Dynamics of social media behavior before and after SARS-CoV-2 infection.

Introduction: Online social media have been both a field of research and a source of data for research since the beginning of the COVID-19 pandemic. In this study, we aimed to determine how and whether the content of tweets by Twitter users reporting SARS-CoV-2 infections changed over time. Methods: We built a regular expression to detect users reporting being infected, and we applied several Natural Language Processing methods to assess the emotions, topics, and self-reports of symptoms present in the timelines of the users. Results: Twelve thousand one hundred and twenty-one twitter users matched the regular expression and were considered in the study. We found that the proportions of health-related, symptom-containing, and emotionally non-neutral tweets increased after users had reported their SARS-CoV-2 infection on Twitter. Our results also show that the number of weeks accounting for the increased proportion of symptoms was consistent with the duration of the symptoms in clinically confirmed COVID-19 cases. Furthermore, we observed a high temporal correlation between self-reports of SARS-CoV-2 infection and officially reported cases of the disease in the largest English-speaking countries. Discussion: This study confirms that automated methods can be used to find digital users publicly sharing information about their health status on social media, and that the associated data analysis may supplement clinical assessments made in the early phases of the spread of emerging diseases. Such automated methods may prove particularly useful for newly emerging health conditions that are not rapidly captured in the traditional health systems, such as the long term sequalae of SARS-CoV-2 infections.

Visible-Light-Driven Water Oxidation on Self-Assembled Metal-Free Organic@Carbon Junctions at Neutral pH.

Sustainable water oxidation requires low-cost, stable, and efficient redox couples, photosensitizers, and catalysts. Here, we introduce the in situ self-assembly of metal-atom-free organic-based semiconductive structures on the surface of carbon supports. The resulting TTF/TTF•+@carbon junction (TTF = tetrathiafulvalene) acts as an all-in-one highly stable redox-shuttle/photosensitizer/molecular-catalyst triad for the visible-light-driven water oxidation reaction (WOR) at neutral pH, eliminating the need for metallic or organometallic catalysts and sacrificial electron acceptors. A water/butyronitrile emulsion was used to physically separate the photoproducts of the WOR, H+ and TTF, allowing the extraction and subsequent reduction of protons in water, and the in situ electrochemical oxidation of TTF to TTF•+ on carbon in butyronitrile by constant anode potential electrolysis. During 100 h, no decomposition of TTF was observed and O2 was generated from the emulsion while H2 was constantly produced in the aqueous phase. This work opens new perspectives for a new generation of metal-atom-free, low-cost, redox-driven water-splitting strategies.