Interdependence, interaction, and relationships

Interdependence theory presents a logical analysis of the structure of interpersonal situations, offering a conceptual framework in which interdependence situations can be analyzed in terms of six dimensions. Specific situations present specific problems and opportunities, logically implying the relevance of specific motives and permitting their expression. Via the concept of transformation, the theory explains how interaction is shaped by broader considerations such as long-term goals and concern for a partner's welfare. The theory illuminates our understanding of social-cognitive processes that are of longstanding interest to psychologists such as cognition and affect, attribution, and self-presentation. The theory also explains adaptation to repeatedly encountered interdependence patterns, as well as the embodiment of such adaptations in interpersonal dispositions, relationship-specific motives, and social norms

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Diverse system stresses: common mechanisms of chromosome fragmentation

Chromosome fragmentation (C-Frag) is a newly identified MCD (mitotic cell death), distinct from apoptosis and MC (mitotic catastrophe). As different molecular mechanisms can induce C-Frag, we hypothesize that the general mechanism of its induction is a system response to cellular stress. A clear link between C-Frag and diverse system stresses generated from an array of molecular mechanisms is shown. Centrosome amplification, which is also linked to diverse mechanisms of stress, is shown to occur in association with C-Frag. This led to a new model showing that diverse stresses induce common, MCD. Specifically, different cellular stresses target the integral chromosomal machinery, leading to system instability and triggering of MCD by C-Frag. This model of stress-induced cell death is also applicable to other types of cell death. The current study solves the previously confusing relationship between the diverse molecular mechanisms of chromosome pulverization, suggesting that incomplete C-Frag could serve as the initial event responsible for forms of genome chaos including chromothripsis. In addition, multiple cell death types are shown to coexist with C-Frag and it is more dominant than apoptosis at lower drug concentrations. Together, this study suggests that cell death is a diverse group of highly heterogeneous events that are linked to stress-induced system instability and evolutionary potential

Disruption of reducing pathways is not essential for efficient disulfide bond formation in the cytoplasm of E. coli

<p>Abstract</p> <p>Background</p> <p>The formation of native disulfide bonds is a complex and essential post-translational modification for many proteins. The large scale production of these proteins can be difficult and depends on targeting the protein to a compartment in which disulfide bond formation naturally occurs, usually the endoplasmic reticulum of eukaryotes or the periplasm of prokaryotes. It is currently thought to be impossible to produce large amounts of disulfide bond containing protein in the cytoplasm of wild-type bacteria such as <it>E. coli </it>due to the presence of multiple pathways for their reduction.</p> <p>Results</p> <p>Here we show that the introduction of Erv1p, a sulfhydryl oxidase and FAD-dependent catalyst of disulfide bond formation found in the inter membrane space of mitochondria, allows the efficient formation of native disulfide bonds in heterologously expressed proteins in the cytoplasm of <it>E. coli </it>even without the disruption of genes involved in disulfide bond reduction, for example <it>trxB </it>and/or <it>gor</it>. Indeed yields of active disulfide bonded proteins were higher in BL21 (DE3) pLysSRARE, an <it>E. coli </it>strain with the reducing pathways intact, than in the commercial Δ<it>gor </it>Δ<it>trxB </it>strain rosetta-gami upon co-expression of Erv1p.</p> <p>Conclusions</p> <p>Our results refute the current paradigm in the field that disruption of at least one of the reducing pathways is essential for the efficient production of disulfide bond containing proteins in the cytoplasm of <it>E. coli </it>and open up new possibilities for the use of <it>E. coli </it>as a microbial cell factory.</p

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Synthesis of tenascin and laminin beta2 chain in human bronchial epithelial cells is enhanced by cysteinyl leukotrienes via CysLT1 receptor

<p>Abstract</p> <p>Background</p> <p>Cysteinyl leukotrienes (CysLTs) are key mediators of asthma, but their role in the genesis of airway remodeling is insufficiently understood. Recent evidence suggests that increased expression of tenascin (Tn) and laminin (Ln) β2 chain is indicative of the remodeling activity in asthma, but represents also an example of deposition of extracellular matrix, which affects the airway wall compliance. We tested the hypothesis that CysLTs affect production of Tn and Ln β2 chain by human bronchial epithelial cells and elucidated, which of the CysLT receptors, CysLT₁or CysLT₂, mediate this effect.</p> <p>Methods</p> <p>Cultured BEAS-2B human bronchial epithelial cells were stimulated with leukotriene D₄(LTD₄) and E₄(LTE₄) and evaluated by immunocytochemistry, Western blotting, flow cytometry, and RT-PCR. CysLT receptors were differentially blocked with use of montelukast or BAY u9773.</p> <p>Results</p> <p>LTD₄and LTE₄significantly augmented the expression of Tn, whereas LTD₄, distinctly from LTE₄, was able to increase also the Ln β2 chain. Although the expression of CysLT₂prevailed over that of CysLT₁, the up-regulation of Tn and Ln β2 chain by CysLTs was completely blocked by the CysLT₁-selective antagonist montelukast with no difference between montelukast and the dual antagonist BAY u9773 for the inhibitory capacity.</p> <p>Conclusion</p> <p>These findings suggest that the CysLT-induced up-regulation of Tn and Ln β2 chain, an important epithelium-linked aspect of airway remodeling, is mediated predominantly by the CysLT₁receptor. The results provide a novel aspect to support the use of CysLT₁receptor antagonists in the anti-remodeling treatment of asthma.</p