Study on Microbial Diversity of Clothing in Maternal and Infant Population (preprint)

With the improvement of Chinese people's living standards, the maintenance of infants and young children is becoming more and more sophisticated. Coupled with the impact of the COVID-19 epidemic in the past few years, mother-to-child families have paid unprecedented attention and expectations to household appliances with sterilization and disinfection functions. In addition to washing machines as household clothing care equipment, clothing care machines with further sterilization, drying, and disinfection functions for infant and young children's clothing are gradually entering households, especially in southern China during the rainy season. In order to thoroughly solve the problem of sterilization of clothing from the source, the distribution of microbial contamination of clothing should be fully investigated. At present, there are few systematic studies on microbial community structure in clothing in China. Therefore, the purpose of this study is to analyze the microbial community structure in Chinese maternal and infant household clothing and explore the key factors affecting the microbial community structure of clothing. A plate culture method and a high-throughput sequencing technology are utilized to comprehensively analyze the community structure of the microorganism in the clothes of the mother and infant. The Chao and Shannon index were used as indicators to explore the key factors affecting the microbial community structure of clothing by one-way analysis of variance. In this study, 149 strains of microorganisms were isolated from 24 clothing samples of mothers and infants, including 102 strains of bacteria, covering 16 genera. The bacteria with higher isolation frequency and wider distribution were Staphylococcus and Micrococcus, Moraxella; 47 strains of fungi covering 24 genera were isolated and the fungi with higher isolation frequency and wider distribution were Cladosporium, Alteraria, Rhodotorula. At present, the sterilization technology of clothing care machine has not been fully investigated in combination with the distribution of clothing microorganisms. Based on the specific distribution of microorganisms in clothing and the types of microorganisms contained, clothing care machines can provide more targeted sterilization treatment for clothing. This study will help to thoroughly address the sterilization and disinfection of microorganisms in clothing from the source.

Factors associated with anxiety and depression in patients with erectile dysfunction: a cross-sectional study.

BACKGROUND: Few studies have investigated factors associated with anxiety and depression among patients with erectile dysfunction (ED). This study aimed to investigate associated factors and the prevalence of anxiety and depression in this special group in China. METHODS: Data from 511 patients with ED aged 18-60 years were collected between July 2021 and April 2022. The 5-item International Index of Erectile Function (IIEF-5) questionnaire, self-rating anxiety scale (SAS) and self-rating depression scale (SDS) were used to evaluate erectile function, anxiety and depression, respectively. Univariate analysis and multivariate linear regression analyses were used to explore the associated factors of depression and anxiety. RESULTS: The prevalence of anxiety and depression among ED patients was 38.16% and 64.97%, respectively. The mean anxiety index score was 47.37 ± 6.69 points, and the mean depression index was 54.72 ± 9.10 points. Multiple linear regression analysis showed that worse ED, low education level, and smoking were positively associated with increased risk of anxiety and depression. In addition, younger age, longer onset time, and irregular sleep were positively associated with high risk of anxiety, and irregular exercise was associated with severe depression. CONCLUSIONS: The prevalence of depression and anxiety in ED patients is high, and the severity of ED, age, education level, smoking, onset time, regular sleep, and exercise were associated with anxiety or depression. Reversible risk factors should be avoided and individualized psychological support services are necessary for ED patients.

SARS-CoV-2 NSP8 suppresses type I and III IFN responses by modulating the RIG-I/MDA5, TRIF, and STING signaling pathways.

SARS-CoV-2 has developed a variety of approaches to counteract host innate antiviral immunity to facilitate its infection, replication and pathogenesis, but the molecular mechanisms that it employs are still not been fully understood. Here, we found that SARS-CoV-2 NSP8 inhibited the production of type I and III interferons (IFNs) by acting on RIG-I/MDA5 and the signaling molecules TRIF and STING. Overexpression of NSP8 downregulated the expression of type I and III IFNs stimulated by poly (I:C) transfection and infection with SeV and SARS-CoV-2. In addition, NSP8 impaired IFN expression triggered by overexpression of the signaling molecules RIG-I, MDA5, and MAVS, instead of TBK1 and IRF3-5D, an active form of IRF3. From a mechanistic view, NSP8 interacts with RIG-I and MDA5, and thereby prevents the assembly of the RIG-I/MDA5-MAVS signalosome, resulting in the impaired phosphorylation and nuclear translocation of IRF3. NSP8 also suppressed the TRIF- and STING- induced IFN expression by directly interacting with them. Moreover, ectopic expression of NSP8 promoted virus replications. Taken together, SARS-CoV-2 NSP8 suppresses type I and III IFN responses by disturbing the RIG-I/MDA5-MAVS complex formation and targeting TRIF and STING signaling transduction. These results provide new insights into the pathogenesis of COVID-19.

A lightweight network for COVID-19 detection in X-ray images.

The Novel Coronavirus 2019 (COVID-19) is a global pandemic which has a devastating impact. Due to its quick transmission, a prominent challenge in confronting this pandemic is the rapid diagnosis. Currently, the commonly-used diagnosis is the specific molecular tests aided with the medical imaging modalities such as chest X-ray (CXR). However, with the large demand, the diagnoses of CXR are time-consuming and laborious. Deep learning is promising for automatically diagnosing COVID-19 to ease the burden on medical systems. At present, the most applied neural networks are large, which hardly satisfy the rapid yet inexpensive requirements of COVID-19 detection. To reduce huge computation and memory demands, in this paper, we focus on implementing lightweight networks for COVID-19 detection in CXR. Concretely, we first augment data based on clinical visual features of CXR from expertise. Then, according to the fact that all the input data are CXR, we design a targeted four-layer network with either 11×11 or 3×3 kernels to recognize regional features and detail features. A pruning criterion based on the weights importance is also proposed to further prune the network. Experiments on a public COVID-19 dataset validate the effectiveness and efficiency of the proposed method.

Geospatial Modeling of Health, Socioeconomic, Demographic, and Environmental Factors with COVID-19 Incidence Rate in Arkansas, US

The COVID-19 pandemic has posed numerous challenges to human society. Previous studies explored multiple factors in virus transmission. Yet, their impacts on COVID-19 are not universal and vary across geographical regions. In this study, we thoroughly quantified the spatiotemporal associations of 49 health, socioeconomic, demographic, and environmental factors with COVID-19 at the county level in Arkansas, US. To identify the associations, we applied the ordinary least squares (OLS) linear regression, spatial lag model (SLM), spatial error model (SEM), and multiscale geographically weighted regression (MGWR) model. To reveal how such associations change across different COVID-19 times, we conducted the analyses for each season (i.e., spring, summer, fall, and winter) from 2020 to 2021. We demonstrate that there are different driving factors along with different COVID-19 variants, and their magnitudes change spatiotemporally. However, our results identify that adult obesity has a positive association with the COVID-19 incidence rate over entire Arkansas, thus confirming that people with obesity are vulnerable to COVID-19. Humidity consistently negatively affects COVID-19 across all seasons, denoting that increasing humidity could reduce the risk of COVID-19 infection. In addition, diabetes shows roles in the spread of both early COVID-19 variants and Delta, while humidity plays roles in the spread of Delta and Omicron. Our study highlights the complexity of how multifactor affect COVID-19 in different seasons and counties in Arkansas. These findings are useful for informing local health planning (e.g., vaccine rollout, mask regulation, and testing/tracing) for the residents in Arkansas.

A lightweight network for COVID-19 detection in X-ray images

The Novel Coronavirus 2019 (COVID-19) is a global pandemic which has a devastating impact. Due to its quick transmission, a prominent challenge in confronting this pandemic is the rapid diagnosis. Currently, the commonly-used diagnosis is the specific molecular tests aided with the medical imaging modalities such as chest X-ray (CXR). However, with the large demand, the diagnoses of CXR are time-consuming and laborious. Deep learning is promising for automatically diagnosing COVID-19 to ease the burden on medical systems. At present, the most applied neural networks are large, which hardly satisfy the rapid yet inexpensive requirements of COVID-19 detection. To reduce huge computation and memory demands, in this paper, we focus on implementing lightweight networks for COVID-19 detection in CXR. Concretely, we first augment data based on clinical visual features of CXR from expertise. Then, according to the fact that all the input data are CXR, we design a targeted four-layer network with either 11

