Unignorable public health risk of avian influenza virus during COVID‐19 pandemic

alexandrossfakianakis shared this article with you from Inoreader Unignorable public health risk of avian influenza virus during COVID‐19 pandemic via Journal of Medical Virology Abstract Human infections with the newly emerging reassortant H5N6 avian influenza viruses (AIV) were reported1. AIV has been prevalent persistently worldwide, which results in a devastating impact on the poultry industry and even public health. Highly pathogenic AIV (HPAIV), including H5Ny lineages (H5N1, H5N2, H5N6, and H5N8) and H7N9 subtype, exhibit severe disease phenotype with high morbidity and mortality rates in birds, especially chickens. Although H9N2 AIV only could induce mild or no obvious clinical signs in poultry, the enlarged host species of H9N2 AIV could induce the potential threat to global health2 In late 2019, the novel coronavirus disease (COVID-19) broke out and swept the world population. Drastic mitigation measures were implemented among the international community to stop the COVID-19 crisis, including mass quarantine, physical distancing, and face mask usage. However, the elevated trend of human infections with the emer ging AIV during ongoing COVID-19 circulation still highlights the alert of the possible risk for the next human pandemic3. This article is protected by copyright. All rights reserved. View on Web

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Biophysiological stress markers relate differently to grit and school engagement among lower‐ and higher‐track secondary school students

alexandrossfakianakis shared this article with you from Inoreader Biophysiological stress markers relate differently to grit and school engagement among lower‐ and higher‐track secondary school students via British Journal of Educational Psychology Abstract Background This study examines the relationship between adolescents' biophysiological stress (i.e. cortisol, alpha-amylase and oxidative stress) and the development of grit and school engagement over one school year. Aims The study aims to identify how objective stress affects grit and three dimensions of school engagement. Based on the conservation of resources (COR) theory, the study considers lower- and higher-track school students and their genders. Sample The sample consists of secondary school students (N = 82; MAge = 13.71; SD = 0.67; 48% girls) from Germany. Methods Students participated in a questionnaire and a biophysiological study in the first semester (t1) of the school year and completed the same questionnaire at the end of the school year (t2). After conducting whole-sample analysis, a multi-group cross-lagged panel model was calculated to identify differences among students at lower- and higher-track schools. Results Whole-sample analysis reveals that students who exhibit high levels of cortisol report lower cognitive school engagement at t2, whereas students who exhibit high levels of alpha-amylase exhibit less grit at t2. Additionally, lower-track students who exhibited high cortisol levels reported lower cognitive and emotional school engagement throughout the school year. Furthermore, higher-track students with high oxidative stress levels reported lower grit and behavioural school engagement at t2. Conclusions Examining the relationship between biophysiological stress markers and grit and school engagement of students at lower- and higher-track schools indicates that the educational context and its specific subculture shapes physiological stress reactions, which are related differently to grit and engagement dimensions. View on Web

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Sparstolonin B inhibits pancreatic adenocarcinoma through the NF-κB signaling pathway

alexandrossfakianakis shared this article with you from Inoreader Sparstolonin B inhibits pancreatic adenocarcinoma through the NF-κB signaling pathway via ScienceDirect Publication: Experimental Cell Research Publication date: Available online 18 May 2022 Source: Experimental Cell Research Author(s): Yang Lyu, Bowen Duan, Ziming Liu, Fan Yang, Chen Chen, Xuejiao Jiang, Xiang Liu View on Web

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Efficacy and safety of Lenzumestrocel (Neuronata-R® inj.) in patients with amyotrophic lateral sclerosis (ALSUMMIT study): study protocol for a multicentre, randomized, double-blind, parallel-group, sham procedure-controlled, phase III trial

alexandrossfakianakis shared this article with you from Inoreader Efficacy and safety of Lenzumestrocel (Neuronata-R® inj.) in patients with amyotrophic lateral sclerosis (ALSUMMIT study): study protocol for a multicentre, randomized, double-blind, parallel-group, sham procedure-controlled, phase III trial via Trials - Latest Articles A single cycle (two repeated treatments) with intrathecal autologous bone marrow-derived mesenchymal stem cells (BM-MSCs, 26-day interval) showed safety and provided therapeutic benefit lasting 6 months in pat... View on Web

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High flow nasal cannula in the management of obstructive sleep Apnoea postoperatively. Is flow a new alternative to positive pressure?

alexandrossfakianakis shared this article with you from Inoreader High flow nasal cannula in the management of obstructive sleep Apnoea postoperatively. Is flow a new alternative to positive pressure? via ScienceDirect Publication: American Journal of Otolaryngology Publication date: Available online 17 May 2022 Source: American Journal of Otolaryngology Author(s): Abhijit S. Nair, Antonio M. Esquinas View on Web

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Association between sperm mitochondrial DNA copy number and deletion rate and industrial air pollution dynamics

alexandrossfakianakis shared this article with you from Inoreader Association between sperm mitochondrial DNA copy number and deletion rate and industrial air pollution dynamics via Earth and environmental sciences : nature.com subject feeds View on Web

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Changes in global DNA methylation under climatic stress in two related grasses suggest a possible role of epigenetics in the ecological success of polyploids

alexandrossfakianakis shared this article with you from Inoreader Changes in global DNA methylation under climatic stress in two related grasses suggest a possible role of epigenetics in the ecological success of polyploids via Earth and environmental sciences : nature.com subject feeds View on Web

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Magnetic resonance imaging assessment of juvenile idiopathic arthritis using OMERACT and EuroTMjoint classifications

alexandrossfakianakis shared this article with you from Inoreader Magnetic resonance imaging assessment of juvenile idiopathic arthritis using OMERACT and EuroTMjoint classifications via International Journal of Oral and Maxillofacial Surgery via MedWorm.com This retrospective case –control study compared inflammatory and structural damage in the temporomandibular joint of patients with juvenile idiopathic arthritis (JIA) and its subtypes and healthy patients using the Outcome Measures in Rheumatology Clinical Trials (OMERACT) and EuroTMjoint classifications. Correlations be tween the scores of the two classifications and time of diagnosis were evaluated. Twenty-nine JIA patients and 48 age-matched healthy participants were examined. TMJ images on each side were considered individually. (Source: International Journal of Oral and Maxillofacial Surgery) View on Web

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Machine Learning Based Forecast of Dengue Fever in Brazilian Cities using Epidemiological and Meteorological Variables

alexandrossfakianakis shared this article with you from Inoreader Machine Learning Based Forecast of Dengue Fever in Brazilian Cities using Epidemiological and Meteorological Variables via American Journal of Epidemiology - Advance Access Abstract Dengue is a serious public health concern in Brazil and globally. In the absence of a universal vaccine or specific treatments, prevention relies on vector control and disease surveillance. Accurate and early forecasts can help reduce the spread of the disease. In this study, we develop a model to predict monthly dengue cases in Brazilian cities one month ahead from 2007-2019. We compare different machine learning algorithms and feature selection methods using epidemiological and meteorological variables. We find that different models work best in different cities, and a random forests model trained on monthly dengue cases performs best overall. It produces lower errors than a seasonal naïve baseline model, gradient boosting regression, feed-forward neural network, and support vector regression. For each city, we compute the mean absolute error between predictions and true monthly dengue cases on the test set. For the median city, the error is 1 2.2 cases. This error is reduced to 11.9 when selecting the optimal combination of algorithm and input features for each city individually. Machine learning and especially decision tree ensemble models may contribute to dengue surveillance in Brazil, as they produce low out-of-sample prediction errors for a geographically diverse set of cities. View on Web

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