Methods of Tail Dependence Estimation

Characterization and quantification of climate extremes and their dependencies are fundamental to the studying of natural hazards. This chapter reviews various parametric and nonparametric tail dependence coefficient estimators. The tail dependence coefficient describes the dependence (degree of association) between concurrent extremes at different locations. Accurate and reliable knowledge of the spatial characteristics of extremes can help improve the existing methods of modeling the occurrence probabilities of extreme events. This chapter will review these methods and use two case studies to demonstrate the application of tail dependence analysis

Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling

Genome-wide expression profiling of mouse and human leukocytes reveal conserved transcriptional programs of plasmacytoid or conventional dendritic cell subsets

Enter Mercury, Sleeping: Delivering Prayers on the Early Modern Stage

This is the author accepted manuscript. The final version is available from CUP via the DOI in this recor

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR‐related metrics based on 20+ different AR identification and tracking methods applied to Modern‐Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria‐based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all‐method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR‐related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR‐related research to consider.Fil: Rutz, Jonathan J.. National Ocean And Atmospheric Administration; Estados UnidosFil: Shields, Christine A.. National Center for Atmospheric Research; Estados UnidosFil: Lora, Juan M.. University of Yale; Estados UnidosFil: Payne, Ashley E.. University of Michigan; Estados UnidosFil: Guan, Bin. California Institute of Technology; Estados UnidosFil: Ullrich, Paul. University of California at Davis; Estados UnidosFil: O'Brien, Travis. Lawrence Berkeley National Laboratory; Estados UnidosFil: Leung, Ruby. Pacific Northwest National Laboratory; Estados UnidosFil: Ralph, F. Martin. Center For Western Weather And Water Extremes; Estados UnidosFil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados UnidosFil: Brands, Swen. Meteogalicia; EspañaFil: Collow, Allison. Universities Space Research Association; Estados UnidosFil: Goldenson, Naomi. University of California at Los Angeles; Estados UnidosFil: Gorodetskaya, Irina. Universidade de Aveiro; PortugalFil: Griffith, Helen. University of Reading; Reino UnidoFil: Kashinath, Karthik. Lawrence Bekeley National Laboratory; Estados UnidosFil: Kawzenuk, Brian. Center For Western Weather And Water Extremes; Reino UnidoFil: Krishnan, Harinarayan. Lawrence Berkeley National Laboratory; Estados UnidosFil: Kurlin, Vitaliy. University of Liverpool; Reino UnidoFil: Lavers, David. European Centre For Medium-range Weather Forecasts; Estados UnidosFil: Magnusdottir, Gudrun. University of California at Irvine; Estados UnidosFil: Mahoney, Kelly. Universidad de Lisboa; PortugalFil: Mc Clenny, Elizabeth. University of California at Davis; Estados UnidosFil: Muszynski, Grzegorz. University of Liverpool; Reino Unido. Lawrence Bekeley National Laboratory; Estados UnidosFil: Nguyen, Phu Dinh. University of California at Irvine; Estados UnidosFil: Prabhat, Mr.. Lawrence Bekeley National Laboratory; Estados UnidosFil: Qian, Yun. Pacific Northwest National Laboratory; Estados UnidosFil: Ramos, Alexandre M.. Universidade Nova de Lisboa; PortugalFil: Sarangi, Chandan. Pacific Northwest National Laboratory; Estados UnidosFil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin

Mutations in INPP5K Cause a Form of Congenital Muscular Dystrophy Overlapping Marinesco-Sjögren Syndrome and Dystroglycanopathy.

Congenital muscular dystrophies display a wide phenotypic and genetic heterogeneity. The combination of clinical, biochemical, and molecular genetic findings must be considered to obtain the precise diagnosis and provide appropriate genetic counselling. Here we report five individuals from four families presenting with variable clinical features including muscular dystrophy with a reduction in dystroglycan glycosylation, short stature, intellectual disability, and cataracts, overlapping both the dystroglycanopathies and Marinesco-Sjögren syndrome. Whole-exome sequencing revealed homozygous missense and compound heterozygous mutations in INPP5K in the affected members of each family. INPP5K encodes the inositol polyphosphate-5-phosphatase K, also known as SKIP (skeletal muscle and kidney enriched inositol phosphatase), which is highly expressed in the brain and muscle. INPP5K localizes to both the endoplasmic reticulum and to actin ruffles in the cytoplasm. It has been shown to regulate myoblast differentiation and has also been implicated in protein processing through its interaction with the ER chaperone HSPA5/BiP. We show that morpholino-mediated inpp5k loss of function in the zebrafish results in shortened body axis, microphthalmia with disorganized lens, microcephaly, reduced touch-evoked motility, and highly disorganized myofibers. Altogether these data demonstrate that mutations in INPP5K cause a congenital muscular dystrophy syndrome with short stature, cataracts, and intellectual disability

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council