726 research outputs found

    Permitting Service of Process by Mail on Japanese Defendants

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    The importance of financial market development on the relationship between loan guarantees for SMEs and local market employment rates

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    We empirically examine whether a major government intervention in the small-firm credit market yields significantly better results in markets that are less financially developed. The government intervention that we investigate is SBA-guaranteed lending. The literature on financing small and medium size enterprises (SMEs) suggests that small firms may be exposed to a particular type of market failure associated with credit rationing. And SMEs in markets that are less financially developed will likely face a greater degree of this market failure. To test our hypothesis, we use the level of bank deposits per capita as our relative measure of financial market development, and we use local market employment rates as our measure of economic performance. After controlling for the appropriate cross-sectional market characteristics, we find that SBA-guaranteed lending has a significantly more (less) positive impact on the average annual level of employment when the local market is relatively less (more) financially developed. This result has important implications for public policy directives concerning where SBA-guaranteed lending should be directed.Small Business Administration ; Financial markets ; Small business - Finance ; Employment

    Oxidation processes in magneto-optic and related materials

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    The surface oxidation processes of thin films of magneto-optic materials, such as the rare-earth transition metal alloys have been studied, starting in ultrahigh vacuum environments, using surface analysis techniques, as a way of modeling the oxidation processes which occur at the base of a defect in an overcoated material, at the instant of exposure to ambient environments. Materials examined have included FeTbCo alloys, as well as those same materials with low percentages of added elements, such a Ta, and their reactivities to both O2 and H2O compared with materials such as thin Fe films coated with ultrathin adlayers of Ti. The surface oxidation pathways for these materials is reviewed, and XPS data presented which indicates the type of oxides formed, and a critical region of Ta concentration which provides optimum protection

    Arginine side chain interactions and the role of arginine as a gating charge carrier in voltage sensitive ion channels

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    Gating charges in voltage-sensing domains (VSD) of voltage-sensitive ion channels and enzymes are carried on arginine side chains rather than lysine. This arginine preference may result from the unique hydration properties of the side chain guanidinium group which facilitates its movement through a hydrophobic plug that seals the center of the VSD, as suggested by molecular dynamics simulations. To test for side chain interactions implicit in this model we inspected interactions of the side chains of arginine and lysine with each of the 19 non-glycine amino acids in proteins in the protein data bank. The arginine guanidinium interacts with non-polar aromatic and aliphatic side chains above and below the guanidinium plane while hydrogen bonding with polar side chains is restricted to in-plane positions. In contrast, non-polar side chains interact largely with the aliphatic part of the lysine side chain. The hydration properties of arginine and lysine are strongly reflected in their respective interactions with non-polar and polar side chains as observed in protein structures and in molecular dynamics simulations, and likely underlie the preference for arginine as a mobile charge carrier in VSD

    Acute Hypersensitivity of Pluripotent Testicular Cancer-Derived Embryonal Carcinoma to Low-Dose 5-Aza Deoxycytidine Is Associated with Global DNA Damage-Associated p53 Activation, Anti-Pluripotency and DNA Demethylation

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    Human embryonal carcinoma (EC) cells are the stem cells of nonseminoma testicular germ cells tumors (TGCTs) and share remarkable similarities to human embryonic stem (ES) cells. In prior work we found that EC cells are hypersensitive to low nanomolar doses of 5-aza deoxycytidine (5-aza) and that this hypersensitivity partially depended on unusually high levels of the DNA methyltransferase, DNMT3B. We show here that low-dose 5-aza treatment results in DNA damage and induction of p53 in NT2/D1 cells. In addition, low-dose 5-aza results in global and gene specific promoter DNA hypomethylation. Low- dose 5-aza induces a p53 transcriptional signature distinct from that induced with cisplatin in NT2/D1 cells and also uniquely downregulates genes associated with pluripotency including NANOG, SOX2, GDF3 and Myc target genes. Changes in the p53 and pluripotency signatures with 5-aza were to a large extent dependent on high levels of DNMT3B. In contrast to the majority of p53 target genes upregulated by 5-aza that did not show DNA hypomethylation, several other genes induced with 5-aza had corresponding decreases in promoter methylation. These genes include RIN1, SOX15, GPER, and TLR4 and are novel candidate tumors suppressors in TGCTs. Our studies suggest that the hypersensitivity of NT2/D1 cells to low-dose 5-aza is multifactorial and involves the combined activation of p53 targets, repression of pluripotency genes, and activation of genes repressed by DNA methylation. Low-dose 5-aza therapy may be a general strategy to treat those tumors that are sustained by cells with embryonic stem-like properties. GEO number for the microarray data: GSE42647

