Transit communication via Twitter during the COVID-19 pandemic

Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021. We developed an analysis framework, using advanced machine learning and natural language processing models, to understand how agencies' tweeting patterns are associated with rider interaction outcomes during the pandemic. From the transit agency perspective, we find smaller agencies tend to generate a higher percentage of COVID-related tweets and some agencies are more repetitive than their peers. Six topics (i.e., face covering, essential service appreciation, free resources, social distancing, cleaning, and service updates) were identified in the COVID-related tweets. From the followers' interaction perspective, most agencies gained followers after the start of the pandemic (i.e., March 2020). The percentage of follower gains is positively correlated with the percentage of COVID-related tweets, tweets replying to followers, and tweets using outlinks. The average like counts per COVID-related tweet is positively correlated with the percentage of COVID-related tweets and negatively correlated with the percentage of tweets discussing social distancing and agency repetitiveness. This work can inform transportation planners and transit agencies on how to use Twitter to effectively communicate with riders to improve public perception of health and safety as it relates to transit ridership during delays and long-term disruptions such as those created by the COVID-19 public health crisis.

The role of cyclophilins in viral infection and the immune response.

Cyclophilins (Cyps) are a subgroup of peptidyl-prolyl cis-trans isomerases (PPIases) that contain a highly conserved domain of PPIases. Sixteen Cyps have been identified in humans, among which the functions of five classical Cyp subtypes (CypA, B, C, D, and 40) have been studied in more detail. Cyps are widely expressed in almost all human tissues and are involved in several intracellular signaling pathways such as oxidative stress, mitochondrial dysfunction, cell migration, and apoptosis. Several studies have also demonstrated that Cyps play an important role in the development of cardiovascular diseases, neurodegeneration, cancer, and other diseases. However, as regulators of intercellular communication, Cyps have increasingly attracted attention as a result of their implications in viral infection. The specific motifs of Cyps can be targeted by viral proteins and thus promote either a viral infection or an antiviral response. This review highlights the present understanding of Cyps in viral infection and immune response. These effects will facilitate revealing the molecular mechanisms of several diseases induced by viruses and may provide novel insight into the development of corresponding drug-based treatment methods.

Disinfectant dodecyl dimethyl benzyl ammonium chloride (DDBAC) disrupts gut microbiota, phospholipids, and calcium signaling in honeybees (Apis mellifera) at an environmentally relevant level.

One of the impacts of the Coronavirus disease 2019 (COVID-19) pandemic has been a profound increase in the application amounts of disinfectants. Dodecyl dimethyl benzyl ammonium chloride (DDBAC) is a widely used disinfectant, yet its hazards to non-target species remain largely unknown. We are unaware of any studies assessing DDBAC's impacts on honeybee, a pollinator species that is a useful indicator of environmental pollution essential for many forms of agricultural production. Here, we assessed the potentially negative effects of DDBAC on honeybees. After conducting a formal toxicity evaluation of DDBAC on honeybee mortality, we detected an accumulation of DDBAC in the honeybee midgut. We subsequently studied the midgut tissues of honeybees exposed to sub-lethal concentrations of DDBAC: histopathological examination revealed damage to midgut tissue upon DDBAC exposure, microbiome analysis showed a decreased abundance of beneficial midgut microbiota, lipidomics analysis revealed a significant reduction in cell membrane phospholipids with known functions in signal transduction, and a transcriptome analysis detected altered expression of genes involved in calcium signaling pathways (that variously function in calcium absorption, muscle contraction, and neurotransmission). Thus, our study establishes that DDBAC impacts honeybee midgut functions at multiple levels. Our study represents an early warning about the hazards of DDBAC and appeals for the proper stewardship of DDBAC to ensure the protection of our ecological environment.

COVID-19 and stock market performance: Evidence from the RCEP countries☆

As the world's largest trading bloc, the agreement of RCEP, which was formalized in September 2020, is believed to play a non-neglectable role in the post-pandemic recovery. Real economies and the capital markets of the participating countries will have greater interactions due to tariff reduction and negative lists. By looking into the shocks in early 2020 that affect the stock markets of RCEP participating countries, we measure the stock market reaction to common risks just before the RCEP agreement was formalized. Following return-based, volume-based and liquidity-based event-study approaches, we use daily data from 11 Asia-Pacific countries to examine the stock market reactions. We find that RCEP economies for which the agreement took effect on January 1st 2022 showed better risk resistance in response to COVID-19 shocks. In the long run, trading benefits brought by the RCEP agreement are expected to form and strengthen a system of circular flow of international trading activities among the participating countries, which will in turn increase the risk resistance ability of their stock markets.

