The double-Kerr equilibrium configurations involving one extreme object

We demonstrate the existence of equilibrium states in the limiting cases of the double-Kerr solution when one of the constituents is an extreme object. In the `extreme-subextreme' case the negative mass of one of the constituents is required for the balance, whereas in the `extreme-superextreme' equilibrium configurations both Kerr particles may have positive masses. We also show that the well-known relation |J|=M^2 between the mass and angular momentum in the extreme single Kerr solution ceases to be a characteristic property of the extreme Kerr particle in a binary system.Comment: 12 pages, 3 figures, submitted to Class. Quantum Gra

A replication study confirms the association of TNFSF4 (OX40L) polymorphisms with systemic sclerosis in a large European cohort

<p><b>Objectives</b> The aim of this study was to confirm the influence of TNFSF4 polymorphisms on systemic sclerosis (SSc) susceptibility and phenotypic features.</p> <p><b>Methods</b> A total of 8 European populations of Caucasian ancestry were included, comprising 3014 patients with SSc and 3125 healthy controls. Four genetic variants of TNFSF4 gene promoter (rs1234314, rs844644, rs844648 and rs12039904) were selected as genetic markers.</p> <p><b>Results</b> A pooled analysis revealed the association of rs1234314 and rs12039904 polymorphisms with SSc (OR 1.15, 95% CI 1.02 to 1.31; OR 1.18, 95% CI 1.08 to 1.29, respectively). Significant association of the four tested variants with patients with limited cutaneous SSc (lcSSc) was revealed (rs1234314 OR 1.22, 95% CI 1.07 to 1.38; rs844644 OR 0.91, 95% CI 0.83 to 0.99; rs844648 OR 1.10, 95% CI 1.01 to 1.20 and rs12039904 OR 1.20, 95% CI 1.09 to 1.33). Association of rs1234314, rs844648 and rs12039904 minor alleles with patients positive for anti-centromere antibodies (ACA) remained significant (OR 1.23, 95% CI 1.10 to 1.37; OR 1.12, 95% CI 1.01 to 1.25; OR 1.22, 95% CI 1.07 to 1.38, respectively). Haplotype analysis confirmed a protective haplotype associated with SSc, lcSSc and ACA positive subgroups (OR 0.88, 95% CI 0.82 to 0.96; OR 0.88, 95% CI 0.80 to 0.96; OR 0.86, 95% CI 0.77 to 0.97, respectively) and revealed a new risk haplotype associated with the same groups of patients (OR 1.14, 95% CI 1.03 to 1.26; OR 1.20, 95% CI 1.08 to 1.35; OR 1.23, 95% CI 1.07 to 1.42, respectively).</p> <p><b>Conclusions</b> The data confirm the influence of TNFSF4 polymorphisms in SSc genetic susceptibility, especially in subsets of patients positive for lcSSc and ACA.</p&gt

A GBD 2019 study of health and Sustainable Development Goal gains and forecasts to 2030 in Spain

This study aimed to report mortality, risk factors, and burden of diseases in Spain. The Global Burden of Disease, Injuries, and Risk Factors 2019 estimates the burden due to 369 diseases, injuries, and impairments and 87 risk factors and risk factor combinations. Here, we detail the updated Spain 1990-2019 burden of disease estimates and project certain metrics up to 2030. In 2019, leading causes of death were ischaemic heart disease, stroke, chronic obstructive pulmonary disease, Alzheimer's disease, and lung cancer. Main causes of disability adjusted life years (DALYs) were ischaemic heart disease, diabetes, lung cancer, low back pain, and stroke. Leading DALYs risk factors included smoking, high body mass index, and high fasting plasma glucose. Spain scored 74/100 among all health-related Sustainable Development Goals (SDGs) indicators, ranking 20 of 195 countries and territories. We forecasted that by 2030, Spain would outpace Japan, the United States, and the European Union. Behavioural risk factors, such as smoking and poor diet, and environmental factors added a significant burden to the Spanish population's health in 2019. Monitoring these trends, particularly in light of COVID-19, is essential to prioritise interventions that will reduce the future burden of disease to meet population health and SDG commitments

Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. / Methods: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. / Findings: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). / Interpretation: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. / Funding: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Effectiveness and safety of first-generation protease inhibitors in clinical practice: Hepatitis C virus patients with advanced fibrosis

AIM: To evaluates the effectiveness and safety of the first generation, NS3/4A protease inhibitors (PIs) in clinical practice against chronic C virus, especially in patients with advanced fibrosis. METHODS: Prospective study and non-experimental analysis of a multicentre cohort of 38 Spanish hospitals that includes patients with chronic hepatitis C genotype 1, treatment-nai¨ve (TN) or treatment-experienced (TE), who underwent triple therapy with the first generation NS3/4A protease inhibitors, boceprevir (BOC) and telaprevir (TVR), in combination with pegylated interferon and ribavirin. The patients were treatment in routine practice settings. Data on the study population and on adverse clinical and virologic effects were compiled during the treatment period and during follow up. RESULTS: One thousand and fifty seven patients were included, 405 (38%) were treated with BOC and 652 (62%) with TVR. Of this total, 30% (n = 319) were TN and the remaining were TE: 28% (n = 298) relapsers, 12% (n = 123) partial responders (PR), 25% (n = 260) null-responders (NR) and for 5% (n = 57) with prior response unknown. The rate of sustained virologic response (SVR) by intention-to-treatment (ITT) was greater in those treated with TVR (65%) than in those treated with BOC (52%) (P < 0.0001), whereas by modified intention-to-treatment (mITT) no were found significant differences. By degree of fibrosis, 56% of patients were F4 and the highest SVR rates were recorded in the non-F4 patients, both TN and TE. In the analysis by groups, the TN patients treated with TVR by ITT showed a higher SVR (P = 0.005). However, by mITT there were no significant differences between BOC and TVR. In the multivariate analysis by mITT, the significant SVR factors were relapsers, IL28B CC and non-F4; the type of treatment (BOC or TVR) was not significant. The lowest SVR values were presented by the F4-NR patients, treated with BOC (46%) or with TVR (45%). 28% of the patients interrupted the treatment, mainly by non-viral response (51%): this outcome was more frequent in the TE than in the TN patients (57% vs 40%, P = 0.01). With respect to severe haematological disorders, neutropaenia was more likely to affect the patients treated with BOC (33% vs 20%, P = 0.0001), and thrombocytopaenia and anaemia, the F4 patients (P = 0.000, P = 0.025, respectively). CONCLUSION: In a real clinical practice setting with a high proportion of patients with advanced fibrosis, effectiveness of first-generation PIs was high except for NR patients, with similar SVR rates being achieved by BOC and TVR

Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study

Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer's disease and three causality networks : The GR@ACE project

Introduction: Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways. Methods: Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets. Results: We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444. Discussion: The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series

Identification of sixteen novel candidate genes for late onset Parkinson’s disease

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment