Was the GLE on May 17, 2012 linked with the M5.1-class flare the first in the 24th solar cycle?

On May 17, 2012 an M5.1-class flare exploded from the sun. An O-type coronal mass ejection (CME) was also associated with this flare. There was an instant increase in proton flux with peak at $\geq 100$ MeV, leading to S2 solar radiation storm level. In about 20 minutes after the X-ray emission, the solar particles reached the Earth.It was the source of the first (since December 2006) ground level enhancement (GLE) of the current solar cycle 24. The GLE was detected by neutron monitors (NM) and other ground based detectors. Here we present an observation by the Tupi muon telescopes (Niteroi, Brazil, $22^{0}.9 S$, $43^{0}.2 W$, 3 m above sea level) of the enhancement of muons at ground level associated with this M5.1-class solar flare. The Tupi telescopes registered a muon excess over background $\sim 20\%$ in the 5-min binning time profile. The Tupi signal is studied in correlation with data obtained by space-borne detectors (GOES, ACE), ground based neutron monitors (Oulu) and air shower detectors (the IceTop surface component of the IceCube neutrino observatory). We also report the observation of the muon signal possibly associated with the CME/sheath striking the Earth magnetosphere on May 20, 2012. We show that the observed temporal correlation of the muon excess observed by the Tupi muon telescopes with solar transient events suggests a real physical connection between them. Our observation indicates that combination of two factors, the low energy threshold of the Tupi muon telescopes and the location of the Tupi experiment in the South Atlantic Anomaly region, can be favorable in the study and detection of the solar transient events. Our experiment provides new data complementary to other techniques (space and ground based) in the study of solar physics.Comment: 9 pages, 10 figure

Novas manifestações clínicas da síndrome da circovirose suína: leitões de maternidade.

bitstream/CNPSA/15848/1/publicacao_r8v4m2p.pd

Impact of Glycemic and Blood Pressure Variability on Surrogate Measures of Cardiovascular Outcomes in Type 2 Diabetic Patients

OBJECTIVE—The effect of glycemic variability (GV) on cardiovascular risk has not been fully clarified in type 2 diabetes. We evaluated the effect of GV, blood pressure (BP), and oxidative stress on intima-media thickness (IMT), left ventricular mass index (LVMI), flow-mediated dilation (FMD), and sympathovagal balance (low frequency [LF]/high frequency [HF] ratio) in 26 type 2 diabetic patients (diabetes duration 4.41 6 4.81 years; HbA1c 6.70 6 1.25%) receiving diet and/or metformin treatment, with no hypotensive treatment or complications. RESEARCH DESIGN AND METHODS—Continuous glucose monitoring (CGM) data were used to calculate mean amplitude of glycemic excursion (MAGE), continuous overall net glycemic action (CONGA)-2, mean blood glucose (MBG), mean postprandial glucose excursion (MPPGE), and incremental area under the curve (IAUC). Blood pressure (BP), circadian rhythm, and urinary 15-F2t-isoprostane (8-iso-prostaglandin F2a [PGF2a]) were also evaluated. Subjects were divided into dipper (D) and nondipper (ND) groups according to DBP. RESULTS—IMT and LVMIwere increased inNDversusD(0.7760.08 vs. 0.6860.13 [P=0.04] and 67 6 14 vs. 55 6 11 [P = 0.03], respectively). MBG, MAGE, and IAUC were significantly associated with LF/HF ratio at night (r = 0.50, P = 0.01; r = 0.40, P = 0.04; r = 0.41, P = 0.04, respectively), MPPGE was negatively associated with FMD (r =20.45, P = 0.02), andCONGA-2was positively associatedwith LVMI (r=0.55, P=0.006).TheDsystolic BP was negatively associated with IMT (r =20.43, P = 0.03) andwith LVMI (r =20.52, P = 0.01). Urinary 8-iso-PGF2a was positively associated with LVMI (r = 0.68 P , 0.001). CONCLUSIONS—An impaired GV and BP variability is associated with endothelial and cardiovascular damage in short-term diabetic patients with optimal metabolic control. Oxidative stress is the only independent predictor of increased LV mass and correlates with glucose and BP variability

Genome-wide association study for resistance to Pseudomonas syringae pv. garcae in Coffea arabica.

Bacteria halo blight (BHB), a coffee plant disease caused by Pseudomonas syringae pv. garcae, has been gaining importance in producing mountain regions and mild temperatures areas as well as in coffee nurseries. Most Coffea arabica cultivars are susceptible to this disease. In contrast, a great source of genetic diversity and resistance to BHB are found in C. arabica Ethiopian accessions. Aiming to identify quantitative trait nucleotides (QTNs) associated with resistance to BHB and the influence of these genomic regions during the domestication of C. arabica, we conducted an analysis of population structure and a Genome-Wide Association Study (GWAS). For this, we used genotyping by sequencing (GBS) and phenotyping for resistance to BHB of a panel with 120 C. arabica Ethiopian accessions from a historical FAO collection, 11 C. arabica cultivars, and the BA-10 genotype. Population structure analysis based on single-nucleotide polymorphisms (SNPs) markers showed that the 132 accessions are divided into 3 clusters: most wild Ethiopian accessions, domesticated Ethiopian accessions, and cultivars. GWAS, using the single-locus model MLM and the multi-locus models mrMLM, FASTmrMLM, FASTmrEMMA, and ISIS EM-BLASSO, identified 11 QTNs associated with resistance to BHB. Among these QTNs, the four with the highest values of association for resistance to BHB are linked to g000 (Chr_0_434_435) and g010741 genes, which are predicted to encode a serine/threonine-kinase protein and a nucleotide binding site leucine-rich repeat (NBS-LRR), respectively. These genes displayed a similar transcriptional downregulation profile in a C. arabica susceptible cultivar and in a C. arabica cultivar with quantitative resistance, when infected with P. syringae pv. garcae. However, peaks of upregulation were observed in a C. arabica cultivar with qualitative resistance, for both genes. Our results provide SNPs that have potential for application in Marker Assisted Selection (MAS) and expand our understanding about the complex genetic control of the resistance to BHB in C. arabica. In addition, the findings contribute to increasing understanding of the C. arabica domestication history

Dopaminergic Neuronal Imaging in Genetic Parkinson's Disease: Insights into Pathogenesis

Objectives:To compare the dopaminergic neuronal imaging features of different subtypes of genetic Parkinson's Disease.Methods:A retrospective study of genetic Parkinson's diseases cases in which DaTSCAN (123I-FP-CIT) had been performed. Specific non-displaceable binding was calculated for bilateral caudate and putamen for each case. The right:left asymmetry index and striatal asymmetry index was calculated.Results:Scans were available from 37 cases of monogenetic Parkinson's disease (7 glucocerebrosidase (GBA) mutations, 8 alpha-synuclein, 3 LRRK2, 7 PINK1, 12 Parkin). The asymmetry of radioligand uptake for Parkinson's disease with GBA or LRRK2 mutations was greater than that for Parkinson's disease with alpha synuclein, PINK1 or Parkin mutations.Conclusions:The asymmetry of radioligand uptake in Parkinsons disease associated with GBA or LRRK2 mutations suggests that interactions with additional genetic or environmental factors may be associated with dopaminergic neuronal loss

Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013

Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0-65·6) in 1990, to 71·5 years (UI 71·0-71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8-48·2) to 54·9 million (UI 53·6-56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade. Funding Bill & Melinda Gates Foundation