Computed tomography-aided diagnosis of COVID-19

Coronavirus disease (COVID-19) is highly infectious, has spread worldwide, and has a relatively high mortality rate. Early diagnosis and timely isolation are essential to control the spread of COVID-19. Computed tomography (CT) is considered to be an effective tool for the rapid diagnosis of COVID-19 and plays a key role in diagnosis, clinical course monitoring, and the evaluation of treatment outcomes. Artificial intelligence (AI) has emerged as a useful technology for early diagnosis, lesion quantification, and prognosis evaluation in patients with COVID-19. In this review, we discuss the role of CT in the diagnosis of COVID-19, typical CT manifestations of COVID-19 throughout the disease course, differential diagnoses, and the application of AI as a diagnostic and therapeutic tool in this patient population.

Impact of Isolation measures on pregnancy outcome during the COVID-19 pandemic.

This study aims to explore the impact of isolation measures implemented during the COVID-19 pandemic on childbirth outcomes in pregnant women. The design was a retrospective cohort study. The pregnant women during the outbreak lockdown and isolation from February 1 to April 30, 2020, were defined as the exposed population, and the pregnant women in the same time frame in 2019 as the non-exposed population. All data for the study were obtained from the National Health Care Data Platform of Shandong University. Generalized linear regression models were used to analyze the differences in pregnancy outcomes between the two study groups. A total of 34,698 pregnant women from Shandong Province, China in the data platform met the criteria and were included in the study. The proportions were 11.53% and 8.93% for macrosomia in the exposed and the non-exposed groups and were 3.47% and 4.37% for low birth weight infants, respectively, which were significantly different. They were 22.55% and 25.94% attributed to average exposed effect for macrosomia and low birth weight infants. Meanwhile, the mean weight and standard deviation of full-term infants in the exposure group were 3414.80 ± 507.43 g, which were significantly higher than in the non-exposed group (3347.22 ± 502.57 g, P < 0.001). The effect of exposure was significant in the third trimester. In conclusion, the isolation during the COVID-19 pandemic increases the birth weight of infants and the probability of macrosomia, regardless of which trimester in isolation a pregnant woman was, while the third trimester is the sensitive window of exposure. Our findings provide a basis for health care and policy development during pregnancy in COVID-19, due to COVID-19 still showing a pandemic trend around the world in 2022.

A nationwide survey on the management of the COVID-19 pandemic and respiratory disease in South Korea.

Background: This study aimed to explore individual prevalence of respiratory symptoms and to describe the Korean population's treatment approaches, preventive health behaviors, and mental health conditions during the pandemic. Methods: We analyzed responses from an online nationwide survey, conducted between February 2021 to May 2021, about people's experiences during the pandemic. Statistical analysis was also performed to see if there were any significant differences in treatment and prevention strategies between different groups of respondents (between those had respiratory symptoms, compared with those who did not, and between those tested positive for COVID-19, compared with those who did not). Results: A total of 2,177 survey respondents completed the survey and, of these, only 142 had experienced symptoms. The most frequently reported respiratory infections related symptoms were runny or blocked nose (47.6%), cough (45.5%), fever (44.1%), sore throat (42.0%), and fatigue (30.1%). More than half of the respondents (53.1%) used complementary and alternative medicine (CAM) approaches as means of preventive measures. In terms of preventive behaviors, the more emphasized behaviors were mask-wearing (58.9%) and hand-washing after coming home (42.7%). The majority of the respondents (64.9%) did not show signs of mental health issues. Conclusion: In South Korea, conventional medicine was mainly used for COVID-19 treatment whereas CAM was commonly used as preventive measures. COVID-19 was also found to have less impact on the general population's mental health. The findings of this study may shed light on how the pandemic impacted the general population.

Investigation of Mental Health Literacy and Status of Residents During the Re-Outbreak of COVID-19 in China

Introduction The current field of research on the impact of COVID-19 on mental health was mostly limited to the evaluation of the first round of the epidemic, few reports focused on the impact of the re-emergence of COVID-19. This study aimed to investigate the mental health literacy and status of residents during the re-outbreak of COVID-19 in China. Methods The basic information sheet, health literacy survey scale, physical health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7), insomnia severity index (ISI), and Alzheimer dementia 8 (AD8) were applied to evaluate the mental health literacy, mental health status and elderly cognitive function, and χ2 test was applied for analysis of the difference between different groups. Results A total of 2,306 participants were involved in this study, of which 734 people completed the mental health literacy survey. The qualified rate of mental health literacy was 6.4%. The difference is statistically significant. A total of 1,015 people completed the survey of mental health status, the prevalence of depressive symptoms was 8.87%, the monthly income of different families (χ2 = 13.96, P = 0.01), the self-assessed health status (χ2 = 128.56, P < 0.05), the presence or absence of chronic diseases (χ2 = 4.78, P = 0.03), among all which the difference was statistically significant;the prevalence of anxiety symptoms was 3.84%, different regions (χ2 = 12.26, P < 0.05), occupations (χ2 = 11.65, P < 0.05), household monthly income (χ2 = 12.65, P = 0.01), self-rated health status (χ2 = 151.11, P < 0.05), and chronic diseases (χ2 = 7.77, P = 0.01), among all which the differences were statistically significant. The prevalence of insomnia symptoms was 7.98%, different age (χ2 = 18.45, P < 0.05), region (χ2 = 5.11, P = 0.02), monthly household income (χ2 = 12.68 P = 0.01), and self-assessed health status (χ2 = 91.71, P < 0.05), in which there was a statistically significant difference between those with or without chronic diseases (χ2 = 3 3.25, P < 0.05). A total of 557 elderly people over 65 years old completed the cognitive dysfunction screening, in which the prevalence of cognitive dysfunction was 17.41%, and the difference was statistically significant at the different self-assessed health status (χ2 = 96.24, P < 0.05) and with or without chronic diseases (χ2 = 107.09, P < 0.05). Conclusion The mental health literacy and status of residents have not improved significantly during the second outbreak of the epidemic, indicating that under the normalization of epidemic prevention and control, more attention should be paid to the mental health of residents, and targeted health education and psychological intervention should be carried out to avoid relative adverse events.

Herbal Medicine Intervention for the Treatment of COVID-19: A Living Systematic Review and Cumulative Meta-Analysis.

Background: Integrative herbal medicine has been reported to have beneficial effects in the treatment of coronavirus disease 2019 (COVID-19). Aim: To compile up-to-date evidence of the benefits and risks of herbal medicine for the treatment of COVID-19 symptoms. Methods: Eleven databases, including PubMed, Cochrane Register of Controlled Trials (CENTRAL), Embase, Allied and Complementary Medicine Database (AMED), Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Database, and Chinese Science and Technique Journals Database (VIP), Research Information Service System (RISS), Korean Medical database (KMBase), Korean Association of Medical Journal database (KoreaMed), and OASIS database, were searched from 15 June, 2020, until 28 March 2022. Randomized controlled trials (RCTs), published in any language, reporting the efficacy and safety outcomes of herbal medicine in patients of all ages with a PCR-confirmed diagnosis of COVID-19 were included in this analysis. Data extraction and quality assessments were performed independently. Results: Random-effects meta-analyses showed evidence of favorable effects of treatment with herbal medicine when added to standard treatment, versus standard treatment alone, on the total effective rate (p = 0.0001), time to remission from fever (p < 0.00001), rate of remission from coughing (p < 0.0001), fatigue (p = 0.02), sputum production (p = 0.004), improvement of manifestations observed on chest computed tomography scans (p < 0.00001), incidence of progression to severe COVID-19 (p = 0.003), all-cause mortality (p = 0.003), time to a negative COVID-19 coronavirus test (p < 0.0001), and duration of hospital stay (p = 0.0003). There was no evidence of a difference between herbal medicine added to standard treatment, versus standard treatment alone, on the rate of remission from symptoms such as a fever, sore throat, nasal congestion and discharge, diarrhea, dry throat, chills, and the rate of conversion to a negative COVID-19 coronavirus test. Meta-analysis showed no evidence of a significant difference in adverse events between the two groups. There was an unclear risk of bias across the RCTs included in this analysis, indicating that most studies had methodological limitations. Conclusion: Current evidence suggests that herbal medicine added to standard treatment has potential benefits in the treatment of COVID-19 symptoms but the certainty of evidence was low.

SARS-CoV-2 ORF10 antagonizes STING-dependent interferon activation and autophagy.

A characteristic feature of COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, is the dysregulated immune response with impaired type I and III interferon (IFN) expression and an overwhelming inflammatory cytokine storm. RIG-I-like receptors (RLRs) and cGAS-STING signaling pathways are responsible for sensing viral infection and inducing IFN production to combat invading viruses. Multiple proteins of SARS-CoV-2 have been reported to modulate the RLR signaling pathways to achieve immune evasion. Although SARS-CoV-2 infection also activates the cGAS-STING signaling by stimulating micronuclei formation during the process of syncytia, whether SARS-CoV-2 modulates the cGAS-STING pathway requires further investigation. Here, we screened 29 SARS-CoV-2-encoded viral proteins to explore the viral proteins that affect the cGAS-STING signaling pathway and found that SARS-CoV-2 open reading frame 10 (ORF10) targets STING to antagonize IFN activation. Overexpression of ORF10 inhibits cGAS-STING-induced interferon regulatory factor 3 phosphorylation, translocation, and subsequent IFN induction. Mechanistically, ORF10 interacts with STING, attenuates the STING-TBK1 association, and impairs STING oligomerization and aggregation and STING-mediated autophagy; ORF10 also prevents the endoplasmic reticulum (ER)-to-Golgi trafficking of STING by anchoring STING in the ER. Taken together, these findings suggest that SARS-CoV-2 ORF10 impairs the cGAS-STING signaling by blocking the translocation of STING and the interaction between STING and TBK1 to antagonize innate antiviral immunity.

AdaGT: An Adaptive Group Testing Method for Improving Efficiency and Sensitivity of Large-Scale Screening Against COVID-19

The ongoing coronavirus disease 2019 (COVID-19) is a pandemic causing millions of deaths, devastating social and economic disruptions. Testing individuals for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of COVID-19, is critical for mitigating and containing COVID-19. Many countries are implementing group testing strategies against COVID-19 to improve testing capacity and efficiency while saving required workloads and consumables. A group of individuals’ nasopharyngeal/oropharyngeal (NP/OP) swab samples is mixed to conduct one test. However, existing group testing methods neglect the fact that mixing samples usually leads to substantial dilution of viral ribonucleic acid (RNA) of SARS-CoV-2, which seriously impacts the sensitivity of tests. In this paper, we aim to screen individuals infected with COVID-19 with as few tests as possible, under the premise that the sensitivity of tests is high enough. To achieve this goal, we propose an Adaptive Group Testing (AdaGT) method. By collecting information on the number of positive and negative samples that have been identified during the screening process, the AdaGT method can estimate the ratio of positive samples in real-time. Based on this ratio, the AdaGT algorithm adjusts its testing strategy adaptively between an individual testing strategy and a group testing strategy. The group size of the group testing strategy is carefully selected to guarantee that the sensitivity of each test is higher than a predetermined threshold and that this group contains at most one positive sample on average. Theoretical performance analysis on the AdaGT algorithm is provided and then validated in experiments. Experimental results also show that the AdaGT algorithm outperforms existing methods in terms of efficiency and sensitivity. Note to Practitioners—Real-time reverse transcription-polymerase chain reaction (rRT-PCR) tests provide scope for automation and are one of the most widely used laboratory methods for detecting the SARS-CoV-2 virus. This paper is motivated by the following challenges: (1) Many countries are experiencing an acute shortage of professionals and consumables for conducting rRT-PCR tests;(2) Group sizes of existing group testing methods against COVID-19 may not be optimal, which adversely impacts the efficiency of the screening of the SARS-CoV-2 virus;(3) Existing group testing methods do not consider the fact that the sensitivity of rRT-PCR tests usually decreases with the group size. The objective of this paper is to improve the efficiency and sensitivity of large-scale screening against COVID-19. For achieving this goal, we propose an Adaptive Group Testing (AdaGT) algorithm, which has the following advantages: (1) It can improve the efficiency for screening the SARS-CoV-2 virus, mainly by adaptively adjusting its testing strategy between an individual testing strategy and a group testing strategy based upon an estimated ratio of positive samples during the screening process;(2) It can guarantee a high sensitivity of the rRT-PCR tests by determining the group sizes of the group testing strategy based upon some constraints;(3) We derive an appropriate threshold for the estimated ratio of positive samples such that the AdaGT algorithm can achieve a minimum average number of rRT-PCR tests and can be directly employed in practical applications. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Exploring the Mediating Effect of Physical Activities on Built Environment and Obesity for Elderly People: Evidence From Shanghai, China.

There is still a scarcity of literature on the specific mechanisms of the linkage between the built environment and obesity. As a result, this study investigated whether and how physical activities mediate the associations between the objective built environment and the BMI of elderly people. To investigate the effect of the duration and intensity of physical activity on the effect of the built environment, the study made use of the bootstrap method. In general, we discovered that physical activity duration has a huge mediating effect on the elderly people in Shanghai, especially with respect to the density and accessibility of facilities (gyms, parks, fast-food restaurants) that can greatly stimulate physical activity in elderly people to reduce their BMI. There were both direct and indirect effects on their BMI, which means that the health benefits of green spaces for older people may be more complicated than first thought.

SARS-CoV-2 NSP5 and N protein counteract the RIG-I signaling pathway by suppressing the formation of stress granules

As a highly pathogenic human coronavirus, SARS-CoV-2 has to counteract an intricate network of antiviral host responses to establish infection and spread. The nucleic acid-induced stress response is an essential component of antiviral defense and is closely related to antiviral innate immunity. However, whether SARS-CoV-2 regulates the stress response pathway to achieve immune evasion remains elusive. In this study, SARS-CoV-2 NSP5 and N protein were found to attenuate antiviral stress granule (avSG) formation. Moreover, NSP5 and N suppressed IFN expression induced by infection of Sendai virus or transfection of a synthetic mimic of dsRNA, poly (I:C), inhibiting TBK1 and IRF3 phosphorylation, and restraining the nuclear translocalization of IRF3. Furthermore, HEK293T cells with ectopic expression of NSP5 or N protein were less resistant to vesicular stomatitis virus infection. Mechanistically, NSP5 suppressed avSG formation and disrupted RIG-I–MAVS complex to attenuate the RIG-I–mediated antiviral immunity. In contrast to the multiple targets of NSP5, the N protein specifically targeted cofactors upstream of RIG-I. The N protein interacted with G3BP1 to prevent avSG formation and to keep the cofactors G3BP1 and PACT from activating RIG-I. Additionally, the N protein also affected the recognition of dsRNA by RIG-I. This study revealed the intimate correlation between SARS-CoV-2, the stress response, and innate antiviral immunity, shedding light on the pathogenic mechanism of COVID-19.

Assessing the Impacts of Human Activities on Air Quality during the COVID-19 Pandemic through Case Analysis

COVID-19 is the latest of many pandemic affecting the world in the past few decades, and it has had a significant impact on the global environment. Some research has analysed the effects of the pandemic on air quality;however, very few studies have employed relationship analytics. In order to analyse the potential relationship between pandemic-related information and air quality data from a more holistic and detailed point of view, we propose a methodology based on pure data analysis. Three types of data were collected, namely air quality index, pandemic-related events, and number of COVID cases. Data were collected from five cities—Wuhan, New York, Seoul, Melbourne, and Singapore—to further analyse the response of air quality index to COVID events, thus revealing how human activity influences air quality from a pandemic perspective. The results show that a potential connection does exist in most cases and provide more evidence showing that air pollution declined during the pandemic. However, the strength of this relationship may also be related to other factors, such as geography, politics, population density, and measures imposed by local authorities, etc. This study provides another perspective to assist stakeholders in improving environmental decision making.

Thermosensitive Poly(DHSe/PEG/PPG Urethane)-Based Hydrogel Extended Remdesivir Application in Ophthalmic Medication.

