Repurposing of poly-gamma-glutamic acid, immunotherapeutic drug for cervical intraepithelial neoplasia 1, as covid-19 treatment

Covid-19 virus variants identified so far are due to viral genetic diversity, genetic evolution, and variable infectivity, suggesting that high infection rates and high mortality rates may be contributed by these mutations. And it has been reported that the targeting strategies for innate immunity should be less vulnerable to viral evolution, variant emergence and resistance. Therefore, the most effective solution to Covid-19 infection has been proposed to prevent and treat severe exacerbation of patients with moderate disease by enhancing human immune responses such as NK cell and T cell. In previous studies, we demonstrated for the first time that gamma-PGA induced significant antitumor activity and antiviral activity by modulating NK cell-mediated cytotoxicity. Especially intranasal administration of gamma-PGA was found to effectively induce protective innate and CTL immune responses against viruses and we found out that gamma-PGA can be an effective treatment for cervical intraepithelial neoplasia 1 through phase 2b clinical trial. In this study, the possibility of gamma-PGA as a Covid-19 immune modulating agent was confirmed by animal experiments infected with Covid-19 viruses. After oral administration of gamma-PGA 300mug/mouse once a day for 5 days in a K18-hACE2 TG mouse model infected with SARS-CoV-2 (NCCP 43326;original strain) and SARS-CoV-2 (NCCP 43390;Delta variant), virus titer and clinical symptom improvement were confirmed. In the RjHan:AURA Syrian hamster model infected with SARS-CoV-2 (NCCP 49930;Delta variant), 350 or 550 mug/head of gamma-PGA was administered orally for 10 days once a day. The virus for infection was administered at 5 x 104 TCID50, and the titer of virus and the improvement of pneumonia lesions were measured to confirm the effectiveness in terms of prevention or treatment. In the mouse model infected with original Covid-19 virus stain, the weight loss was significantly reduced and the survival rate was also improved by the administration of gamma-PGA. And gamma-PGA alleviated the pneumonic lesions and reduced the virus titer of lung tissue in mice infected with delta variant. In the deltavariant virus infected hamster model, gamma-PGA showed statistically significant improvement of weight loss and lung inflammation during administration after infection. This is a promising result for possibility of Covid-19 therapeutics along with the efficacy results of mouse model, suggesting gammaPGA can be therapeutic candidate to modulate an innate immune response for Covid-19.

Change in departure time for a train trip to avoid crowding during the COVID-19 pandemic: A latent class study in the Netherlands

The energy-efficient plate heat exchanger (PHE) and refrigerant R1234yf, which has a low global warming potential (GWP), can be used to realize an energy efficient heat pump (HP) system for electric vehicles (EV), extending their driving range. Therefore, the characteristics of R1234yf in an offset-fin strip (OSF) flowstructured PHE are critical for heat-exchanger design. This study investigates the condensation heat transfer coefficient (C-HTC) and two-phase frictional pressure drop (2P-FPD) of R1234yf during condensation in an OSF flow-structured PHE under various operating conditions. First, a modified Wilson plot method was used to determine the multiplier (C) and Reynolds number exponential (n) for the coolant side as -0.426 and 0.494, respectively. When the heat flux (q), average vapor quality (xa), and mass flux (G) increased, the C-HTC increased, whereas it decreased with saturation temperature (Tsat). Despite the force-convective condensation flow regime, the C-HTC increment was minimal with G at lower xa owing to the lesser significance of the shear effect. Additionally, the 2P-FPD was unaffected by q but increased considerably with an increase in xa and G and a decrease in Tsat. Based on the current experimental database, empirical correlations for forecasting friction factor and Nusselt number were developed with a 91% predictability.

Inherited deficiency of the OAS-RNase L pathway in children with MIS-C

Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic dsRNA-sensing OAS1 and OAS2 generate 2'-5'-linked oligoadenylates (2-5A) that activate the ssRNA-degrading RNase L. Consistent with the absence of pneumonia in these patients, epithelial cells and fibroblasts defective for this pathway restricted SARS-CoV-2 normally. This contrasted with IFNAR1-deficient cells from patients prone to hypoxemic pneumonia without MIS-C. Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNASEL deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or SARS-CoV- 2 stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-but not RNase L- deficient cells. Cytokine production in RNase L-deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by MAVS deficiency. Recessive OAS-RNase L deficiencies in these patients unleash the production of SARS-CoV-2-triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C.Copyright © 2023 Elsevier Inc.

