion is reinforced by the fact that the very discovery of the first Wnt ligand was due to its role as the causative factor of carcinogenic transformation (Nusse and Varmus, 1982). Nowadays our knowledge on Wnt signaling has "moved with the times" and these pathways were identified to be often crucial for tumor formation, its interactions with the microenvironment, and promotion of the metastases (Huang and Du, 2008; Zerlin et al., 2008; Jessen, 2009). Thus the relevance of the pathway as the target for drug development has further increased in the light of modern paradigms of the complex cancer treatments which target also spreading and growth- promoting factors of tumors by specific and highly efficient substances (Pavet et al., 2010). Presently the field of the Wnt-targeting drug research is almost solely dominated by assays based on transcriptional activation induced by the signaling. This approach resulted in development of a number of promising substances (Lee et al., 2011). Despite its effectiveness, the method nevertheless suffers from several drawbacks. Among the major ones is the fact that this approach is prone to identify compounds targeting rather downstream effectors of the pathway, which are indiscriminately used by all the subtypes of the Wnt signaling. Additionally, proteins which are involved in several signaling cascades and not just the Wnt pathway turn out as targets of the new compounds. These issues increase risks of side effects due to off-target interactions and blockade of the pathway in healthy cells. In the present work we put forward a novel biochemical approach for drug development on the Wnt pathway. It targets Frizzleds (Fzs) - a family of 7-transmbembrane proteins which serve as receptors for Wnt ligands. They offer unique properties for the development of highly specific and effective drugs as they control all branches of the Wnt signaling. Recent advances in the understanding of the roles of heterotrimeric G proteins downstream from Fzs (Katanaev et al., 2005; Liu et al., 2005; Jernigan et al., 2010) suggest application of enzymatic properties of these effectors to monitor the receptor-mediated events. We have applied this knowledge in practice and established a specific and efficient method based on utilization of a novel high-throughput format of the GTP-binding assay to follow the activation of Fzs. This type of assay is a robust and well-established technology for the research and screenings on the GPCRs (Harrison and Traynor, 2003). The conventional method of detection involves the radioactively labeled non-hydrolysable GTP analog [35S]GTPyS. Its application in the large-scale screenings is however problematic which promoted development of the novel non-radioactive GTP analog GTP-Eu. The new molecule employs phenomenon of the time-resolved fluorescence to provide sensitivity comparable to the conventional radioactive substance. Initially GTP-Eu was tested only in one of many possible types of GTP-binding assays (Frang et al., 2003). In the present work we expand these limits by demonstrating the general comparability of the novel label with the radioactive method in various types of assays. We provide a biochemical characterization of GTP-Eu interactions with heterotrimeric and small GTPases and a comparative analysis of the behavior of the new label in the assays involving heterotrimeric G protein effectors. These developments in the GTP-binding assay were then applied to monitor G protein activation by the Fz receptors. The data obtained in mammalian cultured cell lines provides for the first time an unambiguous biochemical proof for direct coupling of Fzs with G proteins. The specificity of this interaction has been confirmed by the experiments with the antagonists of Fz and by the pertussis toxin-mediated deactivation. Additionally we have identified the specificity of Wnt3a towards several members of the Fz family and analyzed the properties of human Fz-1 which was found to be the receptor coupled to the Gi/o family of G proteins. Another process playing significant role in the functioning of every GPCR is endocytosis. This phenomenon can also be employed for drug screenings on GPCRs (Bickle, 2010). In the present work we have demonstrated that Drosophila Fz receptors are involved in an unusual for many GPCRs manifestation of the receptor-mediated internalization. Through combination of biochemical approaches and studies on Drosophila as the model organism we have shown that direct interactions of the Fzs and the α-subunit of the heterotrimeric G protein Go with the small GTPase Rab5 regulate internalization of the receptor in early endosomes. We provide data uncovering the decisive role of this self-promoted endocytosis in formation of a proper signaling output in the canonical as well as planar cell polarity (PCP) pathways regulated by Fz. The results of this work thus establish a platform for the high-throughput screening to identify substances active in the cancer-related Wnt pathways. This methodology has been adjusted and applied to provide the important insights in Fz functioning and will be instrumental for further investigations on the Wnt-mediated pathways.

