Borderline Q-waves in individuals without overt cardiovascular disease: relations with adiposity, subclinical atherosclerosis and vascular stiffness

Background: Characteristics and risk factors associated with electrocardiographic borderline Q-waves are not fully elucidated, especially in individuals without overt cardiovascular disease (CVD). Also, the relation of isolated and non-isolated borderline Q-waves with subclinical atherosclerosis and vascular stiffness is unknown. Methods and results: We included 5746 Netherlands Epidemiology of Obesity study participants without overt CVD. Participants were divided in three groups: no Q-waves (93.7%), isolated (4.6%) and non-isolated borderline Q-waves (1.7%). Borderline Q-waves were defined as Minnesota Codes 1.2.x and 1.3.x and non-isolated as ≥1 of abnormal QRS axis, left ventricular hypertrophy or ST/T abnormalities. Several characteristics and measures of body fat were assessed. Vascular stiffness was assessed by pulse wave velocity (PWV) and subclinical atherosclerosis by carotid intima-media thickness (cIMT). Percentage of men, alcohol intake, blood pressure and fasting glucose concentrations were, compared with no Q-waves, higher in the isolated and highest in the non-isolated borderline Q-wave group. Isolated borderline Q-waves were associated with higher body mass index (difference compared with no Q-waves: 1.0 kg/m2; 95%CI: 0.3–1.7; p-value: 0.006), waist circumference (3.4 cm; 1.0–5.8; 0.005), and visceral adipose tissue (21.9 cm2; 7.4–36.3; 0.003) and differences were even larger for non-isolated borderline Q-waves. Compared with no Q-waves, non-isolated borderline Q-waves were associated with higher PWV (1.2 m/s; 0.4–2.0; 0.004) and cIMT (23.4 μm; 3.0–43.8; 0.024), whereas isolated borderline Q-waves were not. Conclusion: Cardiovascular risk factors and measures of body fat, especially abdominal adiposity, were higher in participants with isolated borderline Q-waves, compared with no Q-waves, and highest in the non-isolated borderline Q-wave group. Non-isolated borderline Q-waves were associated with subclinical atherosclerosis and vascular stiffness. Future studies should investigate potential added value of borderline Q-waves in CVD prediction

Hydrology and Meteorology of the Central Alaskan Arctic: Data Collection and Analysis

The availability of environmental data for unpopulated areas of Alaska can best be described as sparse; however, these areas have resource development potential. The central Alaskan Arctic region north of the Brooks Range (referred to as the North Slope) is no exception in terms of both environmental data and resource potential. This area was the focus of considerable oil/gas exploration immediately following World War II. Unfortunately, very little environmental data were collected in parallel with the exploration. Soon after the oil discovery at Prudhoe Bay in November 1968, the U.S. Geological Survey (USGS) started collecting discharge data at three sites in the neighborhood of Prudhoe Bay and one small watershed near Barrow. However, little complementary meteorological data (like precipitation) were collected to support the streamflow observations. In 1985, through a series of funded research projects, researchers at the University of Alaska Fairbanks (UAF), Water and Environmental Research Center (WERC), began installing meteorological stations on the North Slope in the central Alaskan Arctic. The number of stations installed ranged from 1 in 1985 to 3 in 1986, 12 in 1996, 24 in 2006, 23 in 2010, and 7 in 2014. Researchers from WERC also collected hydrological data at the following streams: Imnavait Creek (1985 to present), Upper Kuparuk River (1993 to present), Putuligayuk River (1999 to present, earlier gauged by USGS), Kadleroshilik River (2006 to 2010), Shaviovik River (2006 to 2010), No Name River (2006 to 2010), Chandler River (2009 to 2013), Anaktuvuk River (2009 to 2013), Lower Itkillik River (2012 to 2013), and Upper Itkillik River (2009 to 2013). These catchments vary in size, and runoff generation can emanate from the coastal plain, the foothills or mountains, or any combination of these locations. Snowmelt runoff in late May/early June is the most significant hydrological event of the year, except at small watersheds. For these watersheds, rain/mixed snow events in July and August have produced the floods of record. Ice jams are a major concern, especially in the larger river systems. Solid cold season precipitation is mostly uniform over the area, while warm season precipitation is greater in the mountains and foothills than on the coastal plain (roughly 3:2:1, mountains:foothills: coastal plain).The results reported here are primarily for the drainages of the Itkillik, Anaktuvuk, and Chandler River basins, where a proposed transportation corridor is being considered. Results for 2011 and before can be found in earlier reports.ABSTRACT ..................................................................................................................................... i LIST OF FIGURES ........................................................................................................................ v LIST OF TABLES .......................................................................................................................... x ACKNOWLEDGMENTS AND DISCLAIMER ........................................................................ xiii CONVERSION FACTORS, UNITS, WATER QUALITY UNITS, VERTICAL AND HORIZONTAL DATUM, ABBREVIATIONS, AND SYMBOLS ........................................... xiv ABBREVIATIONS, ACRONYMS, AND SYMBOLS .............................................................. xvi 1 INTRODUCTION ................................................................................................................... 1 2 PRIOR RELATED PUBLICATIONS .................................................................................... 5 3 STUDY AREA ........................................................................................................................ 7 4 PREVIOUS STUDIES .......................................................................................................... 11 5 METHODOLOGY AND EQUIPMENT .............................................................................. 15 5.1 Acoustic Doppler Current Profiler ................................................................................. 17 5.2 Discharge Measurements ............................................................................................... 17 5.3 Suspended Sediments ..................................................................................................... 20 5.3.1 River Sediment ........................................................................................................ 21 5.3.2 Suspended Sediment Observations ......................................................................... 21 5.3.3 Suspended Sediment Discharge .............................................................................. 22 5.3.4 Turbidity ................................................................................................................. 23 5.3.5 Bed Sediment Distribution ...................................................................................... 23 5.3.6 Suspended Sediment Grain-Size Distribution ........................................................ 24 6 RESULTS .............................................................................................................................. 25 6.1 Air Temperature and Relative Humidity ........................................................................ 25 6.2 Wind Speed and Direction ............................................................................................. 30 6.3 Net Radiation .................................................................................................................. 38 6.4 Warm Season Precipitation ............................................................................................ 40 6.5 Cold Season Precipitation .............................................................................................. 46 6.6 Annual Precipitation ....................................................................................................... 52 6.7 Soil ................................................................................................................................. 55 6.7.1 Soil Temperature ..................................................................................................... 56 6.7.1.1 Results ................................................................................................................. 57 6.7.2 Soil Moisture ........................................................................................................... 60 6.7.2.1 Results ................................................................................................................. 61 6.8 North Slope Climatology ............................................................................................... 63 6.8.1 Air Temperature ...................................................................................................... 63 6.8.2 Precipitation ............................................................................................................ 65 6.8.2.1 Warm Season Precipitation ................................................................................. 65 6.8.2.2 Cold Season Precipitation ................................................................................... 68 6.8.2.3 Annual Total Precipitation .................................................................................. 70 6.9 Surface Water Hydrology ............................................................................................... 72 6.9.1 Itkillik River ............................................................................................................ 73 6.9.2 Upper Itkillik River ................................................................................................. 74 6.9.2.1 Dye Trace Results, Upper Itkillik River .............................................................. 81 6.9.3 Lower Itkillik River 2013 Breakup and Spring Flood ............................................ 84 6.9.4 Anaktuvuk River ..................................................................................................... 91 6.9.5 Chandler River ...................................................................................................... 100 6.9.6 Additional Field Observations .............................................................................. 107 6.10 River Sediment Results ................................................................................................ 117 6.10.1 Correlation between Isco and Depth-Integrated Samples ..................................... 117 6.10.2 Suspended Sediment Rating Curves ..................................................................... 118 6.10.3 Suspended Sediment Concentrations .................................................................... 119 6.10.4 Suspended Sediment Discharge ............................................................................ 125 6.10.5 Turbidity ............................................................................................................... 129 6.10.6 Bed Sediment Distribution .................................................................................... 134 6.10.7 Suspended Sediment Grain-Size Distribution ...................................................... 136 7 HYDROLOGIC ANALYSIS .............................................................................................. 139 7.1 Precipitation Frequency Analysis ................................................................................. 139 7.2 Manning’s Roughness Coefficient (n) Calculations Revisited .................................... 142 7.3 Hydrological Modeling ................................................................................................ 147 8 CONCLUSIONS ................................................................................................................. 157 9 REFERENCES .................................................................................................................... 163 10 APPENDICES ..................................................................................................................... 169 Appendix A – Air Temperature and Relative Humidity Appendix B – Wind Speed and Direction: Wind Roses Appendix C – Cumulative Warm Season Precipitation for All Years at Each Station and Cumulative Warm Season Precipitation by Year for All Stations, 2007 to 2013 Appendix D – Soil Temperature and Moisture Content Appendix E – Rating Curves and Discharge Measurement Summarie

COVID-19 associated perimyocarditis

Perimyocarditis is a well-known acute inflammation of the pericardium and the underlying myocardium. Most commonly perimyocarditis is of viral aetiology, specifically the coxsackie B virus. However, nowadays SARSCoV-2 associated with COVID-19 infections has emerged as a potential rare cause of perimyocarditis. This case report will demonstrate a case of a young female with perimyocarditis as diagnosed by magnetic resonance imaging (MRI) accompanied by antigens indicating a past COVID-19 infection. Clinical status as well as Findings at MRI, echocardiography and lab results will be reviewed.Cardiolog

The role of insulin resistance in the relation of visceral, abdominal subcutaneous and total body fat to cardiovascular function

Background and aims: The separate cardiovascular effects of type 2 diabetes and adiposity remain to be examined. This study aimed to investigate the role of insulin resistance in the relations of visceral (VAT), abdominal subcutaneous (aSAT) adipose tissue and total body fat (TBF) to cardiovascular remodeling.Methods and results: In this cross-sectional analysis of the population-based Netherlands Epidemiology of Obesity study, 914 middle-aged individuals (46% men) were included. Participants underwent magnetic resonance imaging. Standardized linear regression coefficients (95%CI) were calculated, adjusted for potential confounding factors. All fat depots and insulin resistance (HOMA-IR), separate from VAT and TBF, were associated with lower mitral early and late peak filling rate ratios (E/A): -0.04 (-0.09;0.01) per SD (54 cm(2)) VAT; -0.05 (-0.10;0.00) per SD (94 cm(2)) aSAT; -0.09 (-0.16;-0.02) per SD (8%) TBF; -0.11 (-0.17;-0.05) per 10-fold increase in HOMA-IR, whereas VAT and TBF were differently associated with left ventricular (LV) end-diastolic volume: -8.9 (-11.7;-6.1) mL per SD VAT; +5.4 (1.1;9.7) mL per SD TBF. After adding HOMA- IR to the model to evaluate the mediating role of insulin resistance, change in E/A was -0.02 (-0.07;0.04) per SD VAT; -0.03 (-0.08;0.02) per SD aSAT; -0.06 (- 0.13;0.01) per SD TBF, and change in LV end-diastolic volume was -7.0 (-9.7;-4.3) mL per SD VAT. In women, adiposity but not HOMA-IR was related to higher aortic arch pulse wave velocity.Conclusion: Insulin resistance was associated with reduced diastolic function, separately from VAT and TBF, and partly mediated the associations between adiposity depots and lower diastolic function. (C) 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.Cardiolog

The effect of glycemic control on renal triglyceride content assessed by proton spectroscopy in patients with type 2 diabetes mellitus: a single-center parallel-group trial

Objective: Ectopic lipid accumulation in the kidney (fatty kidney) is a potential driver of diabetic kidney disease, and tight glycemic control can reduce risk of diabetic nephropathy. We assessed whether glycemic control influences renal triglyceride content (RTGC). Furthermore, we compared glucagon-like peptide-1 receptor agonist liraglutide versus standard glucose-lowering therapy. Design andMethods: In this single-center parallel-group trial, patients with type 2 diabetes mellitus were randomized to liraglutide or placebo added to standard care (metformin/sulfonylurea derivative/insulin). Changes in RTGC after 26 weeks of glycemic control measured by proton spectroscopy and difference in RTGC between treatment groups were analyzed.Results: Fifty patients with type 2 diabetes mellitus were included in the baseline analysis (mean age, 56.5 +/- 9.1 years; range, 33-73 years; 46% males). Seventeen patients had baseline and follow-up measurements. Mean glycated hemoglobin was 7.8 +/- 0.8%, which changed to 7.3 +/- 0.9% after 26 weeks of glycemic control irrespective of treatment group (P = .046). Log-transformed RTGC was -0.68 +/- 0.30% and changed to -0.83 +/- 0.32% after 26 weeks of glycemic control irrespective of treatment group (P = .049). A 26-week-to-baseline RTGC ratio (95% confidence interval) was significantly different between liraglutide (-0.30 [-0.50, -0.09]) and placebo added to standard care (-0.003 [-0.34, 0.34]) (P = .04).Conclusion: In this exploratory study, we found that 26 weeks of glycemic control resulted in lower RTGC, in particular for liraglutide; however, larger clinical studies are needed to assess whether these changes reflect a true effect of glycemic control on fatty kidney. (C) 2020 The Authors. Published by Elsevier Inc. on behalf of the National Kidney Foundation, Inc.Cardiovascular Aspects of Radiolog

Protecting habitats in low-intensity tropical farmland using carbon-based payments for ecosystem services

Tropical land-use change for agricultural expansion is the primary driver of global biodiversity decline. Efforts to stem this decline often focus on protecting pristine habitats or returning farmland to forest, yet such approaches fail to protect vulnerable taxa reliant on habitats within low-intensity farmland. We assess the economic viability of carbon-based payments for ecosystem services (PES) to protect farmland trees and fallowing in Ghana, which provide vital wintering sites for imperiled Afro-palearctic migrant birds and enhance landscape-level carbon storage. We estimate the carbon breakeven prices (BEPs) associated with alternative agricultural management scenarios that protect existing farmland trees. BEPs associated with tree protection on existing farmland were very low, ranging from US$2.49 to US$6.45 t−1 CO2. Extending and reintroducing fallow periods also carried competitive BEPs, US$4.67—US$15.45 t−1 CO2, when combined with the protection of 50 trees per hectare. Accounting for leakage and economic uncertainty increased BEPs considerably, but scenarios protecting farmland trees and extending fallow periods remained below EU Emissions Trading Scheme prices. Protecting low-intensity farmland habitats and associated biodiversity is cost-effective under carbon-based PES. Implementation should be combined with efforts to close yield gaps, providing greater local food security and resilience

Region of Excessive Flux of PeV Cosmic Rays in the Direction Toward Pulsars PSR J1840+5640 and LAT PSR J1836+5925

An analysis of arrival directions of extensive air showers (EAS) registered with the EAS MSU and EAS-1000 prototype arrays has revealed a region of excessive flux of PeV cosmic rays in the direction toward pulsars PSR J1840+5640 and LAT PSR J1836+5925 at significance level up to 4.5sigma. The first of the pulsars was discovered almost 30 years ago and is a well-studied old radio pulsar located at the distance of 1.7pc from the Solar system. The second pulsar belongs to a new type of pulsars, discovered by the space gamma-ray observatory Fermi, pulsations of which are not observed in optical and radio wavelengths but only in the gamma-ray range of energies (gamma-ray-only pulsars). In our opinion, the existence of the region of excessive flux of cosmic rays registered with two different arrays provides a strong evidence that isolated pulsars can give a noticeable contribution to the flux of Galactic cosmic rays in the PeV energy range.Comment: 14 pages; v.2: a few remarks to match a version accepted for Astronomy Letters added. They can be found by redefining the \NEW command in the preamble of the LaTeX fil