Immunotherapy: OFF-THE-SHELF PARTIAL HLA MATCHING SARS-COV-2 ANTIGEN SPECIFIC T CELL THERAPY FOR SEVERE COVID-19 PATIENTS

Background & Aim: Immunological characteristics of COVID-19 show pathological hyperinflammation associated with lymphopenia and dysfunctional T cell responses. These features provide a rationale for restoring functional T cell immunity in COVID-19 patients by adoptive transfer of SARS-CoV-2 specific T cells. Methods, Results & Conclusion(s): To generate SARS-CoV-2 specific T cells, we isolated peripheral blood mononuclear cells from 7 COVID-19 recovered and 13 unexposed donors. Consequently, we stimulated cells with SARS-CoV-2 peptide mixtures covering spike, membrane and nucleocapsid proteins. Then, we culture expanded cells with IL-2 for 21 days. We assessed immunophenotypes, cytokine profiles, antigen specificity of the final cell products. Our results show that SARSCoV- 2 specific T cells could be expanded in both COVID-19 recovered and unexposed groups. Immunophenotypes were similar in both groups showing CD4+ T cell dominance, but CD8+ and CD3+CD56+ T cells were also present. Antigen specificity was determined by ELISPOT, intracellular cytokine assay, and cytotoxicity assays. One out of 14 individuals who were previously unexposed to SARS-CoV-2 failed to show antigen specificity. Moreover, ex-vivo expanded SARS-CoV-2 specific T cells mainly consisted of central and effector memory subsets with reduced alloreactivity against HLA-unmatched cells suggesting the possibility for the development of third-party partial HLA-matching products. In conclusion, our findings show that SARSCoV- 2 specific T cell can be readily expanded from both COVID-19 and unexposed individuals and can therefore be manufactured as a biopharmaceutical product to treat severe COVID-19 patients.Copyright © 2023 International Society for Cell & Gene Therapy

Organic Electrochemical Transistors functionalized with Protein Minibinders for Sensitive and Specific Detection of SARS-CoV-2

There is a need for rapid, sensitive, specific, and low-cost virus sensors. Recent work has demonstrated that organic electrochemical transistors (OECTs) can detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Here, a simple and low-cost approach to the fabrication of OECT devices with excellent stability and unprecedented sensitivity and specificity for the detection of SARS-CoV-2 virus is demonstrated. The devices rely on the engineered protein minibinder LCB1, which binds strongly to SARS-CoV-2. The resulting devices exhibit excellent sensitivity for the detection of SARS-CoV-2 virus and SARS-CoV-2 spike protein receptor binding domain (RBD). These results demonstrate a simple, effective, and low-cost biomolecular sensor applicable to the real-time detection of SARS-CoV-2 virus and a general strategy for OECT device design that can be applied for the detection of other pathogenic viruses.

Electrostatic Precipitator Design Optimization for the Removal of Aerosol and Airborne Viruses

In the midst of the COVID-19 pandemic, new requirements for clean air supply are introduced for heating, ventilation, and air conditioning (HVAC) systems. One way for HVAC systems to efficiently remove airborne viruses is by filtering them. Unlike disposable filters that require repeated purchases of consumables, the electrostatic precipitator (ESP) is an alternative option without the drawback of reduced dust collection efficiency in high-efficiency particulate air (HEPA) filters due to dust buildup. The majority of viruses have a diameter ranging from 0.1 μm to 5 μm. This study proposed a two-stage ESP, which charged airborne viruses and particles via positive electrode ionization wire and collected them on a collecting plate with high voltage. Numerical simulations were conducted and revealed a continuous decrease in collection efficiencies between 0.1 μm and 0.5 μm, followed by a consistent increase from 0.5 μm to 1 μm. For particles larger than 1 μm, collection efficiencies exceeding 90% were easily achieved with the equipment used in this study. Previous studies have demonstrated that the collection efficiency of suspended particles is influenced by both the ESP voltage and turbulent flow at this stage. To improve the collection efficiency of aerosols ranging from 0.1 μm to 1 μm, this study used a multi-objective genetic algorithm (MOGA) in combination with numerical simulations to obtain the optimal parameter combination of ionization voltage and flow speed. The particle collection performance of the ESP was examined under the Japan Electrical Manufacturers' Association (JEMA) standards and showed consistent collection performance throughout the experiment. Moreover, after its design was optimized, the precipitator collected aerosols ranging from 0.1 μm to 3 μm, demonstrating an efficiency of over 95%. With such high collection efficiency, the proposed ESP can effectively filter airborne particles as efficiently as an N95 respirator, eliminating the need to wear a mask in a building and preventing the spread of droplet infectious diseases such as COVID-19 (0.08 μm–0.16 μm). © 2023 by the authors.

