Inducible arginase 1 deficiency in mice leads to hyperargininemia and altered amino acid metabolism

Arginase deficiency is a rare autosomal recessive disorder resulting from a loss of the liver arginase isoform, arginase 1 (ARG1), which is the final step in the urea cycle for detoxifying ammonia. ARG1 deficiency leads to hyperargininemia, characterized by progressive neurological impairment, persistent growth retardation and infrequent episodes of hyperammonemia. Using the Cre/loxP-directed conditional gene knockout system, we generated an inducible Arg1-deficient mouse model by crossing "floxed" Arg1 mice with CreER(T2) mice. The resulting mice (Arg-Cre) die about two weeks after tamoxifen administration regardless of the starting age of inducing the knockout. These treated mice were nearly devoid of Arg1 mRNA, protein and liver arginase activity, and exhibited symptoms of hyperammonemia. Plasma amino acid analysis revealed pronounced hyperargininemia and significant alterations in amino acid and guanidino compound metabolism, including increased citrulline and guanidinoacetic acid. Despite no alteration in ornithine levels, concentrations of other amino acids such as proline and the branched-chain amino acids were reduced. In summary, we have generated and characterized an inducible Arg1-deficient mouse model exhibiting several pathologic manifestations of hyperargininemia. This model should prove useful for exploring potential treatment options of ARG1 deficiency

Liver-specific knockout of arginase-1 leads to a profound phenotype similar to inducible whole body arginase-1 deficiency

Arginase-1 (Arg1) converts arginine to urea and ornithine in the distal step of the urea cycle in liver. We previously generated a tamoxifen-inducible Arg1 deficient mouse model (Arg1-Cre) that disrupts Arg1 expression throughout the whole body and leads to lethality ≈ 2 weeks after gene disruption. Here, we evaluate if liver-selective Arg1 loss is sufficient to recapitulate the phenotype observed in global Arg1 knockout mice, as well as to gauge the effectiveness of gene delivery or hepatocyte transplantation to rescue the phenotype. Liver-selective Arg1 deletion was induced by using an adeno-associated viral (AAV)-thyroxine binding globulin (TBG) promoter-Cre recombinase vector administered to Arg1 "floxed" mice; Arg1(fl/fl) ). An AAV vector expressing an Arg1-enhanced green fluorescent protein (Arg1-eGFP) transgene was used for gene delivery, while intrasplenic injection of wild-type (WT) C57BL/6 hepatocytes after partial hepatectomy was used for cell delivery to "rescue" tamoxifen-treated Arg1-Cre mice. The results indicate that liver-selective loss of Arg1 (> 90% deficient) leads to a phenotype resembling the whole body knockout of Arg1 with lethality ≈ 3 weeks after Cre-induced gene disruption. Delivery of Arg1-eGFP AAV rescues more than half of Arg1 global knockout male mice (survival > 4 months) but a significant proportion still succumb to the enzyme deficiency even though liver expression and enzyme activity of the fusion protein reach levels observed in WT animals. Significant Arg1 enzyme activity from engrafted WT hepatocytes into knockout livers can be achieved but not sufficient for rescuing the lethal phenotype. This raises a conundrum relating to liver-specific expression of Arg1. On the one hand, loss of expression in this organ appears to be both necessary and sufficient to explain the lethal phenotype of the genetic disorder in mice. On the other hand, gene and cell-directed therapies suggest that rescue of extra-hepatic Arg1 expression may also be necessary for disease correction. Further studies are needed in order to illuminate the detailed mechanisms for pathogenesis of Arg1-deficiency

The Murine Angiotensin II-Induced Abdominal Aortic Aneurysm Model: Rupture Risk and Inflammatory Progression Patterns

