26 resultados para Factor Models


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This article combines the research strands of moral politics and political behavior by focusing on the effect of individual and contextual religiosity on individual vote decisions in popular initiatives and public referenda concerning morally charged issues. We rely on a total of 13 surveys with 1,000 respondents each conducted after every referendum on moral policies in Switzerland between 1992 and 2012. Results based on cross-classified multilevel models show that religious behaving instead of nominal religious belonging plays a crucial role in decision making on moral issues. This supports the idea that the traditional confessional cleavage is replaced by a new religious cleavage that divides the religious from the secular. This newer cleavage is characterized by party alignments that extend from electoral to direct democratic voting behavior. Overall, our study lends support to previous findings drawn from American research on moral politics, direct democracies, and the public role of religion.

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Close similarities of various physiological parameters makes the pig one of the preferred animal models for the study of human diseases, especially those involving the cardiovascular system. Unfortunately, the use of pig models to study diseases such as viral hemorrhagic fevers and endotoxic shock syndrome have been hampered by the lack of the necessary immunological tools to measure important immunoregulatory cytokines such as tumor necrosis factor (TNF). Here we describe a TNF-bioassay which is based on the porcine kidney cell line PK(15). Compared to the widely used murine fibroblastoid cell line L929, the PK(15) cell line displays a 100-1000-fold higher sensitivity for porcine TNF-alpha, a higher sensitivity for human TNF-alpha, and a slightly lower sensitivity for murine TNF-alpha. Using a PK(15) bioassay we can detect recombinant TNF-alpha as well as cytotoxic activity in the supernatants of lipopolysaccharide (LPS)-activated porcine monocytes at high dilutions. This suggests that the sensitivity of the test should permit the detection of TNF in biological specimens such as pig serum.

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The most influential theoretical account in time psychophysics assumes the existence of a unitary internal clock based on neural counting. The distinct timing hypothesis, on the other hand, suggests an automatic timing mechanism for processing of durations in the sub-second range and a cognitively controlled timing mechanism for processing of durations in the range of seconds. Although several psychophysical approaches can be applied for identifying the internal structure of interval timing in the second and sub-second range, the existing data provide a puzzling picture of rather inconsistent results. In the present chapter, we introduce confirmatory factor analysis (CFA) to further elucidate the internal structure of interval timing performance in the sub-second and second range. More specifically, we investigated whether CFA would rather support the notion of a unitary timing mechanism or of distinct timing mechanisms underlying interval timing in the sub-second and second range, respectively. The assumption of two distinct timing mechanisms which are completely independent of each other was not supported by our data. The model assuming a unitary timing mechanism underlying interval timing in both the sub-second and second range fitted the empirical data much better. Eventually, we also tested a third model assuming two distinct, but functionally related mechanisms. The correlation between the two latent variables representing the hypothesized timing mechanisms was rather high and comparison of fit indices indicated that the assumption of two associated timing mechanisms described the observed data better than only one latent variable. Models are discussed in the light of the existing psychophysical and neurophysiological data.

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We present the crystal structures of the SEC14-like domain of supernatant protein factor (SPF) in complex with squalene and 2,3-oxidosqualene. The structures were resolved at 1.75 Å (complex with squalene) and 1.6 Å resolution (complex with 2,3-oxidosqualene), leading in both cases to clear images of the protein/ substrate interactions. Ligand binding is facilitated by removal of the Golgi-dynamics (GOLD) C-terminal domain of SPF, which, as shown in previous structures of the apo-protein, blocked the opening of the binding pocket to the exterior. Both substrates bind into a large hydrophobic cavity, typical of such lipid-transporter family. Our structures report no specific recognition mode for the epoxide group. In fact, for both molecules, ligand affinity is dominated by hydrophobic interactions, and independent investigations by computational models or differential scanning micro-calorimetry reveal similar binding affinities for both ligands. Our findings elucidate the molecular bases of the role of SPF in sterol endo-synthesis, supporting the original hypothesis that SPF is a facilitator of substrate flow within the sterol synthetic pathway. Moreover, our results suggest that the GOLD domain acts as a regulator, as its conformational displacement must occur to favor ligand binding and release during the different synthetic steps.

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A synthetic peptide (sPIF) analogous to the mammalian embryo-derived PreImplantation Factor (PIF) enables neuroprotection in rodent models of experimental autoimmune encephalomyelitis and perinatal brain injury. The protective effects have been attributed, in part, to sPIF's ability to inhibit the biogenesis of microRNA let-7, which is released from injured cells during central nervous system (CNS) damage and induces neuronal death. Here, we uncover another novel mechanism of sPIF-mediated neuroprotection. Using a clinically relevant rat newborn brain injury model, we demonstrate that sPIF, when subcutaneously administrated, is able to reduce cell death, reverse neuronal loss and restore proper cortical architecture. We show, both in vivo and in vitro, that sPIF activates cyclic AMP dependent protein kinase (PKA) and calcium-dependent protein kinase (PKC) signaling, leading to increased phosphorylation of major neuroprotective substrates GAP-43, BAD and CREB. Phosphorylated CREB in turn facilitates expression of Gap43, Bdnf and Bcl2 known to have important roles in regulating neuronal growth, survival and remodeling. As is the case in sPIF-mediated let-7 repression, we provide evidence that sPIF-mediated PKA/PKC activation is dependent on TLR4 expression. Thus, we propose that sPIF imparts neuroprotection via multiple mechanisms at multiple levels downstream of TLR4. Given the recent FDA fast-track approval of sPIF for clinical trials, its potential clinical application for treating other CNS diseases can be envisioned.

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Deregulated expression of the MET receptor tyrosine kinase has been reported in up to 50% of patients with hepatocellular carcinoma, the most abundant form of liver cancers, and is associated with decreased survival. Consequently, MET is considered as a molecular target in this malignancy, whose progression is highly dependent on extensive angiogenesis. Here we studied the impact of MET small molecule inhibitors on angiogenesis-associated parameters and growth of xenograft liver models consisting of cells expressing MET-mutated variants M1268T and Y1248H, which exhibit constitutive kinase activity. We demonstrate that MET mutations expression is associated with significantly increased production of vascular endothelial growth factor, which is blocked by MET targeting only in cells expressing the M1268T inhibitor-sensitive but not in the Y1248H inhibitor-resistant variant. Decrease in vascular endothelial growth factor production is also associated with reduction of tyrosine phopshorylation of the vascular endothelial growth factor receptor 2 expressed on primary liver sinusoidal endothelial cells and with inhibition of vessel formation. Furthermore, MET inhibition demonstrated an efficient anti-tumor activity and considerable reduction in microvessel density only against the M1268T-derived intrahepatic tumors. Collectively, our data support the role of targeting MET-associated angiogenesis as a major biological determinant for liver tumor growth control.

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Embryonic-maternal interaction from the earliest stages of gestation has a key, sustained role in neurologic development, persisting into adulthood. Early adverse events may be detrimental in adulthood. Protective factors present during gestation could significantly impact post-natal therapy. The role of PreImplantation Factor (PIF) within this context is herein examined. Secreted by viable early embryos, PIF establishes effective embryonic-maternal communication and exerts essential trophic and protective roles by reducing oxidative stress and protein misfolding and by blunting the nocive let-7 microRNA related pathway. PIF's effects on systemic immunity lead to comprehensive immune modulation, not immune suppression. We examine PIF's role in protecting embryos from adverse maternal environment, which can lead to neurological disorders that may only manifest post-nataly: Synthetic PIF successfully translates endogenous PIF features in both pregnant and non-pregnant clinically relevant models. Specifically PIF has neuroprotective effects in neonatal prematurity. In adult relapsing-remitting neuroinflammation, PIF reverses advanced paralysis while promoting neurogenesis. PIF reversed Mycobacterium smegmatis induced brain infection. In graft-vs.-host disease, PIF reduced skin ulceration, liver inflammation and colon ulceration while maintaining beneficial anti-cancer, graft-vs.-leukemia effect. Clinical-grade PIF has high-safety profile even at supraphysiological doses. The FDA awarded Fast-Track designation, and university-sponsored clinical trials for autoimmune disorder are ongoing. Altogether, PIF properties point to its determining regulatory role in immunity, inflammation and transplant acceptance. Specific plans for using PIF for the treatment of complex neurological disorders (ie. traumatic brain injury, progressive paralysis), including neuroprotection from newborn to adult, are presented.

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Aldosterone is an important factor supporting placental growth and fetal development. Recently, expression of placental growth factor (PlGF) has been observed in response to aldosterone exposure in different models of atherosclerosis. Thus, we hypothesized that aldosterone up-regulates growth-adaptive angiogenesis in pregnancy, via increased placental PlGF expression. We followed normotensive pregnant women (n = 24) throughout pregnancy and confirmed these results in a second independent first trimester cohort (n = 36). Urinary tetrahydroaldosterone was measured by gas chromatography-mass spectrometry and corrected for creatinine. Circulating PlGF concentrations were determined by ELISA. Additionally, cultured cell lines, adrenocortical H295R and choriocarcinoma BeWo cells, as well as primary human third trimester trophoblasts were tested in vitro. PlGF serum concentrations positively correlated with urinary tetrahydroaldosterone corrected for creatinine in these two independent cohorts. This observation was not due to PlGF, which did not induce aldosterone production in cultured H295R cells. On the other hand, PlGF expression was specifically enhanced by aldosterone in the presence of forskolin (p < 0.01) in trophoblasts. A pronounced stimulation of PlGF expression was observed with reduced glucose concentrations simulating starvation (p < 0.001). In conclusion, aldosterone stimulates placental PlGF production, enhancing its availability during human pregnancy, a response amplified by reduced glucose supply. Given the crucial role of PlGF in maintaining a healthy pregnancy, these data support a key role of aldosterone for a healthy pregnancy outcome.