Are We Losing Connection? Lived Experience of Online Mutual Aid Groups During the COVID-19 Pandemic

Background: The current UK based study aimed to explore the experiences of individuals attending online mutual aid groups for alcohol use, while their face-to-face groups were suspended during the COVID-19 pandemic. Emerging evidence suggests that the pandemic and concomitant isolation is associated with elevated mental health problems. Furthermore, historical community-wide crises are associated with increases in alcohol consumption. Due to the paucity of qualitative research on the subjective experience of online mutual aid groups, an interpretative phenomenological analysis was undertaken to explore group members' experiences. Methods: A sample of six eligible members of online alcohol mutual aid groups were recruited and completed semi-structured interviews during the COVID-19 pandemic between October 2020 and February 2021. Interpretative phenomenological analysis was used to identify key themes and evidenced with salient quotations. Results: The superordinate theme developing an understanding of the differences between face-to-face and online group proceedings was identified, which is presented and unpacked with evidential quotes. Conclusion: The study explicates group members' perceived differences between online and face-to-face experiences. Some participants valued the increased control and anonymity of online groups, while others missed the profound intimate connection that face-to-face groups fostered. It is recommended that future provision is informed by service-user voice to develop an attunement with the subjectivity of mutual aid group members' experiences. © The Author(s) 2023.

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee

The year 2020 has marked the spread of a global pandemic, COVID-19, challenging many aspects of our daily lives. Different organizations have been involved in controlling this outbreak. The social distancing intervention is deemed to be the most effective policy in reducing face-to-face contact and slowing down the rate of infections. Stay-at-home and shelter-in-place orders have been implemented in different states and cities, affecting daily traffic patterns. Social distancing interventions and fear of the disease resulted in a traffic decline in cities and counties. However, after stay-at-home orders ended and some public places reopened, traffic gradually started to revert to pre-pandemic levels. It can be shown that counties have diverse patterns in the decline and recovery phases. This study analyzes county-level mobility change after the pandemic, explores the contributing factors, and identifies possible spatial heterogeneity. To this end, 95 counties in Tennessee have been selected as the study area to perform geographically weighted regressions (GWR) models. The results show that density on non-freeway roads, median household income, percent of unemployment, population density, percent of people over age 65, percent of people under age 18, percent of work from home, and mean time to work are significantly correlated with vehicle miles traveled change magnitude in both decline and recovery phases. Also, the GWR estimation captures the spatial heterogeneity and local variation in coefficients among counties. Finally, the results imply that the recovery phase could be estimated depending on the identified spatial attributes. The proposed model can help agencies and researchers estimate and manage decline and recovery based on spatial factors in similar events in the future.

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee.

The year 2020 has marked the spread of a global pandemic, COVID-19, challenging many aspects of our daily lives. Different organizations have been involved in controlling this outbreak. The social distancing intervention is deemed to be the most effective policy in reducing face-to-face contact and slowing down the rate of infections. Stay-at-home and shelter-in-place orders have been implemented in different states and cities, affecting daily traffic patterns. Social distancing interventions and fear of the disease resulted in a traffic decline in cities and counties. However, after stay-at-home orders ended and some public places reopened, traffic gradually started to revert to pre-pandemic levels. It can be shown that counties have diverse patterns in the decline and recovery phases. This study analyzes county-level mobility change after the pandemic, explores the contributing factors, and identifies possible spatial heterogeneity. To this end, 95 counties in Tennessee have been selected as the study area to perform geographically weighted regressions (GWR) models. The results show that density on non-freeway roads, median household income, percent of unemployment, population density, percent of people over age 65, percent of people under age 18, percent of work from home, and mean time to work are significantly correlated with vehicle miles traveled change magnitude in both decline and recovery phases. Also, the GWR estimation captures the spatial heterogeneity and local variation in coefficients among counties. Finally, the results imply that the recovery phase could be estimated depending on the identified spatial attributes. The proposed model can help agencies and researchers estimate and manage decline and recovery based on spatial factors in similar events in the future.

Production efficiency and economic benefit evaluation of biohydrogen produced using macroalgae as a biomass feedstock in Asian circular economies

This study uses three data envelopment analysis models to determine the production efficiency of biohydrogen which is produced from macroalgae and other sources by dark fermentation. The efficiency of macroalgae is greatest in batch mode for S. Japonica using a sDFMEC process at pH 5.3, 35 degrees C, 1 g COD/L and a hydrogen production rate (HPR) of 0.34 L/L/h. The highest efficiency is using an internal circulation batch reactor in continuous mode for beverage waste water. The HPR and substrate concentration are the most important factor of biohydrogen efficiency, and efficiency and temperature are the most important factors of HPR. Malaysia and India are the two economies that most benefit from increased production efficiency due to the use of macroalgae. Increasing biohydrogen yield efficiency will improve macroeconomic growth and establish a renewable hydrogen and biohydrogen industry, which is especially efficient related to the economic recovery during the COVID-19 pandemic. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Does Viral Anxiety Influence the Insomnia Severity Among Patients With Insomnia Disorder During COVID-19 Pandemic?

