Protective Role of Superoxide Dismutase against Diabetogenic Drugs

Copper-zinc superoxide dismutase (SOD) is present in relatively high concentrations in the β-cells of human islets. The activity of the extracted enzyme is partially inhibited upon incubation with the diabetogenic drugs alloxan, streptozotocin, or Vacor. The role of this enzyme in protecting β-cells against chemically induced diabetes was further investigated. Incubation of intact canine islets with alloxan (0.2 mg/ml) and 4 mM glucose decreased the insulin secretory response by 87% during subsequent exposure to 28 mM glucose. Concomitantly the SOD-specific activity (units of enzyme activity per milligram immunoreactive SOD) decreased 50% in alloxan-exposed islets. When islets were protected from alloxan toxicity by including 28 mM glucose with alloxan, the insulin secretory response and SOD specific activity remained identical to controls. Thus, SOD specific activity correlates with maintenance of β-cell function. To test the effectiveness of SOD against streptozotocin in vitro, canine islets were incubated 10 min with or without streptozotocin (0.1 mg/ml) with 4 mM glucose; their functional integrity was tested subsequently as the insulin secretory response to 28 mM glucose. Exposure to streptozotocin alone decreased the response by 70%; inclusion of SOD (1.5 mg/ml) before and during exposure to streptozotocin completely prevented this effect. Cyanide-inactivated SOD was not effective. The potential of SOD to prevent streptozotocin-induced diabetes was tested in rats in vivo. SOD injected 10 s or 50 min before streptozotocin prevented or significantly attenuated diabetes. Injection of SOD and streptozotocin simultaneously was much less effective, and cyanide-inactivated SOP was ineffective. No protection was afforded by injection of SOD 12 or 24 h before streptozotocin. Our results support hypotheses that (a) oxygen radicals mediate the β-cell toxicity of both alloxan and streptozotocin, and (b) β-cells may be particularly vulnerable to oxygen radical damage

Modulation of Rat Skeletal Muscle Branched-Chain α-Keto Acid Dehydrogenase In Vivo Effects of Dietary Protein and Meal Consumption

The effects of dietary protein on the activity of skeletal muscle branched-chain a-keto acid dehydrogenase (BCKAD) were investigated. BCKAD is rate-limiting for branched-chain amino acid (BCAA) catabolism by muscle; its activity is modulated by phosphorylation-dephosphorylation. In rats fed an adequate protein (25% casein) diet, BCKAD was - 2% active postabsorptively and increased to 10% or 16% active after a 25% or 50% protein meal, respectively. Prolonged feeding of a 50% protein diet increased postabsorptive BCKAD activity to 7% with further increases to 40% active postprandially. On a low protein (9% casein) diet BCKAD remained - 2% active regardless of meal-feeding. Dose-dependent activation of BCKAD by intravenous leucine in postabsorptive rats was blunted by a low protein diet. We conclude that excesses of dietary protein enhance the capacity of skeletal muscle to oxidize BCAA, muscle conserves BCAA when protein intake is inadequate, and skeletal muscle may play an important role in whole-body BCAA homeostasis

Administration of Endotoxin, Tumor Necrosis Factor, or Interleukin 1 to Rats Activates Skeletal Muscle Branched-Chain α-Keto Acid Dehydrogenase

Protein catabolic states (i.e., sepsis and trauma) are thought to be associated with accelerated oxidation of branched-chain amino acids (BCAA). Branched-chain α-keto acid dehydrogenase (BCKAD), the rate-limiting enzyme for BCAA oxidation by muscle, is regulated by phosphorylation/dephosphorylation. Skeletal muscle BCKAD was only 2-4% active in control rats. Intravenous injection of Salmonella enteritidis endotoxin (0.25-10 mg/kg) did not change total BCKAI) activity, but increased the percent active enzyme in muscle three- to four-fold in 4-6 h. Identical results were observed in adrenalectomized rats pretreated with one dose of α-methylprednisolone (2.5 mg/kg i.p.) 30-60 min before saline or endotoxin injection, indicating that endotoxin\u27s effect was not mediated by hypersecretion of adrenal hormones. Cortisone pretreatment of normal rats (100 mg/kg per d) for 2 d prevented endotoxin-induced activation of muscle BCKAD, suggesting that endogenous secretion products mediated BCKAD activation by endotoxin. Human recombinant tumor necrosis factor-α and/or IL-1β or α (50 μg/kg) increased muscle BCKAD activation two- to fourfold in normal rats 4-6 h after intravenous injection. We conclude that cytokine-mediated activation of muscle BCKAD may contribute to accelerated BCAA oxidation in septicemia

Go-6976 reverses hyperglycemia-induced insulin resistance independently of cPKC inhibition in adipocytes.

