When electronic management tools work - and don't work - in social-based distribution channels: A study of IT manufacturers and resellers: Working Paper Series--09-16

Electronic information tools have become increasingly popular with channel manufacturers in their efforts to manage resellers. Although these tools have been found to increase the efficiency of communications, researchers and practitioners alike have questioned their overall effectiveness. To investigate how unilaterally supplied electronic information affects ongoing social channel relationships we consider the use of such tools in information technology distribution channels. Using electronic communications theory and channel governance theory we hypothesize that the usefulness of the tools is a function of the type of information inherent in each tool (demand creation information or supply fulfillment information) and the particular communications characteristics of this information. We utilize structural equation modeling to test the conceptual model on a data set of 214 information technology resellers. Strong support is found for the model and theoretical and managerial insights are provided

Reasoning about System-Level Failure Behavior from Large Sets of Function-Based Simulations

This paper presents the use of data clustering methods applied to the analysis results of a design-stage, functional failure reasoning tool. A system simulation using qualitative descriptions of component behaviors and a functional reasoning tool are used to identify the functional impact of a large set of potential single and multiple fault scenarios. The impact of each scenario is collected as the set of categorical function health states for each component-level function in the system. This data represents the space of potential system states. The clustering and statistical tools presented in this paper are used to identify patterns in this system state space. These patterns reflect the underlying emergent failure behavior of the system. Specifically two data analysis tools are presented and compared. First, a modified k-means clustering algorithm is used with a distance metric of functional effect similarity. Second, a statistical approach known as Latent Class Analysis is used to find an underlying probability model of potential system failure states. These tools are used to reason about how the system responds to complex fault scenarios and assist in identifying potential design changes for fault mitigation. As computational power increases, the ability to reason with large sets of data becomes as critical as the analysis methods used to collect that data. The goal of this work is to provide complex system designers with a means of using early design simulation data to identify and mitigate potential emergent failure behavior.Keywords: Clustering, Complex System Design, Big Data, Emergent Behavior, Fault Reasonin

Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains’ climate gradient: Implications for climate change and restoration

Plant response to climate depends on a species’ adaptive potential. To address this, we used reciprocal gardens to detect genetic and environmental plasticity effects on phenotypic variation and combined with genetic analyses. Four reciprocal garden sites were planted with three regional ecotypes of Andropogon gerardii, a dominant Great Plains prairie grass, using dry, mesic, and wet ecotypes originating from western KS to Illinois that span 500–1,200 mm rainfall/year. We aimed to answer: (a) What is the relative role of genetic constraints and phenotypic plasticity in controlling phenotypes? (b) When planted in the homesite, is there a trait syndrome for each ecotype? (c) How are genotypes and phenotypes structured by climate? and (d) What are implications of these results for response to climate change and use of ecotypes for restoration? Surprisingly, we did not detect consistent local adaptation. Rather, we detected co-gradient variation primarily for most vegetative responses. All ecotypes were stunted in western KS. Eastward, the wet ecotype was increasingly robust relative to other ecotypes. In contrast, fitness showed evidence for local adaptation in wet and dry ecotypes with wet and mesic ecotypes producing little seed in western KS. Earlier flowering time in the dry ecotype suggests adaptation to end of season drought. Considering ecotype traits in homesite, the dry ecotype was characterized by reduced canopy area and diameter, short plants, and low vegetative biomass and putatively adapted to water limitation. The wet ecotype was robust, tall with high biomass, and wide leaves putatively adapted for the highly competitive, light-limited Eastern Great Plains. Ecotype differentiation was supported by random forest classification and PCA. We detected genetic differentiation and outlier genes associated with primarily precipitation. We identified candidate gene GA1 for which allele frequency associated with plant height. Sourcing of climate adapted ecotypes should be considered for restoration

Monocytes regulate the mechanism of T-cell death by inducing Fas-mediated apoptosis during bacterial infection.