Mendelian randomization study of the relation between adiponectin and heart function, unravelling the paradox

High adiponectin concentrations are generally regarded as beneficial with regard to cardiometabolic health, but have been paradoxically associated with increased cardiovascular disease risk, specifically heart failure, in individuals at high cardiovascular risk. We aimed to investigate the association between adiponectin and heart function parameters, and inversely, we estimated the effect of genetically-determined heart function and NTproBNP as the main marker of heart failure on adiponectin using Mendelian randomisation. Observational analyses between adiponectin and measures of heart function, i.e. E/A ratio, left, and right ventricular ejection fraction, were performed in participants of the Netherlands Epidemiology of Obesity (NEO) study, assessed by MRI of the heart (n = 1,138). Two-sample Mendelian randomisation analyses were conducted to estimate the effect of NT-proBNP and heart function on adiponectin concentrations using publicly-available summary statistics (ADIPOGen; the PLATO trial). The mean (standard deviation) age was 56 (6) years and mean body mass index was 26 (4) kg/m2. Per five mu g/ mL higher adiponectin, the E/A ratio was -0.05 (95 % CI: -0.10, -0.01) lower, left ventricle ejection fraction was -0.5 % (95 % CI: -1.1, 0.1) lower, and right ventricle ejection fraction was 0.5 % (95 % CI: -0.1, 1.2) higher. Genetically-determined NT-proBNP was causally related to adiponectin concentrations in ADIPOGen: per doubling of genetically-determined NT-proBNP, adiponectin concentrations were 11.4 % (95 % CI: 1.7, 21.6) higher. With causal MR methods we showed that NT-proBNP affects adiponectin concentrations, while adiponectin is not associated with heart function parameters. Therefore, reverse causation may explain the adiponectin paradox observed in previous studies.Clinical epidemiolog

Parameters of the Magnetic Flux inside Coronal Holes

Parameters of magnetic flux distribution inside low-latitude coronal holes (CHs) were analyzed. A statistical study of 44 CHs based on Solar and Heliospheric Observatory (SOHO)/MDI full disk magnetograms and SOHO/EIT 284\AA images showed that the density of the net magnetic flux, $B_{{\rm net}}$, does not correlate with the associated solar wind speeds, $V_x$. Both the area and net flux of CHs correlate with the solar wind speed and the corresponding spatial Pearson correlation coefficients are 0.75 and 0.71, respectively. A possible explanation for the low correlation between $B_{{\rm net}}$ and $V_x$ is proposed. The observed non-correlation might be rooted in the structural complexity of the magnetic field. As a measure of complexity of the magnetic field, the filling factor, $f(r)$, was calculated as a function of spatial scales. In CHs, $f(r)$ was found to be nearly constant at scales above 2 Mm, which indicates a monofractal structural organization and smooth temporal evolution. The magnitude of the filling factor is 0.04 from the Hinode SOT/SP data and 0.07 from the MDI/HR data. The Hinode data show that at scales smaller than 2 Mm, the filling factor decreases rapidly, which means a mutlifractal structure and highly intermittent, burst-like energy release regime. The absence of necessary complexity in CH magnetic fields at scales above 2 Mm seems to be the most plausible reason why the net magnetic flux density does not seem to be related to the solar wind speed: the energy release dynamics, needed for solar wind acceleration, appears to occur at small scales below 1 Mm.Comment: 6 figures, approximately 23 pages. Accepted in Solar Physic