To examine whether melatonin-rich plants can defend against oxidative stress, we subjected melatonin-rich transgenic (MRT) rice plants to the singlet-oxygen-generating herbicide butafenacil. Both MRT and transgenic control (TC; expressing the vector only) rice seeds germinated and grew equally well in continuous dark on half-strength Murashige and Skoog (MS) medium containing 0.1 μm butafenacil. However, after transferring the seedlings to light, the TCs rapidly necrotized, whereas the MRT seedlings showed resistant phenotypes. Seven-day-old MRT seedlings treated with 0.1 μm butafenacil were resistant to the herbicide and contained high chlorophyll levels and low malondialdehyde and hydrogen peroxide contents compared with the TCs. As they did before the herbicide treatment, the MRT plants also produced much more melatonin after the herbicide treatment than the TCs. In addition, the MRT plants exhibited higher superoxide dismutase and catalase activities before and after the herbicide treatment compared with the TCs. This is the first report showing that MRT plants exhibit resistance against a peroxidizing herbicide that acts by generating reactive oxygen species (ROS) that kill plants. This result indicates that melatonin scavenges ROS efficiently in vivo in the transgenic plants, leading to oxidative stress resistance.

Sepsis is an aberrant systemic inflammatory response mediated by excessive production of reactive oxygen species (ROS) and reactive nitrogen species (RNS). Developing an efficient antioxidant therapy for sepsis via scavenging ROS and RNS remains a big challenge owing to the insufficient activity and sustainability of conventional antioxidants. Herein, biocompatible transition-metal dichalcogenide antioxidants with excellent scavenging activity and sustainability for H2O2, O2 •–, OH•, and nitric oxide are developed for effective sepsis treatment. WS2, MoSe2, and WSe2 nanosheets exfoliated and functionalized with a biocompatible polymer effectively scavenge mitochondrial and intracellular ROS and RNS in inflammatory cells. Among the nanosheets, WS2 most efficiently suppresses the excessive secretion of inflammatory cytokines along with scavenging ROS and RNS without affecting the expression levels of the anti-inflammatory cytokine and ROS-producing enzymes. The WS2 nanosheets significantly improve the survival rate up to 90% for severely septic mice by reducing systemic inflammation. The pharmacokinetics suggests that the WS2 nanosheets can be excreted from mice 3 days after intravenous injection. This work demonstrates the potential of therapeutic nanosheet antioxidants for effective treatment of ROS and RNS-related diseases.

The recent COVID-19 pandemic has been disrupting the daily lives of people across the world, causing a major concern for psychological well-being in children. This study aimed to examine (1) how life satisfaction and its potential predictors have been affected by the pandemic among school-aged children in Korea, and (2) which factors would predict their life satisfaction during the pandemic. We surveyed 166 fourth-graders in the Seoul metropolitan area to assess their psychological well-being and potentially related variables during the pandemic. The data were compared with those available from two pre-COVID-19 surveys, the 2018 Korean Children and Youth Panel Survey (n = 1236) and the 2019 Korean Children and Youth Well-being Index Survey (n = 334). Higher levels of stress were observed in children during the COVID-19 pandemic; however, the level of their life satisfaction remained unchanged when compared with data from the pre-COVID-19 surveys. The pandemic also affected peer relationship quality and susceptibility to smartphone addiction, but not perceived parenting style nor academic engagement. Interestingly, peer relationship quality no longer predicted life satisfaction during the pandemic; perceived parenting styles and parent-child conversation time predicted life satisfaction. The results suggest a central role of parent-child relationship in supporting the psychological well-being of school-aged children during the pandemic.

Background Social media platforms provide an easily accessible and time-saving communication approach for individuals with mental disorders compared to face-to-face meetings with medical providers. Recently, machine learning (ML)-based mental health exploration using large-scale social media data has attracted significant attention. Objective We aimed to provide a bibliometric analysis and discussion on research trends of ML for mental health in social media. Methods Publications addressing social media and ML in the field of mental health were retrieved from the Scopus and Web of Science databases. We analyzed the publication distribution to measure productivity on sources, countries, institutions, authors, and research subjects, and visualized the trends in this field using a keyword co-occurrence network. The research methodologies of previous studies with high citations are also thoroughly described. Results We obtained a total of 565 relevant papers published from 2015 to 2020. In the last 5 years, the number of publications has demonstrated continuous growth with Lecture Notes in Computer Science and Journal of Medical Internet Research as the two most productive sources based on Scopus and Web of Science records. In addition, notable methodological approaches with data resources presented in high-ranking publications were investigated. Conclusions The results of this study highlight continuous growth in this research area. Moreover, we retrieved three main discussion points from a comprehensive overview of highly cited publications that provide new in-depth directions for both researchers and practitioners.