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Under pressure: the connection involving cranial form and also digging force throughout caecilians (Gymnophiona).
Overall, 99.5% (205/206) of hand samples yielded microorganisms. Most were non-pathogenic, whether skin microbiota (98.5% of participants) or non-skin microbiota (93.2% of participants). Only 2.4% (5/206) of samples yielded antibiotic-resistant bacteria. Children were more likely than adults to carry potentially pathogenic (OR = 3.63, 95% CI 1.66-7.93) and presumably non-pathogenic (OR = 6.61, 95% CI 1.67-26.15) non-skin microorganisms. Conclusions Large community gatherings can serve as efficient sites for estimating the prevalence of microorganism carriage. A small proportion of participants carried antimicrobial-resistant pathogens on their hands; most carried non-pathogenic microorganisms, and no exposures specific to the state fair were associated with microorganism carriage.Given that COVID-19 (SARS-CoV-2) has crept into Africa, a major public health crisis or threat continues to linger on the continent. Many local governments and various stakeholders have stepped up efforts for early detection and management of COVID-19. This mini review highlights the current trend in Africa, history and general epidemiological information on the virus. Current ongoing efforts (e.g., improving testing capacity) and some effective ways (e.g., intensified surveillance, quick detection, contact tracing, isolation measures [e.g., quarantine], and social distancing) of preventing and managing COVID-19 in Africa are described. The review concludes by emphasizing the need for public health infrastructure development (e.g., laboratories, infectious disease centers, regional hospitals) and human capacity building for combating COVID-19 and potential future outbreaks. Additionally, regular public health educational campaigns are urgently required. Future epidemiological studies to ascertain case fatality and mortality trends across the continent for policy directions are necessary.Background and aims The COVID-19 pandemic has caused social and economic turmoil, which has led to enormous strain for many families. Past work with pandemic outbreaks suggests that media attention can increase anxiety and compensatory behaviors. Social isolation can lead to increase in online communication and parents who use social media may be affected by other people's emotions online through what is known as digital emotion contagion (DEC). The current study aimed to examine the role of DEC in the relationship between stress, concern about COVID-19, parental burnout and emotion regulation (ER). Methods In April 2020, an online survey was advertised in Social Media Parenting Groups and published on FIU Psychology online research system SONA. Data were analyzed using correlational analysis, linear and multiple linear regression, and moderation analysis. Results Concern about COVID-19 predicted stress, depression, and parental burnout. Susceptibility to DEC significantly increased the impact of stress on parental burnout. Having relatives infected with COVID-19 increased the effect of DEC on parental burnout. A higher level of ER buffered the relationship between emotion contagion and concern about COVID-19. Conclusion These findings suggest that susceptibility to digital emotion contagion may have a negative effect on parents. Digital emotion contagion may increase parental burnout and is tied to stress.Introduction A healthcare provider's ability to give a strong recommendation for the HPV vaccine is of utmost importance in increasing HPV vaccination. To reduce the burden of HPV-related cancers, there is a critical need to develop and implement theory-based interventions aimed at strengthening healthcare providers' communication about the HPV vaccine. BX471 research buy Methods We used Intervention Mapping (IM) steps 1-5 to develop and implement a provider-level intervention that aligns with the priorities and needs of a large, urban Federally Qualified Health Center (FQHC). Results In step 1, a diverse planning group identified barriers to HPV vaccination in clinical settings and generated process maps and a logic model of the problem. Step 2 outlined outcomes and provider performance objectives of the intervention and identified knowledge, skills, self-efficacy, outcome expectations, and normative beliefs as modifiable targets that need to change for providers to deliver strong recommendations for the HPV vaccine to parentsoping interventions and may help to facilitate implementation in real-world clinical settings by tailoring intervention components to the needs of the population.Objective Many online and printed media publish health news of questionable trustworthiness and it may be difficult for laypersons to determine the information quality of such articles. The purpose of this work was to propose a methodology for the automatic assessment of the quality of health-related news stories using natural language processing and machine learning. Materials and Methods We used a database from the website HealthNewsReview.org that aims to improve the public dialogue about health care. HealthNewsReview.org developed a set of criteria to critically analyze health care interventions' claims. In this work, we attempt to automate the evaluation process by identifying the indicators of those criteria using natural language processing-based machine learning on a corpus of more than 1,300 news stories. We explored features ranging from simple n-grams to more advanced linguistic features and optimized the feature selection for each task. Additionally, we experimented with the use of pre-trained natural language model BERT. Results For some criteria, such as mention of costs, benefits, harms, and "disease-mongering," the evaluation results were promising with an F1 measure reaching 81.94%, while for others the results were less satisfactory due to the dataset size, the need of external knowledge, or the subjectivity in the evaluation process. Conclusion These used criteria are more challenging than those addressed by previous work, and our aim was to investigate how much more difficult the machine learning task was, and how and why it varied between criteria. For some criteria, the obtained results were promising; however, automated evaluation of the other criteria may not yet replace the manual evaluation process where human experts interpret text senses and make use of external knowledge in their assessment.
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