Background and Objective We aimed to investigate whether viral anxiety affects insomnia severity in patients with insomnia disorder during the coronavirus disease 2019 (COVID-19) pandemic. In addition, we examined whether viral anxiety mediates the influence of dysfunctional beliefs about sleep on insomnia severity. Methods The medical records of 111 patients who visit the sleep clinic from September 2021 to May 2022 were reviewed. Patients' symptoms were rated with rating scales including Insomnia Severity Index (ISI), Stress and Anxiety to Viral Epidemics-6 items (SAVE-6), Dysfunctional Beliefs and Attitudes about Sleep-16 items (DBAS-16), Patient Health Questionnaire-9 items (PHQ-9), Epworth Sleepiness Scale, and discrepancy between desired time in bed and desired total sleep time (the DBST index). Results The SAVE-6 score was not significantly correlated with ISI score among insomnia patients. Linear regression analysis showed that the ISI score was expected by PHQ-9 (β = 0.21, p = 0.038) and DBAS-16 (β = 0.42, p < 0.001). Mediation analysis showed that viral anxiety did not mediate the influence of dysfunctional beliefs about sleep on insomnia severity. Conclusions We could not observe the mediating effect of viral anxiety on the association between dysfunctional beliefs about sleep on insomnia severity. Though COVID-somnia was one of big issues in this COVID-19 pandemic, the influence of virus on the severity of insomnia among insomnia patients needs to be interpreted cautiously © 2023 The Korean Society of Sleep Medicine

Correlates of substance use disorder among persons experiencing homelessness in Los Angeles during the COVID-19 pandemic

Background: People experiencing homelessness (PEH) are vulnerable to COVID-19 transmission due to substance use, congregate living conditions, and underlying medical conditions. Yet, little is known about factors impacting drug use disorder among PEH during COVID-19 pandemic. The purpose of this study was to identify correlates associated with substance use disorder among PEH, both those who were diagnosed with COVID-19 and those who tested negative or never tested. Methods: A cross-sectional, structured survey was administered to PEH (N = 102) who were recruited from sheltered and unsheltered settings. Descriptive analysis, t-tests, Fisher's exact test or chi-squared test, and bivariate and multiple linear regression were conducted. Results: PEH with a COVID-19 diagnosis included male gender, and Latino race/ethnicity (p <.05). Moreover, substance use disorder scores (p -.037) and days on the street were negatively associated with COVID-19 (p <.001). Multivariable analyses revealed a significant positive relationship between days slept on the street and substance use disorder (p <.001), and a significant negative relationship with alcohol use (p <.05);COVID-19 remained negatively associated with substance use disorder, but it was not significant. Conclusions: This study provides evidence about correlates of drug use disorder among PEH. More studies are needed to understand successful individual and system-level strategies for reducing drug-related problems during COVID-19. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.

Robotic Manipulation System Design and Control for Non-Contact Remote Diagnosis in Otolaryngology: Digital Twin Approach

The COVID-19 pandemic has emphasized the need for non-contact medical robots to alleviate the heavy workload and emotional stress experienced by healthcare professionals while preventing infection. In response, we propose a non-contact robotic diagnostic system for otolaryngology clinics, utilizing a digital twin model for initial design optimization. The system employs a master-slave robot architecture, with the slave robot comprising a flexible endoscope manipulation robot and a parallel robot arm for controlling additional medical instruments. The novel 4 degrees of freedom (DOF) control mechanism enables the single robotic arm to handle the endoscope, facilitating the process compared to the traditional two-handed approach. Phantom experiments were conducted to evaluate the effectiveness of the proposed flexible endoscope manipulation system in terms of diagnosis completion time, NASA task load index (NASA-TLX), and subjective risk score. The results demonstrate the system's usability and its potential to alternate conventional diagnosis. © 2013 IEEE.

Relational analysis between economic activities and mobility during the COVID

Coronavirus disease (COVID-19) has significantly affected daily lives since its declaration as a Pandemic in March 2020 by the WHO. Studies in Korea to interpret the relationship between COVID-19 and transportation show that there has been a decrease in public transportation use, and a significant decrease when a widespread infection occurs. In addition, COVID-19 has affected the commercial environment, particularly the number of people using commercial districts where the use of retail outlets decreased significantly. This study analyses the disease-vectors (spread factors) of COVID-19 in terms of transportation demand, the revitalisation of commercial districts, living populations, and socioeconomic indicators. It attempts to identify different infection factors for each district in Seoul using a causal analysis methodology PLS-SEM (Partial Least-Squares Structural Equation Modelling) such that COVID-19 can be managed continuously with the aim to provide a foundation for pre-emptive actions by adjusting or controlling specific influencing factors pertaining to infectious diseases. © 2023 ICE Publishing: All rights reserved.

An Analysis of Factors Influencing the Intention to Use "Untact” Services by Service Type

Since COVID-19, social distancing has become common, and the demand for untact services has increased rapidly, resulting in an economic phenomenon centered on untact worldwide. Due to social distancing, the untact service area is expanding not only to shopping but also to online learning, home training, and telemedicine, and untact services are expected to expand to more diverse areas in the future. This study investigates four types of untact services: online lectures, online meetings related to work and study, online seminars, and online performances, and the effects of concerns about untact services on the intention of use have been examined using a path analysis model. As a result of the analysis, the perceived usefulness had a positive effect on the user's continuous intention to use untact services. However, depending on the type of untact service, it can be confirmed that the factors that affect the intention to continue using the service differ from each other. Practitioners can use the results of this study when designing untact services in the future. © 2023 by the authors.

How Health Systems Can Survive: The Case of Musculoskeletal Care

Healthcare represents 19.7% of the gross national product, making it one of the largest expenses for all U.S. companies. It crowds out investment for growth and is generally considered unsustainable. And the biggest cost is hospitals. Every manager has a vested interest in lowering the cost of care and increasing the viability of hospitals in their community. More than 10% of U.S. hospitals are at immediate risk of closing because of financial losses and lack of financial reserves. Over 70% of 900 hospitals surveyed reported a decrease in operating revenue over the last year. The COVID-19 pandemic provided momentum toward developing alternative deliveries of care, including virtual health, home, and outpatient care. This has created a rapid, massive shift away from hospital-based care. Perhaps the greatest risk is the largest opportunity-to find solutions to this financial crisis in the rapidly changing revenue dynamic of subspecialties, with musculoskeletal care being the prime example. Alternative sites of care and innovative care delivery are being financed by capital market investment. One solution to this crisis is for hospitals to collaborate with capital market-backed companies creating a novel business model.

Understanding experiences of food-delivery-platform workers under algorithmic management using topic modeling

With the emergence of COVID-19, the food-delivery market has grown and now employs large numbers of people as drivers. The independent contractors enjoy flexibility, but their schedules are at the mercy of algorithmic management. This study explores the experiences of food-delivery-platform workers with algorithmic management and their perceptions in response to algorithmic decisions. A collection of 1046 posts containing "AI” (for artificial intelligence) and "algorithm” made to online communities frequently used by platform workers is subjected to keyword analysis, semantic network analysis, and topic modeling using latent Dirichlet allocation. Fifteen latent topics are classified into AI matching, driver behavior, and platform system, and discussed using representative posts from online communities. The results highlight the advancement of AI technology and collaboration strategies used by platform operators to generate trust in algorithmic decisions among food-delivery-platform workers. In addition, this study uses using topic modeling to comprehensively and objectively explore how food-delivery-platform workers with experience working under AI algorithmic management perceive that management. © 2023 Elsevier Inc.

Is the global supply chain hard to reverse? Understanding manufacturing strategies of Chinese, Japanese, and South Korean Firms

As the Covid pandemic underscores global supply chain risks, there is a debate on whether to bring US manufacturing back from overseas. This paper provides insights into the heated debate on the global supply chain by examining the competitive manufacturing environments of China, Japan, and South Korea. More specifically, we conduct a cross-national survey and empirically investigate the manufacturing strategies employed by manufacturing managers in the top Asian players: China, Japan, and South Korea. We examine four dimensions of the manufacturing strategies: quality, inventory, flexibility, and top management involvement. Our findings indicate that Japanese manufacturers are more committed to the cumulative approach to quality management and see enhanced flexibility as a strategic priority. While Chinese managers are also committed to achieving quality, they are more delivery-driven and thus are more likely to occasionally accept slightly off-quality components from suppliers to "save” an order. However, in all three countries, managers with a high focus on quality also focus on just-in-time management and in turn, on flexibility. There is significantly less agreement among Chinese managers, compared to their Japanese and Korean counterparts, that the top management should be involved in operational planning, goal setting, and the provision of rewards. © 2022 Wiley Periodicals LLC.