An abdominal aortic aneurysm (AAA) is an enlargement of the greatest artery in the body defined as an increase in diameter of 1.5-fold. AAAs are common in the elderly population and thousands die each year from their complications. The most commonly used mouse model to study the pathogenesis of AAA is the angiotensin II (Ang II) infusion method delivered via osmotic mini-pump for 28 days. Here, we studied the site-specificity and onset of aortic rupture, characterized three-dimensional (3D) images and flow patterns in developing AAAs by ultrasound imaging, and examined macrophage infiltration in the Ang II model using 65 apolipoprotein E-deficient mice. Aortic rupture occurred in 16 mice (25%) and was nearly as prevalent at the aortic arch (44%) as it was in the suprarenal region (56%) and was most common within the first 7 days after Ang II infusion (12 of 16; 75%). Longitudinal ultrasound screening was found to correlate nicely with histological analysis and AAA volume renderings showed a significant relationship with AAA severity index. Aortic dissection preceded altered flow patterns and macrophage infiltration was a prominent characteristic of developing AAAs. Targeting the inflammatory component of AAA disease with novel therapeutics will hopefully lead to new strategies to attenuate aneurysm growth and aortic rupture

Proof-of-concept gene editing for the murine model of inducible arginase-1 deficiency

Arginase-1 deficiency in humans is a rare genetic disorder of metabolism resulting from a loss of arginase-1, leading to impaired ureagenesis, hyperargininemia and neurological deficits. Previously, we generated a tamoxifen-inducible arginase-1 deficient mouse model harboring a deletion of Arg1 exons 7 and 8 that leads to similar biochemical defects, along with a wasting phenotype and death within two weeks. Here, we report a strategy utilizing the Clustered, Regularly Interspaced, Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system in conjunction with piggyBac technology to target and reincorporate exons 7 and 8 at the specific Arg1 locus in attempts to restore the function of arginase-1 in induced pluripotent stem cell (iPSC)-derived hepatocyte-like cells (iHLCs) and macrophages in vitro. While successful gene targeted repair was achieved, minimal urea cycle function was observed in the targeted iHLCs compared to adult hepatocytes likely due to inadequate maturation of the cells. On the other hand, iPSC-derived macrophages expressed substantial amounts of "repaired" arginase. Our studies provide proof-of-concept for gene-editing at the Arg1 locus and highlight the challenges that lie ahead to restore sufficient liver-based urea cycle function in patients with urea cycle disorders

Strategies to rescue the consequences of inducible arginase-1 deficiency in mice

Arginase-1 catalyzes the conversion of arginine to ornithine and urea, which is the final step of the urea cycle used to remove excess ammonia from the body. Arginase-1 deficiency leads to hyperargininemia in mice and man with severe lethal consequences in the former and progressive neurological impairment to varying degrees in the latter. In a tamoxifen-induced arginase-1 deficient mouse model, mice succumb to the enzyme deficiency within 2 weeks after inducing the knockout and retain <2 % enzyme in the liver. Standard clinical care regimens for arginase-1 deficiency (low-protein diet, the nitrogen-scavenging drug sodium phenylbutyrate, ornithine supplementation) either failed to extend lifespan (ornithine) or only minimally prolonged lifespan (maximum 8 days with low-protein diet and drug). A conditional, tamoxifen-inducible arginase-1 transgenic mouse strain expressing the enzyme from the Rosa26 locus modestly extended lifespan of neonatal mice, but not that of 4-week old mice, when crossed to the inducible arginase-1 knockout mouse strain. Delivery of an arginase-1/enhanced green fluorescent fusion construct by adeno-associated viral delivery (rh10 serotype with a strong cytomegalovirus-chicken beta-actin hybrid promoter) rescued about 30% of male mice with lifespan prolongation to at least 6 months, extensive hepatic expression and restoration of significant enzyme activity in liver. In contrast, a vector of the AAV8 serotype driven by the thyroxine-binding globulin promoter led to weaker liver expression and did not rescue arginase-1 deficient mice to any great extent. Since the induced arginase-1 deficient mouse model displays a much more severe phenotype when compared to human arginase-1 deficiency, these studies reveal that it may be feasible with gene therapy strategies to correct the various manifestations of the disorder and they provide optimism for future clinical studies