The spread of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the coronavirus disease 2019 (COVID-19) outbreak beginning in March 2020. Currently, there is a lack of suitable dose formulations that interrupt novel coronavirus transmission via corneal and conjunctival routes. In the present study, we developed and evaluated a thermosensitive gelling system based on a selenium-containing polymer for topical ocular continuous drug release. In detail, di-(1-hydroxylundecyl) selenide (DHSe), poly(ethylene glycol) (PEG), and poly(propylene glycol) (PPG) were polymerized to form poly(DHSe/PEG/PPG urethane). The polymer was used to carry poorly water-soluble remdesivir (RDV) at room temperature to form the final thermosensitive in situ gel, which exhibited a typical sol-gel transition at 35 °C. The formed polymer was further characterized by rheology, thermology, and scanning electron microscopy. In vitro release studies and in vivo retention and penetration tests indicated that the thermogel provided the prolonged release of RDV. The RDV-loaded in situ gel was proven to be non-biotoxic against human corneal epithelial cells, with good ocular tolerance and biocompatibility in rabbit eyes.

Infection Control Behavior at Home During the COVID-19 Pandemic: Observational Study of a Web-Based Behavioral Intervention (Germ Defence).

BACKGROUND: To control the COVID-19 pandemic, people should adopt protective behaviors at home (self-isolation, social distancing, putting shopping and packages aside, wearing face coverings, cleaning and disinfecting, and handwashing). There is currently limited support to help individuals conduct these behaviors. OBJECTIVE: This study aims to report current household infection control behaviors in the United Kingdom and examine how they might be improved. METHODS: This was a pragmatic cross-sectional observational study of anonymous participant data from Germ Defence between May 6-24, 2020. Germ Defence is an open-access fully automated website providing behavioral advice for infection control within households. A total of 28,285 users sought advice from four website pathways based on household status (advice to protect themselves generally, to protect others if the user was showing symptoms, to protect themselves if household members were showing symptoms, and to protect a household member who is at high risk). Users reported current infection control behaviors within the home and intentions to change these behaviors. RESULTS: Current behaviors varied across all infection control measures but were between sometimes (face covering: mean 1.61, SD 1.19; social distancing: mean 2.40, SD 1.22; isolating: mean 2.78, SD 1.29; putting packages and shopping aside: mean 2.75, SD 1.55) and quite often (cleaning and disinfecting: mean 3.17, SD 1.18), except for handwashing (very often: mean 4.00, SD 1.03). Behaviors were similar regardless of the website pathway used. After using Germ Defence, users recorded intentions to improve infection control behavior across all website pathways and for all behaviors (overall average infection control score mean difference 0.30, 95% CI 0.29-0.31). CONCLUSIONS: Self-reported infection control behaviors other than handwashing are lower than is optimal for infection prevention, although handwashing is much higher. Advice using behavior change techniques in Germ Defence led to intentions to improve these behaviors. Promoting Germ Defence within national and local public health and primary care guidance could reduce COVID-19 transmission.

Nucleocapsid mutations R203K/G204R increase the infectivity, fitness, and virulence of SARS-CoV-2.

Previous work found that the co-occurring mutations R203K/G204R on the SARS-CoV-2 nucleocapsid (N) protein are increasing in frequency among emerging variants of concern or interest. Through a combination of in silico analyses, this study demonstrates that R203K/G204R are adaptive, while large-scale phylogenetic analyses indicate that R203K/G204R associate with the emergence of the high-transmissibility SARS-CoV-2 lineage B.1.1.7. Competition experiments suggest that the 203K/204R variants possess a replication advantage over the preceding R203/G204 variants, possibly related to ribonucleocapsid (RNP) assembly. Moreover, the 203K/204R virus shows increased infectivity in human lung cells and hamsters. Accordingly, we observe a positive association between increased COVID-19 severity and sample frequency of 203K/204R. Our work suggests that the 203K/204R mutations contribute to the increased transmission and virulence of select SARS-CoV-2 variants. In addition to mutations in the spike protein, mutations in the nucleocapsid protein are important for viral spreading during the pandemic.

Pandemics, Vaccines and an Earnings Damage Function

We derive a parsimonious model of damage to corporate earnings from COVID-19. Using measures of expected damage from industry-level earnings forecast revisions, we estimate this model with nonlinear least squares and identifying restrictions related to forecast rationality. Forecasts in mid-May 2020 imply an earnings crash and lower earnings growth until a vaccine arrives in 1.48 years (95% CI [0.61, 5.88]). We extend our framework to account for time-varying vaccine arrival rates. Mid-August 2020 forecasts imply a vaccine arrival in 0.61 years (95% CI [0.35, 1.06]), which is due to positive vaccine news as opposed to fiscal or monetary policy news.