This paper was originally published in PLOS ONE (Robinson KA, Hegyi K, Hannun YA, Buse MG, Sethi JK, PLoS ONE 2014, 9(10): e108963. doi:10.1371/journal.pone.0108963).Chronic hyperglycemia induces insulin resistance by mechanisms that are incompletely understood. One model of hyperglycemia-induced insulin resistance involves chronic preincubation of adipocytes in the presence of high glucose and low insulin concentrations. We have previously shown that the mTOR complex 1 (mTORC1) plays a partial role in the development of insulin resistance in this model. Here, we demonstrate that treatment with Go-6976, a widely used "specific" inhibitor of cPKCs, alleviates hyperglycemia-induced insulin resistance. However, the effects of mTOR inhibitor, rapamycin and Go-6976 were not additive and only rapamycin restored impaired insulin-stimulated AKT activation. Although, PKCα, (but not -β) was abundantly expressed in these adipocytes, our studies indicate cPKCs do not play a major role in causing insulin-resistance in this model. There was no evidence of changes in the expression or phosphorylation of PKCα, and PKCα knock-down did not prevent the reduction of insulin-stimulated glucose transport. This was also consistent with lack of IRS-1 phosphorylation on Ser-24 in hyperglycemia-induced insulin-resistant adipocytes. Treatment with Go-6976 did inhibit a component of the mTORC1 pathway, as evidenced by decreased phosphorylation of S6 ribosomal protein. Raptor knock-down enhanced the effect of insulin on glucose transport in insulin resistant adipocytes. Go-6976 had the same effect in control cells, but was ineffective in cells with Raptor knock-down. Taken together these findings suggest that Go-6976 exerts its effect in alleviating hyperglycemia-induced insulin-resistance independently of cPKC inhibition and may target components of the mTORC1 signaling pathway.This work was supported by grants from the Biotechnology and Biological Sciences Research Council (David Phillips Fellowship, JF16994), Diabetes UK (BDA:RD06/0003237) and British Heart Foundation (PG/10/38/28359) to J.K. Sethi and also from National Institute of Diabetes and Digestive and Kidney Diseases (DK-02001) to M.G. Buse

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

European Multicentre Tics in Children Studies (EMTICS): protocol for two cohort studies to assess risk factors for tic onset and exacerbation in children and adolescents

Genetic predisposition, autoimmunity and environmental factors [e.g. pre- and perinatal difficulties, Group A Streptococcal (GAS) and other infections, stress-inducing events] might interact to create a neurobiological vulnerability to the development of tics and associated behaviours. However, the existing evidence for this relies primarily on small prospective or larger retrospective population-based studies, and is therefore still inconclusive. This article describes the design and methodology of the EMTICS study, a longitudinal observational European multicentre study involving 16 clinical centres, with the following objectives: (1) to investigate the association of environmental factors (GAS exposure and psychosocial stress, primarily) with the onset and course of tics and/or obsessive-compulsive symptoms through the prospective observation of at-risk individuals (ONSET cohort: 260 children aged 3-10 years who are tic-free at study entry and have a first-degree relative with a chronic tic disorder) and affected individuals (COURSE cohort: 715 youth aged 3-16 years with a tic disorder); (2) to characterise the immune response to microbial antigens and the host's immune response regulation in association with onset and exacerbations of tics; (3) to increase knowledge of the human gene pathways influencing the pathogenesis of tic disorders; and (4) to develop prediction models for the risk of onset and exacerbations of tic disorders. The EMTICS study is, to our knowledge, the largest prospective cohort assessment of the contribution of different genetic and environmental factors to the risk of developing tics in putatively predisposed individuals and to the risk of exacerbating tics in young individuals with chronic tic disorders

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages