Background It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies involving public response monitoring. Objective The objective of this study is to examine COVID-19–related discussions, concerns, and sentiments using tweets posted by Twitter users. Methods We analyzed 4 million Twitter messages related to the COVID-19 pandemic using a list of 20 hashtags (eg, “coronavirus,” “COVID-19,” “quarantine”) from March 7 to April 21, 2020. We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. Results Popular unigrams included “virus,” “lockdown,” and “quarantine.” Popular bigrams included “COVID-19,” “stay home,” “corona virus,” “social distancing,” and “new cases.” We identified 13 discussion topics and categorized them into 5 different themes: (1) public health measures to slow the spread of COVID-19, (2) social stigma associated with COVID-19, (3) COVID-19 news, cases, and deaths, (4) COVID-19 in the United States, and (5) COVID-19 in the rest of the world. Across all identified topics, the dominant sentiments for the spread of COVID-19 were anticipation that measures can be taken, followed by mixed feelings of trust, anger, and fear related to different topics. The public tweets revealed a significant feeling of fear when people discussed new COVID-19 cases and deaths compared to other topics. Conclusions This study showed that Twitter data and machine learning approaches can be leveraged for an infodemiology study, enabling research into evolving public discussions and sentiments during the COVID-19 pandemic. As the situation rapidly evolves, several topics are consistently dominant on Twitter, such as confirmed cases and death rates, preventive measures, health authorities and government policies, COVID-19 stigma, and negative psychological reactions (eg, fear). Real-time monitoring and assessment of Twitter discussions and concerns could provide useful data for public health emergency responses and planning. Pandemic-related fear, stigma, and mental health concerns are already evident and may continue to influence public trust when a second wave of COVID-19 occurs or there is a new surge of the current pandemic.

Background Family violence (including intimate partner violence/domestic violence, child abuse, and elder abuse) is a hidden pandemic happening alongside COVID-19. The rates of family violence are rising fast, and women and children are disproportionately affected and vulnerable during this time. Objective This study aims to provide a large-scale analysis of public discourse on family violence and the COVID-19 pandemic on Twitter. Methods We analyzed over 1 million tweets related to family violence and COVID-19 from April 12 to July 16, 2020. We used the machine learning approach Latent Dirichlet Allocation and identified salient themes, topics, and representative tweets. Results We extracted 9 themes from 1,015,874 tweets on family violence and the COVID-19 pandemic: (1) increased vulnerability: COVID-19 and family violence (eg, rising rates, increases in hotline calls, homicide); (2) types of family violence (eg, child abuse, domestic violence, sexual abuse); (3) forms of family violence (eg, physical aggression, coercive control); (4) risk factors linked to family violence (eg, alcohol abuse, financial constraints, guns, quarantine); (5) victims of family violence (eg, the LGBTQ [lesbian, gay, bisexual, transgender, and queer or questioning] community, women, women of color, children); (6) social services for family violence (eg, hotlines, social workers, confidential services, shelters, funding); (7) law enforcement response (eg, 911 calls, police arrest, protective orders, abuse reports); (8) social movements and awareness (eg, support victims, raise awareness); and (9) domestic violence–related news (eg, Tara Reade, Melissa DeRosa). Conclusions This study overcomes limitations in the existing scholarship where data on the consequences of COVID-19 on family violence are lacking. We contribute to understanding family violence during the pandemic by providing surveillance via tweets. This is essential for identifying potentially useful policy programs that can offer targeted support for victims and survivors as we prepare for future outbreaks.

Semiconductor photocatalysis is currently attracting tremendous attention as it holds great potential to address the issues of energy shortage and environmental pollution. 2D materials are excellent candidates for photocatalysis owing to their attractive structural and electronic properties. However, practical applications of 2D materials are still hindered due to limitations, such as fast electron–hole recombination and poor redox ability, both of which lead to low efficiency of photocatalytic reactions. Constructing a heterojunction is the most widely used strategy to solve these problems. In particular, heterojunctions composed of 2D materials interfaced with other semiconductors of different dimensionalities can integrate the respective advantages and mitigate the drawbacks of each component. Hence, this review focuses on the recent developments in the rational design of 2D material‐based heterojunction photocatalysts with different configurations. The synthetic strategies, physicochemical properties, component functions, photocatalytic mechanisms, and applications of these heterojunctions are systematically summarized. Emphasis is placed on correlations between photocatalytic performance and heterojunction configuration. Finally, the ongoing challenges and potential directions for future development of 2D material‐based heterojunction photocatalysts are also proposed.

ABSTRACT. The herpes simplex virus 2 (HSV-2) is one of the most important sexually transmitted pathogens, and can facilitate the spread of human immunodeficiency virus. The currently available antiviral drugs have certain limitations. Nanosilver has received increasing attention recently with respect to its antibacterial and antiviral properties. The purpose of this study was to determine the inhibiting effect and mechanism of silver nanoparticles (Ag-NPs) on HSV-2. The cytotoxicity of Vero cells induced by different Ag-NP concentrations was investigated by using the methyl thiazolyl tetrazolium (MTT) assay. The inhibiting effect of Ag-NPs on HSV-2 at various times was also evaluated by using a plaque assay. The toxicity of 100 μg/mL Ag-NPs on Vero cells was very low. The mixture of Ag-NP suspension and HSV-2 prior to infecting cells could significantly inhibit the production of progeny viruses. AgNPs also inhibited the replication of HSV-2 for 24 h before infecting cells with HSV-2. Therefore, 100 μg/mL Ag-NPs could completely inhibit HSV-2 replication. Ag-NPs at nontoxic concentrations were capable of inhibiting HSV-2 replication when administered prior to viral infection or soon after initial virus exposure. This suggests 7023 Inhibition effect of silver nanoparticles on HSV-2 ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 13 (3): 7022-7028 (2014) that the mode of action of Ag-Nps occurs during the early phases of viral replication.

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