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We present recent improvements of the modeling of the disruption of strength dominated bodies using the Smooth Particle Hydrodynamics (SPH) technique. The improvements include an updated strength model and a friction model, which are successfully tested by a comparison with laboratory experiments. In the modeling of catastrophic disruptions of asteroids, a comparison between old and new strength models shows no significant deviation in the case of targets which are initially non-porous, fully intact and have a homogeneous structure (such as the targets used in the study by Benz and Asphaug, 1999). However, for many cases (e.g. initially partly or fully damaged targets and rubble-pile structures) we find that it is crucial that friction is taken into account and the material has a pressure dependent shear strength. Our investigations of the catastrophic disruption threshold (27, as a function of target properties and target sizes up to a few 100 km show that a fully damaged target modeled without friction has a Q(D)*:, which is significantly (5-10 times) smaller than in the case where friction is included. When the effect of the energy dissipation due to compaction (pore crushing) is taken into account as well, the targets become even stronger (Q(D)*; is increased by a factor of 2-3). On the other hand, cohesion is found to have an negligible effect at large scales and is only important at scales less than or similar to 1 km. Our results show the relative effects of strength, friction and porosity on the outcome of collisions among small (less than or similar to 1000 km) bodies. These results will be used in a future study to improve existing scaling laws for the outcome of collisions (e.g. Leinhardt and Stewart, 2012). (C) 2014 Elsevier Ltd. All rights reserved.

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We propose a way to incorporate NTBs for the four workhorse models of the modern trade literature in computable general equilibrium models (CGEs). CGE models feature intermediate linkages and thus allow us to study global value chains (GVCs). We show that the Ethier-Krugman monopolistic competition model, the Melitz firm heterogeneity model and the Eaton and Kortum model can be defined as an Armington model with generalized marginal costs, generalized trade costs and a demand externality. As already known in the literature in both the Ethier-Krugman model and the Melitz model generalized marginal costs are a function of the amount of factor input bundles. In the Melitz model generalized marginal costs are also a function of the price of the factor input bundles. Lower factor prices raise the number of firms that can enter the market profitably (extensive margin), reducing generalized marginal costs of a representative firm. For the same reason the Melitz model features a demand externality: in a larger market more firms can enter. We implement the different models in a CGE setting with multiple sectors, intermediate linkages, non-homothetic preferences and detailed data on trade costs. We find the largest welfare effects from trade cost reductions in the Melitz model. We also employ the Melitz model to mimic changes in Non tariff Barriers (NTBs) with a fixed cost-character by analysing the effect of changes in fixed trade costs. While we work here with a model calibrated to the GTAP database, the methods developed can also be applied to CGE models based on the WIOD database.

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We performed a quantitative comparison of brittle thrust wedge experiments to evaluate the variability among analogue models and to appraise the reproducibility and limits of model interpretation. Fifteen analogue modeling laboratories participated in this benchmark initiative. Each laboratory received a shipment of the same type of quartz and corundum sand and all laboratories adhered to a stringent model building protocol and used the same type of foil to cover base and sidewalls of the sandbox. Sieve structure, sifting height, filling rate, and details on off-scraping of excess sand followed prescribed procedures. Our analogue benchmark shows that even for simple plane-strain experiments with prescribed stringent model construction techniques, quantitative model results show variability, most notably for surface slope, thrust spacing and number of forward and backthrusts. One of the sources of the variability in model results is related to slight variations in how sand is deposited in the sandbox. Small changes in sifting height, sifting rate, and scraping will result in slightly heterogeneous material bulk densities, which will affect the mechanical properties of the sand, and will result in lateral and vertical differences in peak and boundary friction angles, as well as cohesion values once the model is constructed. Initial variations in basal friction are inferred to play the most important role in causing model variability. Our comparison shows that the human factor plays a decisive role, and even when one modeler repeats the same experiment, quantitative model results still show variability. Our observations highlight the limits of up-scaling quantitative analogue model results to nature or for making comparisons with numerical models. The frictional behavior of sand is highly sensitive to small variations in material state or experimental set-up, and hence, it will remain difficult to scale quantitative results such as number of thrusts, thrust spacing, and pop-up width from model to nature.