792 research outputs found

    Latent class models in financial data analysis

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    This paper deals with optimal international portfolio choice by developing a latent class approach based on the distinction between international and non-international investors. On the basis of micro data, we analyze the effects of many social, demographic, economic and financial characteristics on the probability to be an international investor. Traditional measures of equity home bias do not allow for the existence of international investment rationing operators. On the contrary, by resorting to latent class analysis it is possible to detect the unobservable distinction between international investors and investors who are precluded from operating into international financial markets and, therefore, to evaluate the role of these unobservable constraints on equity home bias

    Clypeogethes elongatus (Rosenhauer, 1856) in Sardinia (Coleoptera. Nitidulidae, Meligethinae)

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    Clypeogethes elongatus (Rosenhauer, 1856) is a pollen-beetle occurring in SW Mediterranean areas, from Southern Iberian Peninsula to most of the North Africa; in Italy, this uncommon species was thus far known only from the Island of Pantelleria (southern Sicily). Recent researches in S Sardinia allowed to find a small relic population of this species in Cagliari (San Michele hill), where it is cer-tainly associated with early-flowering Brassicaceae, on chalk-based rocks

    Structural investigation of Rett-inducing MeCP2 mutations

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    X-ray structure of methyl-CpG binding domain (MBD) of MeCP2, an intrinsically disordered protein (IDP) involved in Rett syndrome, offers a rational basis for defining the spatial distribution for most of the sites where mutations responsible of Rett syndrome, RTT, occur. We have ascribed pathogenicity for mutations of amino acids bearing positively charged side chains, all located at the protein-DNA interface, as positive charge removal cause reduction of the MeCP2-DNA adduct lifetime. Pathogenicity of the frequent proline replacements, outside the DNA contact moiety of MBD, can be attributed to the role of this amino acid for maintaining both unfolded states for unbound MeCP2 and, at the same time, to favor some higher conformational order for stabilizing structural determinants required by protein activity. These hypotheses can be extended to transcription repressor domain, TRD, the other MeCP2-DNA interaction site and, in general, to all the IDP that interact with nucleic acids

    Early onset of hypertension and serum electrolyte changes as potential predictive factors of activity in advanced hcc patients treated with sorafenib: results from a retrospective analysis of the HCC-AVR group

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    Hypertension (HTN) is frequently associated with the use of angiogenesis inhibitors targeting the vascular endothelial growth factor pathway and appears to be a generalized effect of this class of agent. We investigated the phenomenon in 61 patients with advanced hepatocellular carcinoma (HCC) receiving sorafenib. Blood pressure and plasma electrolytes were measured on days 1 and 15 of the treatment. Patients with sorafenib-induced HTN had a better outcome than those without HTN (disease control rate: 63.4% vs. 17.2% (p=0.001); progression-free survival 6.0 months (95% CI 3.2-10.1) vs. 2.5 months (95% CI 1.9-2.6) (p<0.001) and overall survival 14.6 months (95% CI9.7-19.0) vs. 3.9 months (95% CI 3.1-8.7) (p=0.003). Sodium levels were generally higher on day 15 than at baseline (+2.38, p<0.0001) in the group of responders (+4.95, p <0.0001) compared to patients who progressed (PD) (+0.28, p=0.607). In contrast, potassium was lower on day 14 (-0.30, p=0.0008) in the responder group (-0.58, p=0.003) than in those with progressive disease (-0.06, p=0.500). The early onset of hypertension is associated with improved clinical outcome in HCC patients treated with sorafenib. Our data are suggestive of an activation of the renin-angiotensin system in patients with advanced disease who developed HTN during sorafenib treatmen

    Increased Functional Connectivity in the Default Mode Network in Mild Cognitive Impairment: A Maladaptive Compensatory Mechanism Associated with Poor Semantic Memory Performance

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    Semantic memory decline and changes of default mode network (DMN) connectivity have been reported in mild cognitive impairment (MCI). Only a few studies, however, have investigated the role of changes of activity in the DMN on semantic memory in this clinical condition. The present study aimed to investigate more extensively the relationship between semantic memory impairment and DMN intrinsic connectivity in MCI. Twenty-one MCI patients and 21 healthy elderly controls matched for demographic variables took part in this study. All participants underwent a comprehensive semantic battery including tasks of category fluency, visual naming and naming from definition for objects, actions and famous people, word-association for early and late acquired words and reading. A subgroup of the original sample (16 MCI patients and 20 healthy elderly controls) was also scanned with resting state functional magnetic resonance imaging and DMN connectivity was estimated using a seed-based approach. Compared with healthy elderly, patients showed an extensive semantic memory decline in category fluency, visual naming, naming from definition, words-association, and reading tasks. Patients presented increased DMN connectivity between the medial prefrontal regions and the posterior cingulate and between the posterior cingulate and the parahippocampus and anterior hippocampus. MCI patients also showed a significant negative correlation of medial prefrontal gyrus connectivity with parahippocampus and posterior hippocampus and visual naming performance. Our findings suggest that increasing DMN connectivity may contribute to semantic memory deficits in MCI, specifically in visual naming. Increased DMN connectivity with posterior cingulate and medio-temporal regions seems to represent a maladaptive reorganization of brain functions in MCI, which detrimentally contributes to cognitive impairment in this clinical population

    Cluster Correlation in Mixed Models

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    We evaluate the dependence of the cluster correlation length r_c on the mean intercluster separation D_c, for three models with critical matter density, vanishing vacuum energy (Lambda = 0) and COBE normalized: a tilted CDM (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos yielding Omega_h = 0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of sigma_8 (and, henceforth, the observed cluster abundance) and are consistent with the observed abundance of Damped Lyman_alpha systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio sigma_8/sigma_25, yielding the spectral slope parameter Gamma, and nicely fit LCRS reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (side 360/h Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow to cover the same D_c interval inspected through APM and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit of cluster clustering data.Comment: 22 pages + 10 Postscript figures. Accepted for publication in Ap
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