The immune response to SARS-CoV2 is under intense investigation, but not fully understood att this moment. Severe disease is characterized by vigorous inflammatory responses in the lung, often with a sudden onset after 5-7 days of stable disease. Efforts to modulate this hyperinflammation and the associated acute respiratory distress syndrome, rely on the unraveling of the immune cell interactions and cytokines that drive such responses. Systems-level analyses are required to simultaneously capture all immune cell populations and the many protein mediators by which cells communicate. Since every patient analyzed will be captured at different stages of his or her infection, longitudinal monitoring of the immune response is critical. Here we report on a systems-level blood immunomonitoring study of 39 adult patients, hospitalized with severe COVID-19 and followed with up to 14 blood samples from acute to recovery phases of the disease. We describe an IFNg-Eosinophil axis activated prior to lung hyperinflammation and changes in cell-cell coregulation during different stages of the disease. We also map an immune trajectory during recovery that is shared among patients with severe COVID-19.
Nutrition apps for mobile devices such as smartphones are becoming more widely available. They can help ease the arduous chore of documenting intake for nutritional assessment and self-monitoring. This allows people to control food intake, support their participation in physical activities, and promote a healthy lifestyle. However, there remains a lack of research regarding systematic analysis mapping studies in this area. The objective of this study is to identify dietary self-monitoring implementation strategies on a mobile application. This study analyzed 205 journals from the Scopus database using the descriptive-analytic method. The records used in this exploration study were those released between 2007 and 2021 that were collected based on the keywords “dietary self-monitoring,” or “nutrition application,” or “nutrition apps,” and “calorie application.” Data analysis was conducted using the VOSviewer and NVivo software analytical tools. The results show that research studies on dietary self-monitoring increased in 2017. Results also indicated that the country that contributed the most to this topic was China. The study on mobile applications for dietary self-monitoring revealed seven clusters of dominant themes: attitude to improved dietary behaviors, parameters for disease diagnosis, noncommunicable diseases, methods, nutrition algorithms, mobile health applications, and body mass index. This study also analyzed research trends by year. The current research trends are about dietary self-monitoring using a mobile application that can upgrade people’s lifestyles, enable real-time meal recording and the convenience of automatically calculating the calorie content of foods consumed, and potentially improve the delivery of health behavior modification interventions to large groups of people. The researchers summarized the recent advances in dietary self-monitoring research to shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance for future research and perspectives in this rapidly developing field.
This study aims to investigate the influence of credit risk on bank financial stability of Vietnamese commercial banks, understanding the impact channels and patterns of Vietnamese commercial banks in particular by proposing implications for solutions to reduce credit risks and promote financial stability for banks. We employed the POOL, FEM, REM, GMM techniques, and Monte Carlo approach and used secondary data collected from 2005 to 2019. The findings reveal a direct relationship between bank credit risk, profitability, and bank financial stability, as well as a partly indirect association. The above suggests that bank credit risk and bank profitability can explain the stability of the Vietnam commercial banking sector. In the first step, we examine the relationship between bank credit risk and bank profitability. The findings reveal that size and previous period profitability positively affect bank profitability, while non-performing loans, loan loss provision, non-interest income, efficiency, and bank credit growth positively correlate with bank profitability. Bank profitability does not affect bank credit risk. In the second phase, we examine the effects of bank profitability on bank stability. Regression results demonstrate that previous-period profitability and bank stability impact current-period bank financial stability. We test the impact of bank credit risk on bank financial stability in the third step, and the results suggest that non-performing loans, non-interest income, loan loss provision, and prior bank stability positively impact current bank financial stability. This study offers a new understanding of the channel's effect of credit risk on bank financial stability. The results indicated that the credit risk had a direct and partly indirect impact on bank financial stability.
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