Progress in Monte Carlo design and optimization of the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) will be an instrument covering a wide energy range in very-high-energy (VHE) gamma rays. CTA will include several types of telescopes, in order to optimize the performance over the whole energy range. Both large-scale Monte Carlo (MC) simulations of CTA super-sets (including many different possible CTA layouts as sub-sets) and smaller-scale simulations dedicated to individual aspects were carried out and are on-going. We summarize results of the prior round of large-scale simulations, show where the design has now evolved beyond the conservative assumptions of the prior round and present first results from the on-going new round of MC simulations.Comment: 4 pages, 5 figures. In Proceedings of the 33rd International Cosmic Ray Conference (ICRC2013), Rio de Janeiro (Brazil). All CTA contributions at arXiv:1307.223

Progress in Monte Carlo design and optimization of the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) will be an instrument covering a wide energy range in very-high-energy (VHE) gamma rays. CTA will include several types of telescopes, in order to optimize the performance over the whole energy range. Both large-scale Monte Carlo (MC) simulations of CTA super-sets (including many different possible CTA layouts as sub-sets) and smaller-scale simulations dedicated to individual aspects were carried out and are on-going. We summarize results of the prior round of large-scale simulations, show where the design has now evolved beyond the conservative assumptions of the prior round and present first results from the on-going new round of MC simulations.Fil: Bernlöhr, K.. Max-Planck-Institut fur Kernphysik; AlemaniaFil: Barnacka, A.. Polish Academy of Sciences; ArgentinaFil: Becherini, Y.. École Polytechnique; FranciaFil: Blanch Bigas, O.. IFAE; EspañaFil: Bouvier, A.. University of California; Estados UnidosFil: Carmona, E.. Max-Planck-Institut fur Physik; AlemaniaFil: Colin, P.. Max-Planck-Institut fur Physik; AlemaniaFil: Decerprit, G.. DESY; AlemaniaFil: di Pierro, F.. Osservatorio Astrofisico di Torino dell’Istituto Nazionale di Astrofisica; ItaliaFil: Dubois, F.. Universidad Complutense de Madrid; EspañaFil: Farnier, C.. Stockholm University; SueciaFil: Funk, S.. Kavli Institute for Particle Astrophysics and Cosmology; Estados UnidosFil: Hermann, G.. Max-Planck-Institut fur Kernphysik; AlemaniaFil: Hinton, J. A.. The University of Leicester; Reino UnidoFil: Humensky, T. B.. Columbia University; Estados UnidosFil: Jogler, T.. Kavli Institute for Particle Astrophysics and Cosmology; Estados UnidosFil: Khélifi, B.. École Polytechnique; FranciaFil: Kihm, T.. Max-Planck-Institut fur Kernphysik; AlemaniaFil: Komin, N.. Universite de Savoie; FranciaFil: Lenain, J. -P.. Université Denis Diderot Paris 7; FranciaFil: López Coto, R.. IFAE; EspañaFil: Maier, G.. DESY; AlemaniaFil: Mazin, D.. Max-Planck-Institut fur Physik; AlemaniaFil: Medina, Maria Clementina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Moralejo, A.. IFAE; EspañaFil: Moderski, R.. Polish Academy of Sciences; ArgentinaFil: Nolan, S. J.. Durham University; Reino UnidoFil: Ohm, S.. The University of Leicester; Reino UnidoFil: de Oña Wilhelmi, E.. Max-Planck-Institut fur Kernphysik; Alemania33rd International Cosmic Ray ConferenceRío de JaneiroBrasilBrazilian Physical Societ

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Background: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings: We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from &lt;5% of those younger than 20 years to &gt;66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from &lt;1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

Measurement of Energy Correlators inside Jets and Determination of the Strong Coupling Formula Presented

Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of $\sqrt{s}$=13 TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3 fb$^{−1}$. The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the Z boson mass: α$_S$ (m$_Z$)=0.1229 $\frac{0.0040}{-0.0050}$ , the most precise α$_S$m$_Z$ value obtained using jet substructure observable

Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at (s)=13\sqrt{(s)} = 13 TeV

The identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb$^{-1}$ of proton-proton collisions data at a centre-of-mass energy of √(s)=13 TeV collected in 2018 with the CMS experiment at the CERN LHC