Interferential electrical stimulation improves peripheral vasodilatation in healthy individuals

BACKGROUND:Interferential electrical stimulation (IES), which may be linked to greater penetration of deep tissue, may restore blood flow by sympathetic nervous modulation; however, studies have found no association between the frequency and duration of the application and blood flow. We hypothesized that 30 min of IES applied to the ganglion stellate region might improve blood flow redistribution.OBJECTIVES:The purpose of this study was to determine the effect of IES on metaboreflex activation in healthy individuals.METHOD:Interferential electrical stimulation or a placebo stimulus (same protocol without electrical output) was applied to the stellate ganglion region in eleven healthy subjects (age 25±1.3 years) prior to exercise. Mean blood pressure (MBP), heart rate (HR), calf blood flow (CBF) and calf vascular resistance (CVR) were measured throughout exercise protocols (submaximal static handgrip exercise) and with recovery periods with or without postexercise circulatory occlusion (PECO+ and PECO -, respectively). Muscle metaboreflex control of calf vascular resistance was estimated by subtracting the area under the curve when circulation was occluded from the area under the curve from the AUC without circulatory occlusion.RESULTS:At peak exercise, increases in mean blood pressure were attenuated by IES (p<0.05), and the effect persisted under both the PECO+ and PECO- treatments. IES promoted higher CBF and lower CVR during exercise and recovery. Likewise, IES induced a reduction in the estimated muscle metaboreflex control (placebo, 21±5 units vs. IES, 6±3, p<0.01).CONCLUSION:Acute application of IES prior to exercise attenuates the increase in blood pressure and vasoconstriction during exercise and metaboreflex activation in healthy subjects.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FIPE-HCPA, Porto Alegre, BrazilUniversidade Federal de São Paulo (UNIFESP) Cardiovascular Surgery DepartmentHospital de Clinicas de Porto AlegreUniversidade de Brasilia Physical Therapy DepartmentUNIFESP, Cardiovascular Surgery DepartmentSciEL

Recharge assessment in the context of expanding agricultural activity: Urucuia Aquifer System, western State of Bahia, Brazil

Groundwater recharge rate estimation is crucial to sustainable development of aquifers in intensely pumped regions, such as the Urucuia Aquifer System (UAS). A sedimentary aquifer in Western Bahia, Brazil, that underlies one of the major agricultural areas of the country where there has been major growth of irrigated areas. This study seeks to evaluate the recharge component of the water budget in the UAS area, based on three complementary techniques. The double-ring infiltrometer test was used to evaluate surface infiltration capacity, an important control on recharge. Water level data from wells (2011–2019 period, 19 wells) in the Brazilian Geological Survey’s Integrated Groundwater Monitoring Network (RIMAS-CPRM) was used to estimate the aquifer recharge using the water table fluctuation (WTF) method. Additionally, this study used the Soil Water Assessment Tool (SWAT) model in two selected sub-basins to estimate deep recharge from the surface hydrological data. The results of the infiltrometer tests show a notable difference in the infiltration rates between the natural vegetation zones and cropped areas. The WTF and SWAT simulations results suggest similar ranges of recharge rate (an average of 24% of precipitation, in both methods). Results of the study indicate equivalence of these methods to estimate the recharge in sedimentary unconfined aquifers as UAS

CoronaVac vaccine is effective in preventing symptomatic and severe COVID-19 in pregnant women in Brazil: a test-negative case-control study.

BACKGROUND: More doses of CoronaVac have been administered worldwide than any other COVID-19 vaccine. However, the effectiveness of COVID-19 inactivated vaccines in pregnant women is still unknown. We estimated the vaccine effectiveness (VE) of CoronaVac against symptomatic and severe COVID-19 in pregnant women in Brazil. METHODS: We conducted a test-negative design study in all pregnant women aged 18-49 years with COVID-19-related symptoms in Brazil from March 15, 2021, to October 03, 2021, linking records of negative and positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) tests to national vaccination records. We also linked records of test-positive cases with notifications of severe, hospitalised or fatal COVID-19. Using logistic regression, we estimated the adjusted odds ratio and VE against symptomatic COVID-19 and against severe COVID-19 by comparing vaccine status in test-negative subjects to test-positive symptomatic cases and severe cases. RESULTS: Of the 19,838 tested pregnant women, 7424 (37.4%) tested positive for COVID-19 and 588 (7.9%) had severe disease. Only 83% of pregnant women who received the first dose of CoronaVac completed the vaccination scheme. A single dose of the CoronaVac vaccine was not effective at preventing symptomatic COVID-19. The effectiveness of two doses of CoronaVac was 41% (95% CI 27.1-52.2) against symptomatic COVID-19 and 85% (95% CI 59.5-94.8) against severe COVID-19. CONCLUSIONS: A complete regimen of CoronaVac in pregnant women was effective in preventing symptomatic COVID-19 and highly effective against severe illness in a setting that combined high disease burden and marked COVID-19-related maternal deaths

Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle

Abstract\ud \ud Background\ud Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.\ud \ud \ud Results\ud Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches.\ud \ud \ud Conclusions\ud The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.This study was conducted with funding from EMBRAPA (Macroprograma1,\ud 01/2005) and FAPESP (process number 2012/23638-8). GBM, LLC, LCAR and\ud MMA were granted CNPq fellowships. We thank Sean McWilliam, Marina R. S.\ud Fortes, Edilson Guimaraes, Robson Rodrigues Santiago, Roselito F. da Silva,\ud Fernando F. Cardoso, Flavia Aline Bressani, Wilson Malago Jr., Avelardo U. C.\ud Ferreira, Michel E. B. Yamaguishi and Fabio D. Vieira for the help and\ud technical assistance. The authors would like to acknowledge the\ud collaborative efforts among EMBRAPA, University of Sao Paulo and CSIRO

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Effects of Home-Based Electrical Stimulation on Plasma Cytokines Profile, Redox Biomarkers, and Metalloproteinases in the Heart Failure with Reduced Ejection Fraction: A Randomized Trial

Background: Low-frequency electrical stimulation (LFES) is an adjuvant method for heart failure (HF) patients with restrictions to start an exercise. However, the impact on molecular changes in circulating is unknown. We investigated the effects of 10 weeks of home-based LFES on plasma cytokines profile, redox biomarkers, metalloproteinases (MMPs) activity, and exercise performance in HF patients. Methods: Twenty-four HF patients (52.45 ± 9.15 years) with reduced ejection fraction (HFrEF) (EF 0.05). Conclusion: LFES protocol is a promising intervention to modulate MMPs activity in HFrEF patients, although with limited functional effects. These preliminary responses may help the muscle to adapt to future mechanical demands dynamically

LMP based bid formation for virtual power players operating in smart grids

Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units