    Applying the ROBINS-I tool to natural experiments: an example from public health

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    Background: A new tool to assess Risk of Bias In Non-randomised Studies of Interventions (ROBINS-I) was published in Autumn 2016. ROBINS-I uses the Cochrane-approved risk of bias (RoB) approach and focusses on internal validity. As such, ROBINS-I represents an important development for those conducting systematic reviews which include non-randomised studies (NRS), including public health researchers. We aimed to establish the applicability of ROBINS-I using a group of NRS which have evaluated non-clinical public health natural experiments. Methods: Five researchers, all experienced in critical appraisal of non-randomised studies, used ROBINS-I to independently assess risk of bias in five studies which had assessed the health impacts of a domestic energy efficiency intervention. ROBINS-I assessments for each study were entered into a database and checked for consensus across the group. Group discussions were used to identify reasons underpinning lack of consensus for specific questions and bias domains. Results: ROBINS-I helped to systematically articulate sources of bias in NRS. However, the lack of consensus in assessments for all seven bias domains raised questions about ROBINS-I’s reliability and applicability for natural experiment studies. The two RoB domains with least consensus were selection (Domain 2) and performance (Domain 4). Underlying the lack of consensus were difficulties in applying an intention to treat or per protocol effect of interest to the studies. This was linked to difficulties in determining whether the intervention status was classified retrospectively at follow-up, i.e. post hoc. The overall risk of bias ranged from moderate to critical; this was most closely linked to the assessment of confounders. Conclusion: The ROBINS-I tool is a conceptually rigorous tool which focusses on risk of bias due to the counterfactual. Difficulties in applying ROBINS-I may be due to poor design and reporting of evaluations of natural experiments. While the quality of reporting may improve in the future, improved guidance on applying ROBINS-I is needed to enable existing evidence from natural experiments to be assessed appropriately and consistently. We hope future refinements to ROBINS-I will address some of the issues raised here to allow wider use of the tool

    Pelagic Functional Group Modeling: Progress, Challenges and Prospects

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    In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochernical cycles in the ocean will respond to global warming. We define the term biogeochemical functional group to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, functional groups have no phylogenetic meaning-these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. One obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our tendency to model the organisms for which we have the most validation data (e.g., E huxleyi and Trichodesmium) even when they may represent only a fraction of the biogeochemical functional group we are trying to represent. When we step back and look at the paleo-oceanographic record, it suggests that oxygen concentrations have played a central role in the evolution and emergence of many of the key functional groups that influence biogeochemical cycles in the present-day ocean. However, more subtle effects are likely to be important over the next century like changes in silicate supply or turbulence that can influence the relative success of diatoms versus dinoflagellates, coccolithophorids and diazotrophs. In general, inferences drawn from the paleo-oceanographic record and theoretical work suggest that global warming will tend to favor the latter because it will give rise to increased stratification. However, decreases in pH and Fe supply could adversely impact coccolithophorids and diazotrophs in the future. It may be necessary to include explicit dynamic representations of nitrogen fixation, denitrification, silicification and calcification in our models if our goal is predicting the oceanic carbon cycle in the future, because these processes appear to play a very significant role in the carbon cycle of the present-day ocean and they are sensitive to climate change. Observations and models suggest that it may also be necessary to include the DMS cycle to predict future climate, though the effects are still highly uncertain. We have learned a tremendous amount about the distributions and biogeochemical impact of bacteria in the ocean in recent years, yet this improved understanding has not yet been incorporated into many of our models. All of these considerations lead us toward the development of increasingly complex models. However, recent quantitative model intercomparison studies suggest that continuing to add complexity and more functional groups to our ecosystem models may lead to decreases in predictive ability if the models are not properly constrained with available data. We also caution that capturing the present-day variability tells us little about how well a particular model can predict the future. If our goal is to develop models that can be used to predict how the oceans will respond to global warming, then we need to make more rigorous assessments of predictive skill using the available data

    A multidimensional view of racial differences in access to prostate cancer care

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139082/1/cncr30894.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139082/2/cncr30894_am.pd
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