Rational drug repositioning for coronavirus-associated diseases using directional mapping and side-effect inference.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of coronavirus disease 2019 (COVID-19), has infected hundreds of millions of people and caused millions of deaths. Looking for valid druggable targets with minimal side effects for the treatment of COVID-19 remains critical. After discovering host genes from multiscale omics data, we developed an end-to-end network method to investigate drug-host gene(s)-coronavirus (CoV) paths and the mechanism of action between the drug and the host factor in a directional network. We also inspected the potential side effect of the candidate drug on several common comorbidities. We established a catalog of host genes associated with three CoVs. Rule-based prioritization yielded 29 Food and Drug Administration (FDA)-approved drugs via accounting for the effects of drugs on CoVs, comorbidities, and drug-target confidence information. Seven drugs are currently undergoing clinical trials as COVID-19 treatment. This catalog of druggable host genes associated with CoVs and the prioritized repurposed drugs will provide a new sight in therapeutics discovery for severe COVID-19 patients.

Browsing for food: Will COVID‐induced online grocery delivery persist?

The COVID‐19 pandemic altered daily activities. Many consumers reverted to online grocery shopping and home delivery. We analyze factors associated with the decision to grocery shop online and whether this will persist post‐COVID using data collected via a representative online Qualtrics panel in the State of New Jersey (N = 1,419). Around half of respondents either decreased in‐person shopping, increased online shopping, or pursued a combination of both. We used factor analysis to decompose attitudes towards the pandemic, finding that attitudinal responses broke down into ‘fearful’, ‘believers’, and ‘deniers’. Binomial regressions were used to analyze patterns of frequency of grocery shopping during the pandemic and changes in behavior during the pandemic. Results suggest that age, gender, ethnicity, educational attainment, having children at home, and attitudes towards COVID‐19 are likely to influence frequency of online and in‐person grocery shopping. Specifically, being 50 years or older is negatively associated with online grocery shopping. Those who deny COVID‐19 were less likely to decrease in‐person grocery shopping. People who had children at home, who had advanced degrees, or who were of Hispanic origin were more likely to increase online shopping and decrease in‐person shopping during the pandemic. While our results suggest that in‐person grocery shopping will return to prepandemic levels, we found that respondents report some increased persistence in online grocery shopping post‐COVID.

Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review.

Over the past decade, artificial intelligence (AI) and machine learning (ML) have become the breakthrough technology most anticipated to have a transformative effect on pharmaceutical research and development (R&D). This is partially driven by revolutionary advances in computational technology and the parallel dissipation of previous constraints to the collection/processing of large volumes of data. Meanwhile, the cost of bringing new drugs to market and to patients has become prohibitively expensive. Recognizing these headwinds, AI/ML techniques are appealing to the pharmaceutical industry due to their automated nature, predictive capabilities, and the consequent expected increase in efficiency. ML approaches have been used in drug discovery over the past 15-20 years with increasing sophistication. The most recent aspect of drug development where positive disruption from AI/ML is starting to occur, is in clinical trial design, conduct, and analysis. The COVID-19 pandemic may further accelerate utilization of AI/ML in clinical trials due to an increased reliance on digital technology in clinical trial conduct. As we move towards a world where there is a growing integration of AI/ML into R&D, it is critical to get past the related buzz-words and noise. It is equally important to recognize that the scientific method is not obsolete when making inferences about data. Doing so will help in separating hope from hype and lead to informed decision-making on the optimal use of AI/ML in drug development. This manuscript aims to demystify key concepts, present use-cases and finally offer insights and a balanced view on the optimal use of AI/ML methods in R&D.

SARS-CoV-2 3C-like protease antagonizes interferon-beta production by facilitating the degradation of IRF3.

The prevalence of SARS-CoV-2 is a great threat to global public health. However, the relationship between the viral pathogen SARS-CoV-2 and host innate immunity has not yet been well studied. The genome of SARS-CoV-2 encodes a viral protease called 3C-like protease. This protease is responsible for cleaving viral polyproteins during replication. In this investigation, 293T cells were transfected with SARS-CoV-2 3CL and then infected with Sendai virus (SeV) to induce the RIG-I like receptor (RLR)-based immune pathway. q-PCR, luciferase reporter assays, and western blotting were used for experimental analyses. We found that SARS-CoV-2 3CL significantly downregulated IFN-ß mRNA levels. Upon SeV infection, SARS-CoV-2 3CL inhibited the nuclear translocation of IRF3 and p65 and promoted the degradation of IRF3. This effect of SARS-CoV-2 3CL on type I IFN in the RLR immune pathway opens up novel ideas for future research on SARS-CoV-2.