Characteristics and effectiveness of diabetes self-management educational programs targeted to racial/ethnic minority groups: a systematic review, meta-analysis and meta-regression.

BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.

Controlled contrast transcranial Doppler and arterial blood gas analysis to quantify shunt through patent foramen ovale.

BACKGROUND AND PURPOSE: A right-to-left shunt can be identified by contrast transcranial Doppler ultrasonography (c-TCD) at rest and/or after a Valsalva maneuver (VM) or by arterial blood gas (ABG) measurement. We assessed the influence of controlled strain pressures and durations during VM on the right-to-left passage of microbubbles, on which depends the shunt classification by c-TCD, and correlated it with the right-to-left shunt evaluation by ABG measurements in stroke patients with patent foramen ovale (PFO). METHODS: We evaluated 40 stroke patients with transesophageal echocardiography-documented PFO. The microbubbles were recorded with TCD at rest and after 4 different VM conditions with controlled duration and target strain pressures (duration in seconds and pressure in cm H2O, respectively): V5-20, V10-20, V5-40, and V10-40. The ABG analysis was performed after pure oxygen breathing in 34 patients, and the shunt was calculated as percentage of cardiac output. RESULTS: Among all VM conditions, V5-40 and V10-40 yielded the greatest median number of microbubbles (84 and 95, respectively; P<0.01). A significantly larger number of microbubbles were detected in V5-40 than in V5-20 (P<0.001) and in V10-40 than in V10-20 (P<0.01). ABG was not sensitive enough to detect a shunt in 31 patients. CONCLUSIONS: The increase of VM expiratory pressure magnifies the number of microbubbles irrespective of the strain duration. Because the right-to-left shunt classification in PFO is based on the number of microbubbles, a controlled VM pressure is advised for a reproducible shunt assessment. The ABG measurement is not sensitive enough for shunt assessment in stroke patients with PFO.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

Farm-Level Analysis of Risk Management Proposals, March 2000

This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.

Financing Constraints, Irreversibility, and Investment Dynamics

We develop a model of an industry with many heterogeneous firms that face both financing constraints and irreversibility constraints. The financing constraint implies that firms cannot borrow unless the debt is secured by collateral; the irreversibility constraint that they can only sell their fixed capital by selling their business. We use this model to examine the cyclical behavior of aggregate fixed investment, variable capital investment, and output in the presence of persistent idiosyncratic and aggregate shocks. Our model yields three main results. First, the effect of the irreversibility constraint on fixed capital investment is reinforced by the financing constraint. Second, the effect of the financing constraint on variable capital investment is reinforced by the irreversibility constraint. Finally, the interaction between the two constraints is key for explaining why input inventories and material deliveries of US manufacturing firms are so volatile and procyclical, and also why they are highly asymmetrical over the business cycle.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Notes for a new guide to Keynes (I): Wages, aggregate demand, and employment

I revisit the General Theory's discussion of the role of wages inemployment determination through the lens of the New Keynesianmodel. The analysis points to the key role played by the monetarypolicy rule in shaping the link between wages and employment, andin determining the welfare impact of enhanced wage flexibility. I showthat the latter is not always welfare improving.

Input chains and industrialization

A key aspect of industrialization is theadoption of increasing-returns-to-scale, industrial,technologies. Two other, well-documented aspects arethat industrial technologies are adopted throughoutintermediate-input chains and that they use intermediateinputs intensively relative to the technologies theyreplace. These features of industrial technologiescombined imply that countries with access to similartechnologies may have very different levels ofindustrialization and income, even if the degree ofincreasing returns to scale at the firm level is relativelysmall. Furthermore, a small improvement in theproductivity of industrial technologies can trigger full-scaleindustrialization and a large increase in income.