Τετάρτη 18 Μαΐου 2022

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

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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.

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Reducing gender differences in student motivational‐affective factors: A meta‐analysis of school‐based interventions

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Abstract

Background

Research shows that gender differences tend to exist in student motivational-affective factors in core subjects such as math, science or reading, where one gender is stereotypically disadvantaged.

Aims

This study aimed to investigate strategies that could reduce these gender differences by conducting a meta-analysis on school-based intervention studies that targeted student motivational-affective factors. We therefore evaluated whether interventions had differential effects for male and female students' motivational-affective factors in a given academic subject. We also evaluated potential moderator variables.

Method

After conducting a systematic database search and screening abstracts for inclusion, we synthesized 71 effect sizes from 20 primary studies. All included studies were conducted in science or mathematics-related subjects, which are stereotypically female-disadvantaged.

Results

While the interventions had significant positive effects for both genders, there was no statistically significant difference between the two genders with regard to the intervention effects on motivational-affective factors. However, the descriptive effect size for female students (g = .49) was far greater than for male students (g = .28). Moderator analyses showed no significant effects for grade level, intervention duration, or school subject, but there was a significant influence of intervention method used.

Conclusions

This study demonstrated that school-based interventions have positive effects on motivational-affective factors for both genders. It also provides evidence that interventions in subjects where female students are stereotypically disadvantaged may have greater effects for females than for males. Implications and suggestions for future research are discussed.
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Biophysiological stress markers relate differently to grit and school engagement among lower‐ and higher‐track secondary school students

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

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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
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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

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

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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

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Total inferior border ostectomy versus T-shape genioplasty for chin narrowing combined with mandibular contouring

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The objective of this study was to compare the indications and outcomes of the total inferior border ostectomy and T-shape genioplasty. A retrospective study was conducted using the clinical notes and records of patients who underwent total inferior border ostectomy (group 1, n  = 42) and T-shape genioplasty (group 2, n = 60). The outcomes were evaluated by assessment of computed tomography images combined with medical records and photographs. Lower facial height, chin width, chin symmetry, and facial proportions, as well as patient satisfaction and complications were investigated. (Source: International Journal of Oral and Maxillofacial Surgery)
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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
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.
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