Characterization of the SARS-CoV-2 E Protein: Sequence, Structure, Viroporin, and Inhibitors.

The COVID-19 epidemic is one of the most influential epidemics in history. Understanding the impact of coronaviruses (CoVs) on host cells is very important for disease treatment. The SARS-CoV-2 envelope (E) protein is a small structural protein involved in many aspects of the viral life cycle. The E protein promotes the packaging and reproduction of the virus, and deletion of this protein weakens or even abolishes the virulence. This review aims to establish new knowledge by combining recent advances in the study of the SARS-CoV-2 E protein and by comparing it with the SARS-CoV E protein. The E protein amino acid sequence, structure, self-assembly characteristics, viroporin mechanisms and inhibitors are summarized and analyzed herein. Although the mechanisms of the SARS-CoV-2 and SARS-CoV E proteins are similar in many respects, specific studies on the SARS-CoV-2 E protein, for both monomers and oligomers, are still lacking. A comprehensive understanding of this protein should prompt further studies on the design and characterization of effective targeted therapeutic measures.

Computational Study of the Ion and Water Permeation and Transport Mechanisms of the SARS-CoV-2 Pentameric E Protein Channel.

Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus (SARS-CoV-2) and represents the causative agent of a potentially fatal disease that is a public health emergency of international concern. Coronaviruses, including SARS-CoV-2, encode an envelope (E) protein, which is a small, hydrophobic membrane protein; the E protein of SARS-CoV-2 shares a high level of homology with severe acute respiratory syndrome coronavirus (SARS-CoV). In this study, we provide insights into the function of the SARS-CoV-2 E protein channel and the ion and water permeation mechanisms using a combination of in silico methods. Based on our results, the pentameric E protein promotes the penetration of cation ions through the channel. An analysis of the potential mean force (PMF), pore radius and diffusion coefficient reveals that Leu10 and Phe19 are the hydrophobic gates of the channel. In addition, the pore exhibits a clear wetting/dewetting transition with cation selectivity under transmembrane voltage, indicating that it is a hydrophobic voltage-dependent channel. Overall, these results provide structure-based insights and molecular dynamic information that are needed to understand the regulatory mechanisms of ion permeability in the pentameric SARS-CoV-2 E protein channel.

Mental distress and influencing factors in nurses caring for patients with COVID-19.

BACKGROUND: Nurses are experiencing tremendous stress during the new coronavirus disease 2019 (COVID-19) pandemic, especially intensive care nurses. The pandemic of the disease is a tragedy, which may leave a catastrophic psychological imprint on nurses. Understanding nurses' mental distress can help when implementing interventions to mitigate psychological injuries to nurses. AIMS AND OBJECTIVES: To quantify the severity of nurses' post-traumatic stress disorder (PTSD) symptoms and stress and explore the influencing factors of their psychological health when caring for patients with COVID-19. DESIGN: A cross-sectional survey. METHODS: The PTSD Checklist-Civilian and the Perceived Stress Scale were administered from 11 to 18 March 2020, to 90 nurses selected from another city to go and help an intensive care unit (ICU) in Wuhan, China. These nurses were selected because of their high levels of clinical performance and resilience status. RESULTS: Nurses' average PTSD score was 24.62 ± 6.68, and five (5.6%) of the nurses reported a clinically significant level of PTSD symptoms (>38 points). Nurses' perceived stress averaged 19.33 ± 7, and 20 nurses (22.22%) scored positively >25 points. Nurses' stress and PTSD symptoms were positively correlated (P < .01). Major stress sources included working in an isolated environment, concerns about personal protective equipment shortage and usage, physical and emotional exhaustion, intensive workload, fear of being infected, and insufficient work experiences with COVID-19. CONCLUSIONS: This study showed that even relatively highly resilient nurses experienced some degree of mental distress, including PTSD symptoms and perceived stress. Our findings highlight the importance of helping nurses cultivate resilience and reduce stress. RELEVANCE TO CLINICAL PRACTICE: Recommendations for practice include providing adequate training and orientation before assigning nurses to ICU to help, offering disaster-emergency-preparedness training to keep nurses prepared, providing caring and authentic nursing leadership, offering ongoing psychological support to frontline nurses.