Monocytes and T-cells are critical to the host response to acute bacterial infection but monocytes are primarily viewed as amplifying the inflammatory signal. The mechanisms of cell death regulating T-cell numbers at sites of infection are incompletely characterized. T-cell death in cultures of peripheral blood mononuclear cells (PBMC) showed 'classic' features of apoptosis following exposure to pneumococci. Conversely, purified CD3(+) T-cells cultured with pneumococci demonstrated necrosis with membrane permeabilization. The death of purified CD3(+) T-cells was not inhibited by necrostatin, but required the bacterial toxin pneumolysin. Apoptosis of CD3(+) T-cells in PBMC cultures required 'classical' CD14(+) monocytes, which enhanced T-cell activation. CD3(+) T-cell death was enhanced in HIV-seropositive individuals. Monocyte-mediated CD3(+) T-cell apoptotic death was Fas-dependent both in vitro and in vivo. In the early stages of the T-cell dependent host response to pneumococci reduced Fas ligand mediated T-cell apoptosis was associated with decreased bacterial clearance in the lung and increased bacteremia. In summary monocytes converted pathogen-associated necrosis into Fas-dependent apoptosis and regulated levels of activated T-cells at sites of acute bacterial infection. These changes were associated with enhanced bacterial clearance in the lung and reduced levels of invasive pneumococcal disease

Strategic plan for integrated care of patients with kidney failure

There is a huge gap between the number of patients worldwide requiring versus those actually receiving safe, sustainable, and equitable care for kidney failure. To address this, the International Society of Nephrology coordinated the development of a Strategic Plan for Integrated Care of Patients with Kidney Failure. Implementation of the plan will require engagement of the whole kidney community over the next 5-10 years

A cardinal role for cathepsin D in co-ordinating the host-mediated apoptosis of macrophages and killing of pneumococci

The bactericidal function of macrophages against pneumococci is enhanced by their apoptotic demise, which is controlled by the anti-apoptotic protein Mcl-1. Here, we show that lysosomal membrane permeabilization (LMP) and cytosolic translocation of activated cathepsin D occur prior to activation of a mitochondrial pathway of macrophage apoptosis. Pharmacological inhibition or knockout of cathepsin D during pneumococcal infection blocked macrophage apoptosis. As a result of cathepsin D activation, Mcl-1 interacted with its ubiquitin ligase Mule and expression declined. Inhibition of cathepsin D had no effect on early bacterial killing but inhibited the late phase of apoptosis-associated killing of pneumococci in vitro. Mice bearing a cathepsin D-/- hematopoietic system demonstrated reduced macrophage apoptosis in vivo, with decreased clearance of pneumococci and enhanced recruitment of neutrophils to control pulmonary infection. These findings establish an unexpected role for a cathepsin D-mediated lysosomal pathway of apoptosis in pulmonary host defense and underscore the importance of apoptosis-associated microbial killing to macrophage function

Capturing and monitoring global differences in untreated and treated end-stage kidney disease, kidney replacement therapy modality, and outcomes

A large gap between the number of people with end-stage kidney disease (ESKD) who received kidney replacement therapy (KRT) and those who needed it has been recently identified, and it is estimated that approximately one-half to three-quarters of all people with ESKD in the world may have died prematurely because they could not receive KRT. This estimate is aligned with a previous report that estimated that >3 million people in the world died each year because they could not access KRT. This review discusses the reasons for the differences in treated and untreated ESKD and KRT modalities and outcomes and presents strategies to close the global KRT gap by establishing robust health information systems to guide resource allocation to areas of need, inform KRT service planning, enable policy development, and monitor KRT health outcomes

The mouse Gene Expression Database (GXD): 2019 update.

The mouse Gene Expression Database (GXD) is an extensive, well-curated community resource freely available at www.informatics.jax.org/expression.shtml. Covering all developmental stages, GXD includes data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments in wild-type and mutant mice. GXD\u27s gene expression information is integrated with the other data in Mouse Genome Informatics and interconnected with other databases, placing these data in the larger biological and biomedical context. Since the last report, the ability of GXD to provide insights into the molecular mechanisms of development and disease has been greatly enhanced by the addition of new data and by the implementation of new web features. These include: improvements to the Differential Gene Expression Data Search, facilitating searches for genes that have been shown to be exclusively expressed in a specified structure and/or developmental stage; an enhanced anatomy browser that now provides access to expression data and phenotype data for a given anatomical structure; direct access to the wild-type gene expression data for the tissues affected in a specific mutant; and a comparison matrix that juxtaposes tissues where a gene is normally expressed against tissues, where mutations in that gene cause abnormalities

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos