Ivermectin as a possible treatment for COVID-19: a review of the 2022 protocols / Ivermectina como um possível tratamento para COVID-19: uma revisão dos protocolos de 2022

Ivermectin is a safe and effective drug in humans and has been approved for use in numerous parasitic infections for over 50 years. In addition, many studies have already shown its antiviral activity. Ivermectin is generally well tolerated, with no indication of central nervous system-associated toxicity at doses up to 10 times the highest FDA-approved dose of 200 µg/kg. The in vitro results of ivermectin for reducing SARS-CoV-2 viral load are promising and show that Ivermectin kills SARS-CoV-2 within 48 hours. A hypothesized mechanism of action for this drug is a likely inhibition of IMPα/ß1-mediated nuclear import of viral proteins as demonstrated for other RNA viruses. However, controlled and randomized studies are needed to prove its effectiveness in COVID-19 in humans. In a single in vivo study with published results, patients confirmed to be infected with SARS-CoV-2 received at least one dose of ivermectin at any time during hospitalization. The use of ivermectin was associated with lower mortality during treatment with COVID-19, especially in patients who required increased inspired oxygen or ventilatory support. Additionally, 81 studies with the clinical use of ivermectin in humans are being carried out worldwide according to ClinicalTrials.gov. However, none of these data has been published so far. However, private and public entities in Brazil have been adopting this drug in their protocols as prophylaxis and in the initial phase of the disease. In addition, ivermectin has been used in mass treatment to prevent onchocerciasis and lymphatic filariasis in sub-Saharan Africa for many years. Surprisingly, this region has the lowest proportional mortality rate among the continents, despite the increasing numbers of infected people released by the World Health Organization.

A ivermectina é um fármaco seguro e eficaz em seres humanos e é aprovado para uso em inúmeras infecções parasitárias há mais de 50 anos. Além disso, muitos estudos já evidenciaram sua atividade antiviral. A ivermectina é geralmente bem tolerada, sem indicação de toxicidade associada ao sistema nervoso central para doses até 10 vezes a dose mais alta, aprovada pelo FDA (Food and Drug Administration), de 200 µg/kg. Os resultados in vitro da ivermectina para redução da carga viral do SARS-CoV-2 são promissores e mostram que a Ivermectina mata o SARS-CoV-2 dentro de 48 horas. Uma hipótese de mecanismo de ação para esta droga é uma provável inibição da importação nuclear de proteínas virais mediada por IMPα / ß1 como demonstrado para outros vírus de RNA. No entanto, estudos controlados e randomizados são necessários para comprovar sua eficácia na COVID-19 em humanos. Em um único estudo in vivo com resultados publicados, pacientes confirmadamente infectados por SARS-CoV-2 receberam pelo menos uma dose de ivermectina em qualquer momento durante a hospitalização. A utilização da ivermectina foi associada a menor mortalidade durante o tratamento com COVID-19, especialmente em pacientes que necessitaram de maior oxigênio inspirado ou suporte ventilatório. Adicionalmente, 81 estudos com o uso clínico da ivermectina em humanos estão sendo realizados em todo o mundo segundo o site ClinicalTrials.gov. Porém, nenhum destes teve seus dados publicados até o momento. No entanto, entidades privadas e públicas no Brasil vêm adotando este medicamento em seus protocolos como profilaxia e na fase inicial da doença. Além disto, a ivermectina é utilizada no tratamento em massa na prevenção da oncocercose e filariose linfática na África subsaariana há muitos anos. Surpreendentemente, esta região possui o menor índice de mortalidade proporcional entre os continentes, apesar dos números crescentes de contaminados divulgados pela Organização Mundial da Saúde.

Inhibitory effect of thymoquinone from Nigella sativa against SARS-CoV-2 main protease. An in-silico study / Efeito inibitório da timoquinona de Nigella sativa contra a principal protease do SARS-CoV-2. Um estudo in silico

Nigella sativa is known for the safety profile, containing a wealth of useful antiviral compounds. The main protease (Mpro, 3CLpro) of severe acute respiratory syndrome 2 (SARS-CoV-2) is being considered as one of the most attractive viral target, processing the polyproteins during viral pathogenesis and replication. In the current investigation we analyzed the potency of active component, thymoquinone (TQ) of Nigella sativa against SARS-CoV-2 Mpro. The structures of TQ and Mpro was retrieved from PubChem (CID10281) and Protein Data Bank (PDB ID 6MO3) respectively. The Mpro and TQ were docked and the complex was subjected to molecular dynamic (MD) simulations for a period 50ns. Protein folding effect was analyzed using radius of gyration (Rg) while stability and flexibility was measured, using root means square deviations (RMSD) and root means square fluctuation (RMSF) respectively. The simulation results shows that TQ is exhibiting good binding activity against SARS-CoV-2 Mpro, interacting many residues, present in the active site (His41, Cys145) and also the Glu166, facilitating the pocket shape. Further, experimental approaches are needed to validate the role of TQ against virus infection. The TQ is interfering with pocket maintaining residues as well as active site of virus Mpro which may be used as a potential inhibitor against SARS-CoV-2 for better management of COVID-19.

Nigella sativa é conhecida pelo perfil de segurança, contendo uma grande variedade de compostos antivirais úteis. A principal protease (Mpro, 3CLpro) da síndrome respiratória aguda grave 2 (SARS-CoV-2) está sendo considerada como um dos alvos virais mais atraentes, processando as poliproteínas durante a patogênese e replicação viral. Na presente investigação analisamos a potência do componente ativo, timoquinona (TQ) de Nigella sativa contra SARS-CoV-2 Mpro. As estruturas de TQ e Mpro foram recuperadas de PubChem (CID10281) e Protein Data Bank (PDB ID 6MO3), respectivamente. O Mpro e o TQ foram acoplados e o complexo foi submetido a simulações de dinâmica molecular (MD) por um período de 50ns. O efeito de dobramento de proteínas foi analisado usando o raio de giração (Rg) enquanto a estabilidade e a flexibilidade foram medidas usando a raiz quadrada média dos desvios (RMSD) e a raiz média quadrada da flutuação (RMSF), respectivamente. Os resultados da simulação mostram que o TQ está exibindo boa atividade de ligação contra o SARS-CoV-2 Mpro, interagindo em muitos resíduos presentes no sítio ativo (His41, Cys145) e também o Glu166, facilitando o formato da bolsa. Além disso, são necessárias abordagens experimentais para validar o papel do TQ contra a infecção pelo vírus. O TQ está interferindo nos resíduos de manutenção do bolso, bem como no sítio ativo do vírus Mpro, que pode ser usado como um potencial inibidor contra o SARS-CoV-2 para um melhor gerenciamento da Covid-19.

Study of innovation capacity of fisheries companies in the covid-19 pandemic crisis / Estudo da capacidade de inovação das empresas de pesca na crise da pandemia de covid-19

Many countries have encountered coronavirus pandemic crisis around the world. Through the outbreak of this disease in Iran, preventive plans have been implemented to break the chain of the disease infection. These measures in the economic sector have affected supply, production and demand, and to some extent have led to the partial or complete closure of some businesses and occupations. In the context, it seems that innovative an "innovation capacity" infrastructure measures and turning to innovation in this crisis can be a strategy to moderate and optimize the situation. This study tries to design concepts of the fisheries firms' innovation capacity model in the context of the COVID-19 pandemic crisis. After collecting data, they were analyzed using SPSS and PLS SMART software, which were performed in two parts: descriptive statistics and analytical or inferential statistics. A novel research model is presented to examine the impact of factors such as innovation management, social, cultural, human and organizational capital, crisis strategies, government actions in crisis situations, and marketing strategies in crisis situations, as well as, recognition and application of marketing advantages in crisis situations, which offers a re-analysis of innovation capacity. According to the results, among the variables played a significant role on the level of innovation capacity in epidemic conditions, innovation management (p> 0.000; ß = 0.593), and recognition and application of marketing advantages (p> 0.049; ß = 0.209) were the most significant, independent variables affecting the innovation capacity, which explained its variations.

Muitos países enfrentaram crises na pandemia de coronavírus em todo o mundo. Por meio do surto dessa doença no Irã, planos preventivos foram implementados para quebrar a cadeia de infecção da doença. Essas medidas no setor econômico afetaram a oferta, a produção e a demanda e, em certa medida, levaram ao fechamento parcial ou total de alguns negócios e serviços. Nesse contexto, parece que medidas de infraestrutura inovadoras e com "capacidade de inovação" podem ser uma estratégia para moderar e otimizar a situação nesta crise. Este estudo tenta desenhar conceitos do modelo de capacidade de inovação das empresas de pesca no contexto da crise da pandemia de COVID-19. Após a coleta dos dados, eles foram analisados ​​por meio dos softwares SPSS e PLS SMART e realizados em duas partes: estatística descritiva e estatística analítica ou inferencial. Um novo modelo de pesquisa é apresentado para examinar o impacto de fatores como gestão da inovação, capital social, cultural, humano e organizacional, estratégias de crise, ações governamentais em situações de crise e estratégias de marketing em situações de crise, bem como reconhecimento e aplicação de vantagens de marketing em situações de crise, que oferece uma reanálise da capacidade de inovação. De acordo com os resultados, entre as variáveis ​​que desempenharam um papel significativo no nível de capacidade de inovação em condições epidêmicas, a gestão da inovação (p > 0,000; ß = 0,593) e o reconhecimento e aplicação de vantagens de marketing (p > 0,049; ß = 0,209) foram as variáveis ​​independentes mais significativas que afetaram a capacidade de inovação, o que explicou suas variações.

Acute necrotic disorder of the small intestine post-coronavirus disease-2019 vaccination.

The Pfizer-BioNTech coronavirus disease 2019 (COVID-19) vaccine is extensively used worldwide, and its safety has been proven. Herein, we report a case of an acute necrotic disorder in the small intestine post-COVID-19 vaccination. The patient developed severe abdominal pain the day after the first vaccination. Contrast-enhanced computed tomography showed extensive ileum wall thickening and ascites. Colonoscopy revealed a ring-shaped ulcer and stricture in the terminal ileum. Ileocecal resection was performed, and the patient did not have further episodes of a necrotic disorder in the small intestine. Although it is unknown if this event is associated with vaccination, and this occurrence also does not outweigh the efficacy and safety of the Pfizer-BioNTech COVID-19 vaccine, gastroenterologists need to be aware of this rare case, given its noteworthy timing.

Setting up a three-stage pre-endoscopy triage during the coronavirus disease 2019 pandemic: A multicenter observational study.

Objectives: Between May and July 2021, the coronavirus disease 2019 (COVID-19) pandemic led to a sharp surge in community transmission in Taiwan. We present a three-stage restructuring process of pre-endoscopy triage at the beginning of the pandemic, which can support urgent endoscopic procedures while protecting endoscopy staff. Methods: The pre-endoscopy triage framework was set up with three checkpoints at the hospital entrance, outpatient department, and endoscopy unit, with a specific target patient population and screening methods. Relevant data included the number of endoscopic procedures performed, outpatient department visits, and performing screening methods such as temperature measurement, travel, occupation, contact, and clustering history checking, polymerase chain reaction assay, and rapid antigen test. Results: Forehead temperature measurement and verification of travel, occupation, contact, and clustering history provided rapid, easy, and early mass screening of symptomatic patients at the hospital entrance. During the pandemic, outpatient department visits and endoscopic procedures decreased by 37% and 64%, respectively. The pre-endoscopy screening methods used displayed regional variations in COVID-19 prevalence. Among 16 endoscopy units with a community prevalence of ≥ 31.04 cases per 100,000 residents, 12 (75%) used polymerase chain reaction assay and four (25%) used rapid antigen test to identify asymptomatic patients before endoscopy. Of 6540 pre-endoscopy screening patients, 15 (0.23%) tested positive by laboratory testing. No endoscopy-related nosocomial COVID-19 infections were reported during the pandemic. Conclusions: We present a three-stage pre-endoscopy triage based on the local laboratory capacity, medical resources, and community prevalence. These measures could be useful during the COVID-19 pandemic.

Reinforcement sensitivity theory may predict COVID-19 infection outcome and vulnerability.

Research suggests that specific behavior patterns may be related with the outcome and vulnerability of a COVID-19 infection; nevertheless, much of this information has been obtained by means of psychological paradigms that are not based on research conducted using experimental designs. Thus, the purpose of the present study was to identify behavior patterns associated with COVID-19 outcome and vulnerability from the point of view of the Reinforcement Sensitivity Theory. A total of 464 college students from Mexico-City participated in the study. Participants answered the Behavior Inhibition, Behavior Activation scales (Carver & White, 1994), the Reinforcement Sensitivity Theory Personality Questionnaire (Corr & Cooper, 2016) and a COVID-19 symptom checklist. Data showed that those individuals who respond in an enthusiastic way to rewards develop less symptoms of COVID-19. Additionally, individuals who are keen in the exploration and identification of new rewarding opportunities are less likely to develop a COVID-19 infection. Both findings suggest that a potent Behavior Activation System could protect individuals during the present pandemic. These results are in general agreement with others produced within the same framework.

Introduction to the special issue on the role of operational research in future epidemics/ pandemics.

In this special issue, 23 research papers are published focusing on COVID-19 and operational research solution techniques. First, we detail the process from advertising the call for papers to the point where the best papers are accepted. Then, we provide a summary of each paper focusing on applications, solution techniques and insights for practitioners and policy makers. To provide a holistic view for readers, we have clustered the papers into different groups: transmission, propagation and forecasting, non-pharmaceutical intervention, healthcare network configuration, healthcare resource allocation, hospital operations, vaccine and testing kits, and production and manufacturing. Then, we introduce other possible subjects that can be considered for future research.

Social media-based COVID-19 sentiment classification model using Bi-LSTM.

Internet public social media and forums provide a convenient channel for people concerned about public health issues, such as COVID-19, to share and discuss information/misinformation with each other. In this paper, we propose a natural language processing (NLP) method based on Bidirectional Long Short-Term Memory (Bi-LSTM) technique to perform sentiment classification and uncover various issues related to COVID-19 public opinions. Bi-LSTM is an improved version of conventional LSTMs for generating the output from both left and right contexts at each time step. We experimented with real datasets extracted from Twitter and Reddit social media platforms, and our experimental results showed improved metrics compared with the conventional LSTM model as well as recent studies available in the literature. The proposed model can be used by official institutions to mitigate the effects of negative messages and to understand peoples' concerns during the pandemic. Furthermore, our findings shed light on the importance of using NLP techniques to analyze public opinion and to combat the spreading of misinformation and to guide health decision-making.

Adoption of measures to mitigate the impact of COVID-19: In search of a Hofstedian explanation for patterns among individual countries and country clusters.

We consider multiple safety measures in relation to the COVID-19 virus and look at their adoption levels for a variety of 15 individual countries, based on data from Yougov.co.uk. Subsequently, we establish correlation coefficients between measure-specific uptake levels and Hofstede dimension scores for all countries considered. We notably find that Power Distance Index (PDI) and Individualism (IDV) have a considerable explanatory power. In addition, we carried out a Principal Components Analysis (PCA) and a cluster analysis to see whether the behavioural patterns across countries can be grouped, and which Hofstede dimensions correlate strongest with the two main components that follow from the PCA. The PCA provides further confirmation of PDI and IDV being the most important explanatory factors for the uptake of measures across countries. The cluster analysis, in turn, reveals four broad groups, which only partly coincide with the way that the mental image clustering scheme by Wursten (2019) allots countries into its respective clusters. Hence, this provides a basis to suggest that data-driven exercises like the ones from our paper can serve to adjust Wursten's intuitive scheme.

Networks in lockdown: The consequences of COVID-19 for social relationships and feelings of loneliness.

This paper studies social network changes during the COVID-19 crisis in the Netherlands and their relation to perceived loneliness for the younger and the older cohorts. Arguments from opportunity theory and social capital theory are used to formulate hypotheses on network changes during the pandemic. Core discussion networks and networks with practical helpers from two representative cohorts (18-35 years of age and 65+ years of age, n = 1342 participants in both waves) during the lockdown in May 2020 are compared with networks of the same respondents in May 2019. We find that networks became smaller and more focused on stronger ties, while weaker ties more often decayed. Feelings of loneliness incsreased on average for all respondents and in particular for those who live alone or have a disadvantaged socioeconomic position. Importantly, the decrease in the number of the practical helper network, that is, decline in relatively weaker ties, affects experiences of loneliness in both groups.

Safety, immunogenicity, efficacy, and acceptability of COVID-19 vaccination in people with multiple sclerosis: a narrative review.

In the last two years, a new severe acute respiratory syndrome coronavirus (SARS-CoV) infection has spread worldwide leading to the death of millions. Vaccination represents the key factor in the global strategy against this pandemic, but it also poses several problems, especially for vulnerable people such as patients with multiple sclerosis. In this review, we have briefly summarized the main findings of the safety, efficacy, and acceptability of Coronavirus Disease 2019 (COVID-19) vaccination for multiple sclerosis patients. Although the acceptability of COVID-19 vaccines has progressively increased in the last year, a small but significant part of patients with multiple sclerosis still has relevant concerns about vaccination that make them hesitant about receiving the COVID-19 vaccine. Overall, available data suggest that the COVID-19 vaccination is safe and effective in multiple sclerosis patients, even though some pharmacological treatments such as anti-CD20 therapies or sphingosine l-phosphate receptor modulators can reduce the immune response to vaccination. Accordingly, COVID-19 vaccination should be strongly recommended for people with multiple sclerosis and, in patients treated with anti-CD20 therapies and sphingosine l-phosphate receptor modulators, and clinicians should evaluate the appropriate timing for vaccine administration. Further studies are necessary to understand the role of cellular immunity in COVID-19 vaccination and the possible usefulness of booster jabs. On the other hand, it is mandatory to learn more about the reasons why people refuse vaccination. This would help to design a more effective communication campaign aimed at increasing vaccination coverage among vulnerable people.

Modeling COVID-19 hospital admissions and occupancy in the Netherlands.

We describe the models we built for predicting hospital admissions and bed occupancy of COVID-19 patients in the Netherlands. These models were used to make short-term decisions about transfers of patients between regions and for long-term policy making. For forecasting admissions we developed a new technique using linear programming. To predict occupancy we fitted residual lengths of stay and used results from queueing theory. Our models increased the accuracy of and trust in the predictions and helped manage the pandemic, minimizing the impact in terms of beds and maximizing remaining capacity for other types of care.

A privacy-preserving blockchain-based tracing model for virus-infected people in cloud.

The outbreak of COVID-19 has exposed the privacy of positive patients to the public, which will lead to violations of users' rights and even threaten their lives. A privacy-preserving scheme involving virus-infected positive patients is proposed by us. The traditional ciphertext policy attribute-based encryption (CP-ABE) has the features of enhanced plaintext security and fine-grained access control. However, the encryption process requires the high computational performance of the device, which puts a high strain on resource-limited devices. After semi-honest users successfully decrypt the data, they will get the real private data, which will cause serious privacy leakage problems. Traditional cloud-based data management architectures are extremely vulnerable in the face of various cyberattacks. To address the above challenges, a verifiable ABE scheme based on blockchain and local differential privacy is proposed, using LDP to perturb the original data locally to a certain extent to resist collusion attacks, outsourcing encryption and decryption to corresponding service providers to reduce the pressure on mobile terminals, and deploying smart contracts in combination with blockchain for fair execution by all parties to solve the problem of returning wrong search results in a semi-honest cloud server. Detailed security proofs are performed through the defined security goals, which shows that the proposed scheme is indeed privacy-protective. The experimental results show that the scheme is optimized in terms of data accuracy, computational overhead, storage performance, and fairness. In terms of efficiency, it greatly reduces the local load, enhances personal privacy protection, and has high practicality as well as reliability. As far as we know, it is the first case of applying the combination of LDP technology and blockchain to a tracing system, which not only mitigates poisoning attacks on user data, but also improves the accuracy of the data, thus making it easier to identify infected contacts and making a useful contribution to health prevention and control efforts.

Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive.

The study explores the dynamics of a COVID-19 epidemic in multiple susceptible populations, including the various stages of vaccination administration. In the model, there are eight human compartments: completely susceptible; susceptible with dose-1 vaccination; susceptible with dose-2 vaccination; susceptible with booster dose vaccination; exposed; infected with and without symptoms, and recovered compartments. The biological feasibility of the model is analysed. The threshold value, R 0 , is derived using the next-generation matrix. The stability analysis of the equilibrium points was performed locally and globally using the threshold parameter of the model. The conditions determining disease persistence is obtained. The model is subjected to sensitivity analysis, and the most sensitive parameters are identified. Also, MATLAB is used to verify the mathematical outcomes of the system's dynamic behaviour and suggests that necessary steps should be taken to keep the spread of the omicron variant infectious disease under control. The findings of this study could aid health officials in their efforts to combat the spread of COVID-19.

Rewriting the script: How COVID-19 affected the relation between intrinsic aspirations and depressive symptoms.

Self-determination theory proposes that intrinsic aspirations protect against negative mental health outcomes by satisfying people's basic psychological needs of autonomy, relatedness, and competence. The present study investigated this relationship using two four-wave prospective longitudinal studies which followed undergraduate students across the Canadian academic calendar (September to May). The first was conducted across 2018-19 and the second across 2019-20. By comparing these two samples, we examined whether baseline levels of intrinsic aspirations moderated the impact of the COVID-19 pandemic on the development of depressive symptoms. Three main findings emerged, the first being that students reported higher levels of depressive symptoms in Spring 2020 than in Spring 2019. Second, students with more intrinsic aspirations in the pre-pandemic sample (2018-19) experienced fewer depressive symptoms from December to May while students with more intrinsic aspirations in the pandemic sample (2019-20) experienced more depressive symptoms during this period. Lastly, the latter relationship was mediated by need frustration, whereby students with higher levels of intrinsic aspirations experienced greater need frustration during the pandemic year. Together, these findings suggest that although intrinsic aspirations typically protect against negative psychological outcomes, the unique need frustrating context of the pandemic made them a risk factor for depression.

Burnout and depression among anesthesiology trainees in the United States: An updated National Survey.

STUDY OBJECTIVE: A high prevalence of burnout, depression and suicidal ideation has been reported among anesthesiology trainees. Over the last decade, there has been a significant emphasis on the development of wellness programs in academic departments to mitigate the prevalence and effects of burnout during anesthesiology training. Therefore, we aimed to reevaluate the prevalence of burnout and depression in anesthesiology trainees in the United States. DESIGN: Cross-sectional survey. SETTING: Anesthesiology Department. PATIENTS: A nationally representative sample of 1000 anesthesiology trainees in the United States. MEASUREMENTS: A 33-item questionnaire consisting of 1) burnout, 2) depression, 3) job satisfaction, 4) family support, 5) work characteristics, 6) demographic factors, 7) self-reported errors, and 8) impact of COVID-19 pandemic. RESULTS: We received 384 responses. Twenty-four percent (91/384) of the respondents met the criteria for high burnout risk and 58/384 (15%) of the respondents screened positive for depression. Multivariable analysis revealed that: (1) hours per week > 70, (odds ratio [OR; 95% confidence interval {CI}] = 3.1 [1.4-6.8], P=0.005 and (2) overnight calls per month > 7 (OR [95% CI] = 2.5 [1.0- 6.0], P=0.03 were independent factors for increased odds of burnout whereas the presence of (3) married/domestic partnership (OR [95% CI} = 0.52 [0.32-0.85], P=0.01 was associated with lower odds of burnout and/or depression. Ten percent (4/40) of high burnout/depression residents reported that they often times fall short in the quality of care provided to patients compared to 0.36% (1/275) residents with low burnout/depression scores, P < 0.001. Similarly, 22% (9/40) of high burnout/depression residents reported that they often times did not have enough attention to their patients compared to 4% (11/275) residents with low burnout/depression scores, P < 0.001. CONCLUSIONS: We report a still concerning but significantly lower rate of burnout and depression in anesthesiology trainees than previously reported a decade ago. This suggests that efforts on wellness implemented by academic programs have positively impacted the work experience of anesthesia trainees.

Eco-friendly spectrophotometric methods for determination of remdesivir and favipiravir; the recently approved antivirals for COVID-19 treatment.

Remdesivir (REM) and Favipiravir (FAV) are recently approved antivirals prescribed in severely ill COVID-19 patients. Therefore, development of new, simple, rapid, sensitive, and selective methods for analysis of such drugs in their pharmaceutical formulations will be highly advantageous. Herein, we have developed different spectrophotometric methods for analysis of the studied analytes. Method I is based on direct spectrophotometric analysis of REM and FAV in ethanol at λmax 244 and 323 nm, respectively. For simultaneous quantitation of REM and FAV, methods II-V were followed. Method II is based on derivative spectrophotometry in which REM was determined in second-order derivative spectra at 248 nm (the zero-crossing wavelength for FAV), while FAV was measured in first-order derivative spectra at 337 nm (the zero-crossing point for REM). Method III is the dual-wavelength method in which spectral intensities were subtracted at 244-207 nm for REM and at 330-400 nm for FAV. Method IV is the ratio subtraction in which ratio spectra were obtained by a suitable divisor followed by subtraction of intensities at 272-340 nm and 335-222 nm for REM and FAV, respectively. Method V is the derivative ratio method in which the obtained ratio spectra in method IV were converted to first-order derivative and then REM and FAV were recorded at 280 and 340 nm, respectively. Calibration graphs were linear in the ranges of 1-10 µg/mL for REM through all methods and 1-20 µg/mL for FAV in methods I and II, and 2-20 µg/mL by the other methods. The evolved methods were applied to pharmaceutical dosage forms of REM and FAV. All the proposed methods were further applied to human plasma samples containing both drugs with acceptable mean recoveries.

Xuanfei Baidu formula alleviates impaired mitochondrial dynamics and activated NLRP3 inflammasome by repressing NF-κB and MAPK pathways in LPS-induced ALI and inflammation models.

BACKGROUND: Xuanfei Baidu Formula (XBF) is an effective traditional Chinese medicine (TCM) remedy for treating coronavirus disease 2019 (COVID-19) in China. This herbal medicine has shown effects in reducing clinical symptoms and shortening the average length of hospital stay for COVID-19 patients. Previous studies have demonstrated that XBF alleviates acute lung injury (ALI) by regulating macrophage-mediated immune inflammation, but the mechanisms of action remain elusive. PURPOSE: This study aimed to evaluate the lung-protective and anti-inflammatory effects of XBF and its underlying mechanisms. METHODS: Here, XBF's effects were investigated in an ALI mouse model induced by inhalation of atomized lipopolysaccharide (LPS). Besides, the LPS-induced inflammation model in RAW264.7 cells was used to clarify the underlying mechanisms of XBF against ALI. RESULTS: Our results showed that XBF treatment alleviated LPS-induced lung injury, as evidenced by reduced histopathological changes, pulmonary alveoli permeability, fibrosis, and apoptosis in the lung tissues. In addition, inflammation was alleviated as shown by decreased levels of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1ß in serum and bronchoalveolar lavage fluid (BALF), and reduced white blood cell (WBC) count in BALF. Furthermore, consistent with the in vivo assay, XBF inhibited LPS-induced inflammatory cytokines release and pro-inflammatory polarization in RAW264.7 cells. Mechanistically, XBF increased mitochondrial fusion by upregulating Mfn1 and attenuated NLRP3 inflammasome activation by repressing Casp11, respectively, to inhibit NF-κB and MAPK pathways, thus repressing pro-inflammatory macrophage polarization. CONCLUSION: In this study, we demonstrate that XBF exerts anti-ALI and -inflammatory effects by recovering mitochondrial dynamics and reducing inflammasome activation, providing a biological illustration of the clinical efficacy of XBF in treating COVID-19 patients.

Assessment of relationship between aging and contaminant-carryover for different filter layer of surgical mask under urban environmental stressors.

Abundant disposable surgical masks (SMs) remain in the environment and continue to age under urban environmental stressors. This study aimed to investigate the aging characteristics of SMs and the effect of different aged layers of SMs on phenanthrene (PHE), tylosin (TYL), and sulfamethazine (SMT) under two different urban environmental stressors (UV and ozone). The results show that UV exposure causes more severe aging of the SM layers than ozone. The middle layer, made of melt-brown fabric, has displayed the highest degree of aging due to its smaller diameter and mechanical strength. The two-dimensional correlation spectroscopy (2D-COS) analysis reveals the different aging sequences of functional groups and three layers in aged SMs under the two urban environmental stressors. Whether the SMs are aged or not, the adsorptions of three organic pollutants on SMs are positively correlated with the octanol-water partition coefficient. Furthermore, except for the dominant hydrophobic interaction, aged SMs can promote the adsorption of three organic pollutants by accessory interactions (hydrogen bonding and partition), depending on their structures. These findings highlight the environmental effects of new microplastic (MP) sources and coexisting pollutants under the influence of COVID-19, which is helpful in accurately evaluating the biological toxicity of SMs.

Neuro faces of beneficial T cells: essential in brain, impaired in aging and neurological diseases, and activated functionally by neurotransmitters and neuropeptides.

T cells are essential for a healthy life, performing continuously: immune surveillance, recognition, protection, activation, suppression, assistance, eradication, secretion, adhesion, migration, homing, communications, and additional tasks. This paper describes five aspects of normal beneficial T cells in the healthy or diseased brain. First, normal beneficial T cells are essential for normal healthy brain functions: cognition, spatial learning, memory, adult neurogenesis, and neuroprotection. T cells decrease secondary neuronal degeneration, increase neuronal survival after central nervous system (CNS) injury, and limit CNS inflammation and damage upon injury and infection. Second, while pathogenic T cells contribute to CNS disorders, recent studies, mostly in animal models, show that specific subpopulations of normal beneficial T cells have protective and regenerative effects in several neuroinflammatory and neurodegenerative diseases. These include Multiple Sclerosis (MS), Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), stroke, CNS trauma, chronic pain, and others. Both T cell-secreted molecules and direct cell-cell contacts deliver T cell neuroprotective, neuroregenerative and immunomodulatory effects. Third, normal beneficial T cells are abnormal, impaired, and dysfunctional in aging and multiple neurological diseases. Different T cell impairments are evident in aging, brain tumors (mainly Glioblastoma), severe viral infections (including COVID-19), chronic stress, major depression, schizophrenia, Parkinson's disease, Alzheimer's disease, ALS, MS, stroke, and other neuro-pathologies. The main detrimental mechanisms that impair T cell function are activation-induced cell death, exhaustion, senescence, and impaired T cell stemness. Fourth, several physiological neurotransmitters and neuropeptides induce by themselves multiple direct, potent, beneficial, and therapeutically-relevant effects on normal human T cells, via their receptors in T cells. This scientific field is called "Nerve-Driven Immunity". The main neurotransmitters and neuropeptides that induce directly activating and beneficial effects on naïve normal human T cells are: dopamine, glutamate, GnRH-II, neuropeptide Y, calcitonin gene-related peptide, and somatostatin. Fifth, "Personalized Adoptive Neuro-Immunotherapy". This is a novel unique cellular immunotherapy, based on the "Nerve-Driven Immunity" findings, which was recently designed and patented for safe and repeated rejuvenation, activation, and improvement of impaired and dysfunctional T cells of any person in need, by ex vivo exposure of the person's T cells to neurotransmitters and neuropeptides. Personalized adoptive neuro-immunotherapy includes an early ex vivo personalized diagnosis, and subsequent ex vivo → in vivo personalized adoptive therapy, tailored according to the diagnosis. The Personalized Adoptive Neuro-Immunotherapy has not yet been tested in humans, pending validation of safety and efficacy in clinical trials, especially in brain tumors, chronic infectious diseases, and aging, in which T cells are exhausted and/or senescent and dysfunctional.

An electrochemical paper-based hydrogel immunosensor to monitor serum cytokine for predicting the severity of COVID-19 patients.

Analysis of cytokines levels in human serum is critical as it can be a "symptom diagnostic biomarker" in COVID-19, giving real-time information about human health status. Here, we present the construction and performance of a low-price immunosensor (∼US$0.428 per test) based on microfluidic paper-based system to detect cytokine for predicting the health status of COVID-19 patients. Interleukin-6 (IL-6) was selected as the detection model for the close relationship between IL-6 and COVID-19. The assay, which we integrated into foldable paper system, leverages the magnetic immunoassay, the streptavidin-horseradish peroxidase (HRP) associated with tetramethyl benzidine/hydrogen peroxide (TMB/H2O2) to amplify the signal for electrochemical readout. To improve the sensitivity of cytokine detection, a hybrid of gold nanoparticles (AuNPs) and polypyrrole (PPy) hydrogel was modified on the working electrode to increase the conductivity and improve the electron transfer rate. With our prototypic origami paper-based immunosensor operated in differential pulse voltammetry (DPV) mode, we achieved excellent results with a dynamic range from 5 to 1000 pg/mL and a lower detection limit (LOD) of 0.654 pg/mL. Furthermore, we evaluated the capability of the clinical application of the proposed immunosensor using human serum samples from a hospital. The results indicate that our proposed immunosensor has great potential in early diagnosing high-risk COVID-19 patients.

Dynamic variation and inhalation exposure of organophosphates esters and phthalic acid esters in face masks.

The coronavirus pandemic (COVID-19) has posed a huge global health threat since December 2019. Wearing face masks is known as an effective measure for controlling the wide spread of COVID-19 and its variants. But on the other hand, face masks could be a potential source of organophosphate esters (OPEs) and phthalic acid esters (PAEs) as they are extensively added in masks. However, knowledge associated with the occurrence as well as inhalation risks of OPEs and PAEs in masks is limited. In this study, OPEs and PAEs were determined in different types of mask samples collected from the local market. OPEs and PAEs were detected in mask samples ranging from 36.7 to 855 ng/g, and from 251 to 3830 ng/g, respectively. Relatively lower OPEs and PAEs concentrations were observed in disposable mask for toddlers. Simulated inhalation experiment indicated that the mass loss of OPEs and PAEs was 136 and 3910 ng/mask in disposable masks, 71.9 and 763 ng/mask in disposable mask for toddlers, 924 and 1020 ng/mask in N95 mask after 12 h, respectively. Significantly negative correlations were exhibited between the decrement of OPEs in masks and the increment of OPEs in corresponding polyurethane foams (PUFs) during the course, elucidating OPEs released from masks could be well captured by PUFs. With regard to the variation over time, predominant OPE and PAE analogues showed semblable release and absorption tendency in mask and corresponding PUF. Inhalation exposure risk of OPEs and PAEs was estimated based on the increment of pollutants in PUF. The estimated daily intakes (EDIs), hazard index (HI) and carcinogenic risk (CR) were also calculated and they were within the threshold levels. This study provides the evidence of OPEs and PAEs releasing from the face masks during wearing and unveiled a potential source of OPEs and PAEs exposure to humans.

Impact of COVID-19 on Croatian mariculture: Findings from the first national surveys.

An overview of the negative effects of the COVID-19 pandemic on the mariculture industry of the republic of Croatia is provided. An initial online survey was circulated early after the onset of the pandemic and a follow-up field survey was performed a year into the pandemic. The surveyed companies varied in size (micro to medium enterprises), location (north, central and southern coast) and cultured organism (European flat oyster, Mediterranean mussel, European sea bass, Gilthead sea bream and/or Bluefin tuna) and were asked questions on the subject of economic and job losses, aquaculture supply chain processes and implemented or proposed measures for mitigation of negative effects. Results from the online survey showed higher economic loss than job loss, but companies reported increased job loss in the period leading to the field survey. Most companies reported reductions in sales and avenues of procurement, which, in addition to direct stressors, indirectly affected business processes. Micro enterprises fared well due to their part-time nature, low capital investments and running costs, while small to medium enterprises were under the most pressure. Large enterprises were barely affected as they had secure local and/or international distribution chains and dominated the market. Producers most affected were those that relied on the HoReCa market for product placement and/or had difficulty coping with existing stressors. Bivalve producers generally experienced a higher drop in sales than finfish farms and companies with specialized production were not able to adapt to market changes to the degree that more versatile businesses seemed capable of.

Capacitive immunosensor for COVID-19 diagnosis.

COVID-19 has spread worldwide and early detection has been the key to controlling its propagation and preventing severe cases. However, diagnostic devices must be developed using different strategies to avoid a shortage of supplies needed for tests' fabrication caused by their large demand in pandemic situations. Furthermore, some tropical and subtropical countries are also facing epidemics of Dengue and Zika, viruses with similar symptoms in early stages and cross-reactivity in serological tests. Herein, we reported a qualitative immunosensor based on capacitive detection of spike proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. The sensor device exhibited a good signal-to-noise ratio (SNR) at 1 kHz frequency, with an absolute value of capacitance variation significantly smaller for Dengue and Zika NS1 proteins (|ΔC| = 1.5 ± 1.0 nF and 1.8 ± 1.0 nF, respectively) than for the spike protein (|ΔC| = 7.0 ± 1.8 nF). Under the optimized conditions, the established biosensor is able to indicate that the sample contains target proteins when |ΔC| > 3.8 nF, as determined by the cut-off value (CO). This immunosensor was developed using interdigitated electrodes which require a measurement system with a simple electrical circuit that can be miniaturized to enable point-of-care detection, offering an alternative for COVID-19 diagnosis, especially in areas where there is also a co-incidence of Zika and Dengue.

An optimization framework for COVID-19 vaccine allocation and inventory management: A case study.

As the novel coronavirus pandemic wreaked havoc globally, governments have implemented massive vaccination programs to tackle it. However, since the pandemic's emergence moves beyond the second year, some issues have stymied vaccination programs, including vaccine hesitancy, vaccine distribution inequality, new strains of the virus, and a possibility that the virus enters a stage of a requirement for cyclical vaccination. These challenges highlight the need for an appropriate mass COVID-19 vaccination program. Therefore, we attempt to address this problem by developing a bi-objective integrated vaccine allocation and inventory management framework. The goal is to minimize the system costs while maximizing the vaccination service level. Several important factors, such as multiple types of vaccines, the vaccines' perishability concept, demand uncertainty, and motivational strategy, have been addressed using dynamic planning. Besides that, the model development mechanism is carried out to be compatible and applicable to the current general vaccination program policies, forcing few strategic changes. Then, a case study concerning the vaccination program of the city of Mashhad in Iran is applied to the model. The results demonstrated significant advantages in total cost, vaccine shortage, and wastage compared to the current policy. Finally, the Lagrangian relaxation method is implemented on the model to strengthen further its capacity to handle larger-scale problems.

Turning waste into valuables: In situ deposition of polypyrrole on the obsolete mask for Cr(VI) removal and desalination.

The global mask consumption has been exacerbated because of the coronavirus disease 2019 (COVID-19) pandemic. Simultaneously, the traditional mask disposal methods (incineration and landfill) have caused serious environmental pollution and waste of resources. Herein, a simple and green mass-production method has been proposed to recycle carbon protective mask (CPM) into the carbon protective mask/polydopamine/polypyrrole (CPM/PDA/PPy) composite by in situ polymerization of PPy. The CPM/PDA/PPy composite was used for the removal of Cr(VI) and salt ions to produce clean water. The synergistic effect of PPy and the CPM improved the removal capability of Cr(VI). The CPM/PDA/PPy composite provided high adsorption capacity (358.68 mg g-1) and economic value (811.42 mg $-1). Consequently, the CPM/PDA/PPy (cathode) was combined with MnO2 (anode) for desalination in CDI cells, demonstrated excellent desalination capacity (26.65 mg g-1) and ultrafast salt adsorption rate (6.96 mg g-1 min-1), which was higher than conventional CDI cells. Our work proposes a new low-carbon strategy to recycle discarded masks and demonstrates their utilization in Cr(VI) removal and seawater desalination.

A novel rumor detection with multi-objective loss functions in online social networks.

COVID-19 quickly swept across the world, causing the consequent infodemic represented by the rumors that have brought immeasurable losses to the world. It is imminent to achieve rumor detection as quickly and accurately as possible. However, the existing methods either focus on the accuracy of rumor detection or set a fixed threshold to attain early detection that unfortunately cannot adapt to various rumors. In this paper, we focus on textual rumors in online social networks and propose a novel rumor detection method. We treat the detection time, accuracy and stability as the three training objectives, and continuously adjust and optimize this objective instead of using a fixed value during the entire training process, thereby enhancing its adaptability and universality. To improve the efficiency, we design a sliding interval to intercept the required data rather than using the entire sequence data. To solve the problem of hyperparameter selection brought by integration of multiple optimization objectives, a convex optimization method is utilized to avoid the huge computational cost of enumerations. Extensive experimental results demonstrate the effectiveness of the proposed method. Compared with state-of-art counterparts in three different datasets, the recognition accuracy is increased by an average of 7%, and the stability is improved by an average of 50%.

Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available.

A novel multi-attribute decision-making for ranking mobile payment services using online consumer reviews.

The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-payment) services. Consumer usage behavior towards m-payment services continues to increase due to access to usage experiences shared through online consumer reviews (OCRs). The proliferation of massive OCRs, coupled with quick and effective decisions concerning the evaluation and selection of m-payment services, is a practical issue for research. This paper develops a novel decision evaluation model that integrates OCRs and multi-attribute decision-making (MADM) with probabilistic linguistic information to identify m-payment usage attributes and utilize these attributes to evaluate and rank m-payment services. First and foremost, the attributes of m-payment usage discussed by consumers in OCRs are extracted using the Latent Dirichlet Allocation (LDA) topic modeling approach. These key attributes are used as the evaluation scales in the MADM. Based on an unsupervised sentiment algorithm, the sentiment scores of the text reviews regarding the attributes are calculated. We convert the sentiment scores into probabilistic linguistic elements based on the probabilistic linguistic term set (PLTS) theory and statistical analysis. Furthermore, we construct a novel technique known as probabilistic linguistic indifference threshold-based attribute ratio analysis (PL-ITARA) to discover the weight importance of the usage attributes. Subsequently, the positive and negative ideal-based PL-ELECTRE I methodology is proposed to evaluate and rank m-payment services. Finally, a case study on selecting appropriate m-payment services in Ghana is examined to authenticate the validity and applicability of our proposed decision evaluation methodology.

Energy-saving COVID-19 biomedical plastic waste treatment using the thermal - Catalytic pyrolysis.

The rate of Biomedical waste generation increases exponentially during infectious diseases, such as the SARS-CoV-2 virus, which burst in December 2019 and spread worldwide in a very short time, causing over 6 M casualties worldwide till May 2022. As per the WHO guidelines, the facemask has been used by every person to prevent the infection of the SARS-CoV-2 virus and discarded as biomedical waste. In the present work, a 3-ply facemask was chosen to be treated using the solvent, which was extracted from the different types of waste plastics through the thermal-catalytic pyrolysis process using a novel catalyst. The facemask was dispersed in the solvent in a heating process, followed by dissolution and precipitation of the facemask in the solvent and by filtration of the solid facemask residue out of the solvent. The effect of peak temperature, heating rate, and type of solvent is observed experimentally, and it found that the facemask was dissolved completely with a clear supernate in the solvent extracted from the (polypropylene + poly-ethylene) plastic also saved energy, while the solvent from ABS plastic was not capable to dissolute the facemask. The potential of the presented approach on the global level is also examined.

The effect of fear and situational motivation on online information avoidance: The case of COVID-19.

During the COVID-19 pandemic, a plethora of online sources for information and news dissemination have emerged. Extant research suggests that very quickly, individuals become disinterested and begin avoiding the information. In this study, we investigate how an individual's fear and situational motivation impact Online Information Avoidance. Using the self-determination theory and information avoidance theories, we argue that fear and external regulation are associated with increased Online Information Avoidance. We also argue that intrinsic motivation and identified regulation are associated with a decrease in Online Information Avoidance. Our findings suggest that fear, intrinsic motivation, and external regulation drive Online Information Avoidance, where intrinsic motivation is the most significant driver. We also found that identified regulation is a crucial inhibitor of Online Information Avoidance. While focusing on COVID-19, our study contributes to the broader information systems research literature and specifically to the information avoidance literature during a pandemic or a prolonged crisis. Our study's findings will be useful for governments, health organizations, and communities that utilize online platforms, forums, and related outlets to reach larger audiences for disseminating pertinent information and recommendations during a crisis.

In-situ fabrication of 3D interior hotspots templated with a protein@Au core-shell structure for label-free and on-site SERS detection of viral diseases.

Nanoscale plasmonic hotspots play a critical role in the enhancement of molecular Raman signals, enabling the sensitive and reliable trace analysis of biomedical molecules via surface-enhanced Raman spectroscopy (SERS). However, effective and label-free SERS diagnoses in practical fields remain challenging because of clinical samples' random adsorption and size mismatch with the nanoscale hotspots. Herein, we suggest a novel SERS strategy for interior hotspots templated with protein@Au core-shell nanostructures prepared via electrochemical one-pot Au deposition. The cytochrome c and lysates of SARS-CoV-2 (SLs) embedded in the interior hotspots were successfully functionalized to confine the electric fields and generate their optical fingerprint signals, respectively. Highly linear quantitative sensitivity was observed with the limit-of-detection value of 10-1 PFU/mL. The feasibility of detecting the targets in a bodily fluidic environment was also confirmed using the proposed templates with SLs in human saliva and nasopharyngeal swabs. These interior hotspots templated with the target analytes are highly desirable for early and on-site SERS diagnoses of infectious diseases without any labeling processes.

The SEIR model incorporating asymptomatic cases, behavioral measures, and lockdowns: Lesson learned from the COVID-19 flow in Sweden.

The Sweden approach is unique in handling the COVID-19 flow, compared to other European countries. While other countries have practiced the full lockdowns, Sweden has practiced the lighter lockdowns or the partial lockdowns as public spaces such as cafes and restaurants are allowed to serve their customers subject to government recommendations. This study aims to develop an SEIR model for Sweden capturing important issues such as the roles of behavioral measures, partial lockdowns, and undocumented cases. The suggested SEIR model is probably the first SEIR model capturing the roles of behavioral measures, partial lockdowns, hospital preparedness, and asymptomatic cases for Sweden. The SEIR model can successfully reproduce similar main observed outputs, namely documented infected cases and documented death cases. This study finds that the effects of partial lockdowns effectively start 52 days after the first confirmed case. Again, behavioral measures and partial lockdowns reduce possible infected cases about 22% and 70% respectively. This study also suggests that the Sweden government should step up to the full lockdowns by conducting public closures so COVID-19 flow can be curtailed significantly. Likewise, owing to airborne transmission, protecting vulnerable people such as senior citizens should be prioritised.

Screen media exposure and behavioral adjustment in early childhood during and after COVID-19 home lockdown periods.

There is ample evidence that young children's screen media use has sharply increased since the outbreak of the novel 2019 coronavirus disease (COVID-19). However, the long-term impact of these changes on children's adjustment is currently unclear. The goals of the current study were to assess longitudinal trajectories of young children's screen media exposure through a series of national COVID-19 home lockdowns and to examine the predictive associations between different aspects of media exposure and post-lockdown behavioral adjustment. Data were collected at four timepoints during and after home lockdown periods in Israel. Longitudinal data measuring various aspects of media use, behavioral conduct and emotional problems were gathered from a sample of 313 Israeli children (54% females) between the ages two to five years (Mage at T1 = 3.6), by surveying their mothers at 5 points in time. Child overall screen time use, exposure to background television, use of media to regulate child distress and maternal mobile device use all changed throughout the lockdown periods. Moreover, during lockdowns children's behavior problems were concurrently and positively correlated with screen time, use of media to regulate child distress, and exposure to background television. However, these were not longitudinally related to child behavior problems in the post-lockdown period. Possible implications for family media use during a public health crisis are discussed.

An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction.

The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection.

COVID-19 and finance scholarship: A systematic and bibliometric analysis.

COVID-19 has posed unprecedented challenges to global finances because of its unparalleled global scope, with both concomitant shocks as well as the likely altering of risk assessments and forecasts for the foreseeable future. As the effects of COVID-19 on financial markets and institutions have been widely addressed by various literature, we systematically synthesize this literature. Through a comprehensive search process, we extract and review 818 articles. Appling bibliometric methods, we explore the trends among various research constituents involved in the field. Using multi-dimensional scaling, we identify the intellectual structure of research in the domain and outline four distinct themes. We also identify the evolution and shifts in research within the short span of three years since the inception of COVID-19. Through detailed content analysis, various future research directions are proposed.

The role of capital structure management in maintaining the financial stability of hotel firms during the pandemic-A global investigation.

Due to the detrimental effects of the Covid-19 pandemic on the hotel sector, pandemic crisis management research has received lots of academic attention, from studies in sales-marketing to human resource management. However, financial management has been largely overlooked in the agenda of pandemic crisis management and hotel resilience. Therefore, this paper aims to address the research gap by exploring the role of capital structure management in maintaining financial stability and resilience capacities of hotel firms during this evolving and unpredictable Covid-19 pandemic. Using a database of 1882 firm-quarter observations of 196 hotel firms in 30 countries from Quarter 3 2018 to Quarter 2 2021, it is found that low debt capital structure mitigates the adverse impact of the pandemic on hotel firms' financial stability during this turbulent time; particularly the negative impacts caused by government restrictions on both domestic and international travel. The benefit of low debt levels is more pronounced for more vulnerable hotels such as small, less diversified, and slow growing hotel firms. Also, hotel firms that have less long-term debt are more financial stable and resilient during pandemic period. Research outcomes suggest that financial management, in particular capital structure policies should be a critical part of hotel resilience building and crisis management strategy for hotel firms.

Recurrent upper extremity arterial thrombosis preceding a diagnosis of COVID-19.

Arterial thrombosis occurs when there is endothelial damage in the setting of hypercoagulability and arterial blood stasis. COVID-19 has been theorized to cause both endothelial damage and promote hypercoagulability by causing an imbalance of clotting factors. In many studies, there have been a large proportion of COVID-19 patients that suffered a thromboembolic event, in both the venous and arterial systems. Our patient, who did not have a significant past medical history, presented with a recurrent brachial artery occlusion despite medical and surgical management, and subsequently tested positive for COVID-19 late in his admission. In conclusion, there is high suspicion that there is a relationship between COVID-19 infection and recurrent arterial thrombosis.

Using an experiential learning model to teach clinical reasoning theory and cognitive bias: an evaluation of a first-year medical student curriculum.

BACKGROUND: Most medical students entering clerkships have limited understanding of clinical reasoning concepts. The value of teaching theories of clinical reasoning and cognitive biases to first-year medical students is unknown. This study aimed to evaluate the value of explicitly teaching clinical reasoning theory and cognitive bias to first-year medical students. METHODS: Using Kolb's experiential learning model, we introduced dual process theory, script theory, and cognitive biases in teaching clinical reasoning to first-year medical students at an academic medical center in New York City between January and June 2020. Due to the COVID-19 pandemic, instruction was transitioned to a distance learning format in March 2020. The curriculum included a series of written clinical reasoning examinations with facilitated small group discussions. Written self-assessments prompted each student to reflect on the experience, draw conclusions about their clinical reasoning, and plan for future encounters involving clinical reasoning. We evaluated the value of the curriculum using mixed-methods to analyze faculty assessments, student self-assessment questionnaires, and an end-of-curriculum anonymous questionnaire eliciting student feedback. RESULTS: Among 318 total examinations of 106 students, 254 (80%) had a complete problem representation, while 199 (63%) of problem representations were considered concise. The most common cognitive biases described by students in their clinical reasoning were anchoring bias, availability bias, and premature closure. Four major themes emerged as valuable outcomes of the CREs as identified by students: (1) synthesis of medical knowledge; (2) enhanced ability to generate differential diagnoses; (3) development of self-efficacy related to clinical reasoning; (4) raised awareness of personal cognitive biases. CONCLUSIONS: We found that explicitly teaching clinical reasoning theory and cognitive biases using an experiential learning model provides first-year medical students with valuable opportunities for developing knowledge, skills, and self-efficacy related to clinical reasoning.

Efficacy and safety of Reyanning mixture in patients infected with SARS-CoV-2 Omicron variant: A prospective, open-label, randomized controlled trial.

BACKGROUND: A wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant rapidly resulted in a steep increase in the infected population and an overloaded healthcare system. Effective medications for Omicron are currently limited. The previous observational study supports the efficacy and safety of Reyanning (RYN) mixture in the treatment of coronavirus disease 2019 (COVID-19). PURPOSE: To evaluate the efficacy of RYN in asymptomatic and mildly infected patients with SARS-CoV-2 infection. STUDY DESIGN AND METHODS: This study was a prospective, open-label, randomized controlled trial. We consecutively recruited 2830 patients from Shanghai New International Expo Center mobile cabin hospital and randomized them in a 1:1 ratio to receive RYN plus standard care or receive standard care alone. The primary outcomes were the negative conversion of nucleic acid. Secondary outcomes included the hospital duration, new-onset symptoms, proportion of disease progression, and the viral load measured by the cycle threshold (Ct) value. RESULTS: A total of 1393 patients in the intervention group and 1407 patients in the control group completed the study. The negative conversion time of nucleic acid was significantly shortened in the intervention group (median: 6 d vs. 7 d, Hazard ratio: 0.768, 95CI %: 0.713-0.828, p < 0.0001). The negative conversion rate of nucleic acid was significantly higher in the intervention group (Day 3: 32.4% vs. 18.3%; Day7: 65.3% vs. 55.2%, p < 0.001). The hospitalization duration was significantly shortened in the intervention group (median: 8 d vs. 9 d, Hazard ratio: 0.759, 95% CI: 0.704-0.818, p < 0.0001). The proportion of new-onset fever (2.4% vs. 4.1%, p = 0.012), coughing (12.2% vs. 14.8%, p = 0.046), and expectoration (6.0% vs. 8.0%, p = 0.032) in the intervention group was significantly lower. RYN treatment increased Ct values and reduced the viral load. No disease progression and serious adverse events were reported during the study. CONCLUSION: RYN is a safe and effective treatment that can accelerate virus clearance and promote disease recovery in asymptomatic and mild Omicron infections.

The interplay among COVID-19 economic recovery, behavioural changes, and the European Green Deal: An energy-economic modelling perspective.

In the EU, COVID-19 and associated policy responses led to economy-wide disruptions and shifts in services demand, with considerable energy-system implications. The European Commission's response paved the way towards enhancing climate ambition through the European Green Deal. Understanding the interactions among environmental, social, and economic dimensions in climate action post-COVID thus emerged as a key challenge. This study disaggregates the implications of climate ambition, speed of economic recovery from COVID-19, and behavioural changes due to pandemic-related measures and/or environmental concerns for EU transition dynamics, over the next decade. It soft-links two large-scale energy-economy models, EU-TIMES and NEMESIS, to shed light on opportunities and challenges related to delivering on the EU's 2030 climate targets. Results indicate that half the effort required to reach the updated 55% emissions reduction target should come from electricity decarbonisation, followed by transport. Alongside a post-COVID return to normal, the European Green Deal may lead to increased carbon prices and fossil-fuel rebounds, but these risks may be mitigated by certain behavioural changes, gains from which in transport energy use would outweigh associated consumption increases in the residential sector. Finally, the EU recovery mechanism could deliver about half the required investments needed to deliver on the 2030 ambition.

[Association of SARS-CoV-2 infection and administration of COVID-19 vaccines with alterations in the menstrual cycle. Literature review]. / Asociación de la infección por SARS-CoV-2 y la administración de las vacunas contra la COVID-19 con alteraciones en el ciclo menstrual. Revisión de la literatura.

A number of factors can affect a woman's menstrual cycle, including diseases or drugs, such as COVID-19 disease and vaccinations. The aim of this review is to explore the studies published to date that have studied the presence of alterations that may be related to COVID-19 or vaccination against the SARS-CoV-2 virus.We conducted a review in the PubMed database, selecting 10 articles in which the menstrual cycle of adult women of childbearing age was studied, 3 of them in which the participants had been diagnosed with COVID-19 and 7 in which the participants had been vaccinated against the SARS-CoV-2 virus.Regarding COVID-19-related disturbances, 16%-47.2% of the participants presented a prolongation of their cycle, which was more frequent in those who reported more COVID-19 symptoms, and which normalised after 1-2 cycles.Regarding the alterations described after SARS-CoV-2 vaccination, 45%-78% of participants reported menstrual cycle alterations, with disparate results for the different parameters analysed, except that the alterations resolved in about 2 months.Both COVID-19 disease and vaccination appear to be associated with the occurrence of menstrual disturbances, which are limited in time and not severe. However, studies are scarce to date, and it is important to continue to develop studies that provide scientific evidence.

Digitalization and entrepreneurial firms' resilience to pandemic crises: Evidence from COVID-19 and the German Mittelstand.

While stressing the relevance of context, the organizational resilience literature has so far not extensively examined resilience in times of healthcare crises such as the ongoing COVID-19 pandemic. The Parasite Stress Theory of Values suggests that such pandemic crises have detrimental impacts on entrepreneurial activity due to social distancing and its effects on interaction, collaboration, and innovation. However, alternatives to personal contact now available thanks to digitalization, have not yet been examined. We expect entrepreneurial firms with more digitalized business models to show higher resilience to pandemic crises, especially those highly affected by globalization and more for non-family businesses than for family businesses. Based on a survey of German Mittelstand firms in the midst of the crisis induced by COVID-19, our findings broadly support our expectations and thus help qualify the Parasite Stress Theory of Values and contribute to a better understanding of organizational resilience in times of pandemic crises.

Masked face recognition with convolutional visual self-attention network.

With the global outbreak of COVID-19, wearing face masks has been actively introduced as an effective public measure to reduce the risk of virus infection. This measure leads to the failure of face recognition in many cases. Therefore, it is very necessary to improve the recognition performance of masked face recognition (MFR). Inspired by the successful application of self-attention in computer vision, we propose a Convolutional Visual Self-Attention Network (CVSAN), which uses self-attention to augment the convolution operator. Specifically, this is achieved by connecting a convolutional feature map, which enforces local features, to a self-attention feature map that is capable of modeling long-range dependencies. Since there is currently no publicly available large-scale masked face data, we generate a Masked VGGFace2 dataset based on the face detection algorithm to train the CVSAN model. Experiments show that the CVSAN algorithm significantly improves the performance of MFR compared to other algorithms.

Analysis on the thermal performance of low-temperature radiant floor coupled with intermittent stratum ventilation (LTR-ISV) for space heating.

With increasing energy use and outbreaks of respiratory infectious diseases (such as COVID-19) in buildings, there is a growing interest in creating healthy and energy-efficient indoor environments. A novel heating system named low-temperature radiant floor coupled with intermittent stratum ventilation (LTR-ISV) is proposed in this study. Thermal performance, indoor air quality, energy and exergy performance were investigated and compared with conventional radiant floor heating (CRFH) and conventional radiant floor heating with mixing ventilation (CRFH + MV). The results indicated that LTR-ISV had a more uniform operative temperature distribution and overall thermal sensation, and air mixing was enhanced without generating additional draft sensation. Compared with CRFH and CRFH + MV, the indoor CO2 concentration in LTR-ISV can be reduced by 1355 ppm and 400 ppm, respectively. Airborne transmission risk can also be reduced by 5.35 times. The coefficient of performance for CRFH, CRFH + MV, and LTR-ISV during working hours was 4.2, 2.5, and 3.4, respectively. The lower value of LTR-ISV was due to the high energy usage of the primary air handing unit. In the non-working hours, LTR-ISV was 0.6 and 1.3 higher compared to CRFH and CRFH + MV, respectively. The exergy efficiency of LTR-ISV, CRFH, and CRFH + MV was 81.77 %, 76.43 %, and 64.71 %, respectively. Therefore, the LTR-ISV system can meet the requirements of high indoor air quality and thermal comfort and provides a reference for the energy-saving use of low-grade energy in space heating.

COVID-19's effect on the spatial integration of fish markets: Evidence from carp price in China.

While curbing the spread of Coronavirus Disease 2019 (COVID-19), lockdown policies and "stay-at-home" restrictions caused massive supply chain disruptions worldwide. This led to breaks in spatial market integration, which could further lead to market inefficiency and resource misallocation. Taking daily price data from 2016 to 2021, this study investigates COVID-19's effect on the spatial market integration of fish in China using cointegration tests. We find a high degree of spatial market integration for fish in China before the COVID-19 pandemic. Further, our results show that COVID-19's effect on the spatial market integration of fish varies spatially in China. Specifically, COVID-19 reduces the degree of spatial market integration in most provinces, especially those with high infection rates. Meanwhile, the degree of spatial market integration in provinces with low infection rates remains high. Therefore, the government should be regionally specific when formulating market recovery policies.

CEO duality and firm performance during the 2020 coronavirus outbreak.

Stewardship theory suggests that CEO duality can provide strong leadership and facilitate the development and coordination of firm strategy. These benefits should affect firm risk and financial performance, particularly when the firm has high information-gathering costs. We use the 2020 coronavirus outbreak as a natural experiment to determine whether CEO duality is beneficial during crisis periods. We find that in 2020, S&P 1500 firms with CEO duality exhibit smaller increases in default probability risk than firms with non-duality in the presence of high information costs. Firms with CEO duality experience a smaller decrease in profitability when information costs are high. We also find that firms with CEO duality offer cumulative abnormal returns significantly higher than those of other firms. CEO duality is more valuable in firms with higher information costs. Our results indicate that CEO duality is valuable during crisis periods, particularly when information costs are high. These results are consistent with stewardship theory and indicate that the concentration of power from CEO duality is beneficial during crisis periods.

The impact of medical infrastructure on regional innovation: An empirical analysis of China's prefecture-level cities.

Because of public health emergencies, such as the COVID-19 pandemic, having an optimal medical infrastructure is an important way to maintain the normal operation of society and stimulate vitality in regional innovation. Based on the data on 260 cities at the prefecture level and above in China from 2001 to 2018, this paper investigates the characteristics and mechanisms of medical infrastructure on regional innovation. After a series of regressions, we robustly find that medical infrastructure has a significantly positive impact on regional innovation. In addition, based on the mediating effect model, the mechanism test shows that medical infrastructure can promote regional innovation through the channels of the natural population growth rate, educational level, and the environmental greening level. Finally, considering the urban heterogeneity, we find that the positive impact of medical infrastructure on regional innovation is reflected mainly in eastern and central cities, non-sub-provincial cities, and non-resource-based cities. These conclusions not only enrich the theoretical research on regional innovation from the perspective of medical infrastructure but also shed light on how to better promote regional innovation for China or even other countries.

Getting by with a little help from my friends? Expanding mentorship for career development and satisfaction.

Collaboration and teamwork are well-established cornerstones of modern clinical and academic medicine as well as research, including radiology. Mentorship is also part and parcel of daily medical practice and training. As it is, there is a wide range of opinions on the effectiveness of standard mentorship models. In some cases, academic departments may offer mentorship to fulfill a requirement rather than as a sign of commitment to ensuring that all mentees receive the guidance they seek. Although mentor-mentee relationships might have arisen organically, and such situations are still possible, the overall lack of face-to-face interactions in many departments in the COVID era suggests the need to emphasize formal mentoring programs. We appreciate the overall successes of mentorship in medicine as well as radiology, while acknowledging that, like anything, it is not perfect. Because the processes of decision making and career planning are similar across fields, a peer-to-peer cross-specialty mentorship model could yield untold benefits to early-career radiologists who may receive valuable advice from friends or colleagues outside of medicine, or simply outside of radiology, at crucial points in their careers. There is no ideal formula or format for mentoring, however. We endorse the theory or intentions of mentorship and believe that its effectiveness can take several forms. Having a formal program in place, with built-in flexibility to address our rapidly changing times, remains highly desirable. Our proposal is to expand this notion to a "whatever works," "anything goes," or, in the spirit of the COVID era, a hybrid model.

Loss, adaptation and growth: The experiences of creative arts therapists during the Covid-19 pandemic.

Since the outbreak of the COVID-19 pandemic in March 2020, mental health professionals have been called upon to cope with various challenges, including the shift to telehealth without prior training, overload in the workplace, increased risk of infection, and personal stressors relating to the pandemic. This article presents the qualitative findings of a larger international mixed-method study that explored the experiences of creative arts therapists around the globe during the first year of the pandemic (Feniger-Schaal et al., 2022). Twenty creative arts therapists were interviewed between July 2020 and March 2021. Transcriptions of the interviews were qualitatively analyzed through reflexive thematic analysis. Three main themes were identified: an experience of processing the losses caused by the pandemic, a restorative orientation that focused on adaptations the therapists made, and innovations that lead to personal and professional growth. Artistic engagement and creativity were found to be a resource when coping with losses and helped therapists adapt to the shift to tele-creative arts therapies (tele-CAT). Although this shift can lead to advances in the field of creative arts therapies, it requires further consideration, including the need for ethical guidelines, specific training, the development of digital methods that support the creative process, and dedicated supervision for therapists. The findings also point to the importance of psychological support to mitigate the burden therapists experience during stressful events.

Two in one: Overlapping CT findings of COVID-19 and underlying lung diseases.

Coronavirus disease 2019 (COVID-19) is associated with pneumonia and has various pulmonary manifestations on computed tomography (CT). Although COVID-19 pneumonia is usually seen as bilateral predominantly peripheral ground-glass opacities with or without consolidation, it can present with atypical radiological findings and resemble the imaging findings of other lung diseases. Diagnosis of COVID-19 pneumonia is much more challenging for both clinicians and radiologists in the presence of pre-existing lung disease. The imaging features of COVID-19 and underlying lung disease can overlap and obscure the findings of each other. Knowledge of the radiological findings of both diseases and possible complications, correct diagnosis, and multidisciplinary consensus play key roles in the appropriate management of diseases. In this pictorial review, the chest CT findings are presented of patients with underlying lung diseases and overlapping COVID-19 pneumonia and the various reasons for radiological lung abnormalities in these patients are discussed.

Longitudinal Postvaccine SARS-CoV-2 Immunoglobulin G Titers, Memory B-Cell Responses, and Risk of COVID-19 in Multiple Sclerosis Over 1 Year.

BACKGROUND AND OBJECTIVES: Some disease-modifying treatments impair response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in multiple sclerosis (MS), potentially increasing the risk of breakthrough infections. We aimed to investigate longitudinal SARS-CoV-2 antibody dynamics and memory B cells after 2 and 3 messenger RNA (mRNA) vaccine doses and their association with the risk of COVID-19 in patients with MS on different treatments over 1 year. METHODS: Prospective observational cohort study in patients with MS undergoing SARS-CoV-2 mRNA vaccinations. Antispike (anti-S) immunoglobulin G (IgG) titers were measured by chemiluminescence microparticle immunoassay. Frequencies of spike-specific memory B cells were measured on polyclonal stimulation of peripheral blood mononuclear cells and screening of secreted antibodies by ELISA. RESULTS: We recruited 120 patients with MS (58 on anti-CD20 antibodies, 9 on sphingosine 1-phosphate (S1P) receptor modulators, 15 on cladribine, 24 on teriflunomide (TFL), and 14 untreated) and collected 392 samples up to 10.8 months after 2 vaccine doses. When compared with untreated patients, anti-CD20 antibodies (ß = -2.07, p < 0.001) and S1P modulators (ß = -2.02, p < 0.001) were associated with lower anti-S IgG, while TFL and cladribine were not. Anti-S IgG decreased with months since vaccine (ß = -0.14, p < 0.001), independently of treatments. Within anti-CD20 patients, anti-S IgG remained higher in those with greater baseline B-cell counts and were not influenced by postvaccine anti-CD20 infusions. Anti-S IgG increase after a 3rd vaccine was mild on anti-CD20 and S1P modulators. Spike-specific memory B-cell responses were weaker on S1P modulators and anti-CD20 than on TFL and influenced by postvaccine anti-CD20 infusions. The frequency of breakthrough infections was comparable between DMTs, but the risk of COVID-19 was predicted by the last measured anti-S IgG titer before infection (OR = 0.56, 95% CI = 0.37-0.86, p = 0.008). DISCUSSION: Postvaccine anti-S IgG titers decrease over time regardless of MS treatment and are associated with breakthrough COVID-19. Both humoral and specific memory B-cell responses are diminished on S1P modulators. Within anti-CD20-treated patients, B-cell count at first vaccine determines anti-S IgG production, whereas postvaccine anti-CD20 infusions negatively affect spike-specific memory B cells.

Postconcussional Syndrome: Clinical Diagnosis and Treatment.

Diagnosis and treatment of postconcussional syndrome (PCS) is challenging because symptoms are vague, difficult to confirm, and attributable to other conditions. There are no uniformly accepted diagnostic PCS criteria. Clinical care largely focuses on symptom reduction and management. Moreover, the coronavirus disease 2019 (COVID-19) pandemic has increased the challenge because post-acute COVID-19 syndrome symptoms overlap with PCS. Future research should center on base rates of PCS-type symptoms in nonneurological samples and the identification and improved understanding of moderating variables contributing to the frequency, intensity, and duration of PCS symptoms.

Dysautonomia: Diagnosis and Management.

Dysautonomias are a heterogenous group of disorders that can cause variable symptoms ranging from isolated impairment of one autonomic function to multisystem failure. The causes are also diverse and can be central or peripheral and primary (owing to an intrinsic neurologic cause) or secondary (owing to a disorder that secondarily causes damage to the autonomic nervous system). This review covers common phenotypes of dysautonomias, primary and secondary causes, initial clinical workups, interpretation of common autonomic tests, and first-line treatments. A brief review of autonomic impairment associated with acute and long-COVID is also presented.

Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19.

The COVID-19 pandemic and subsequent public health restrictions led to a significant slump in economic activities around the globe. This slump has been met by various policy actions to cushion the detrimental socio-economic consequences of the COVID-19 crisis and eventually bring the economy back on track. We provide an ex-ante evaluation of the effectiveness of a massive expansion of RDI funding in Finland to stimulate post-crisis recovery growth through an increase in RDI activities of Finnish firms. We make use of the fact that novel RDI grants for firms in disruptive circumstances granted in 2020 were allocated through established RDI policy channels. This allows us to estimate the structural link between RDI funding and economic growth for Finnish NUTS-3 regions based on pre-COVID-19 data. Estimates are then used to predict regional recovery growth out of sample and to quantify the growth contribution of RDI funding. Depending on the chosen scenario, our out-of-sample predictions point to a mean recovery growth rate of GDP between ~2-4 % in 2021 after a decline of up to -2.5 % in 2020. RDI funding constitutes a significant pillar of the recovery process with mean contributions in terms of GDP growth of between 0.4 and 1 %-points.

The ecological impact of liquid chromatographic methods reported for bioanalysis of COVID-19 drug, hydroxychloroquine: Insights on greenness assessment.

Hydroxychloroquine is a drug that has been widely used during the early stages of COVID-19 pandemic. Different liquid chromatographic methods have been reported for the analysis of hydroxychloroquine in various biological matrices such as human plasma, serum, whole blood, oral fluid, rat plasma and tissues. In this comparative study, the most popular tools used for assessing the greenness profile: National Environmental Methods Index (NEMI), Eco-Scale Assessment (ESA), Green Analytical Procedure Index (GAPI) and Analytical Greenness metric (AGREE) were utilized to evaluate the ecological impact of eighteen liquid chromatographic methods developed for the bioanalysis of COVID-19 drug; hydroxychloroquine. NEMI is the simplest tool for evaluating the greenness profile of developed methods, but it is the least informative approach as all the reported methods had the same NEMI pictograms. On the other hand, GAPI is a dependable tool providing a complete picture about the method greenness starting from sampling until the final determination. ESA and AGREE tools are digitally presented and more easily applied. Therefore, their utilization for greenness assessment is highly recommended. Selection of the highest eco-friendly analytical procedure is of a paramount importance for protecting human health and the environment. Considering the greenness of the analytical procedures is highly recommended before proceeding to routine use in order to minimize the chemical hazards to the environment. The most eco-friendly analytical procedures for the analysis of hydroxychloroquine in biological samples according to ESA, GAPI and AGREE tools will be highlighted and discussed.

Three Nordic countries responding to COVID-19 - Eldercare perspectives.

Comparative international studies show that about half of the deceased in the COVID-19 pandemic were persons living in institutional and residential eldercare. As seniors are the most affected age group, we aim to study if and to what extent the eldercare services were included in the National Pandemic Plans, and how they were included in the response during the first phase of the pandemic in Finland, Iceland, and Sweden. We use the CRISMART approach to crisis documentation and analysis in comparing national response to the pandemic for the eldercare sector. The method enables comparison of extraordinary crisis situations from the decision-making and policy-making perspective. We found that there were both similarities and differences in the preparedness of the three Nordic countries, as well as in how they responded to the pandemic. In all three countries the focus of the national responses framed the problem as a health and healthcare services' problem. We also found value conflicts in the response between the value of protection versus social contact and self-determination and hence relating to the quality of eldercare. Keeping in mind the proportional increase of elderly people, care challenges, and future crises, we must strengthen the position of local social services within the emergency management systems to enhance disaster resilience and sustainability of our societies.

The impact of the COVID-19 outbreak on Japanese shipping industry: An event study approach.

This paper examines the stock market response of Japanese shipping firms on the COVID-19 outbreak. We adopt an event study method to investigate the announcement effect of COVID-19-related news such as the incident of largest numbers of cases in a cruise ship, the Princess Diamond on February 3, 2020 and the tight border closing by the Japanese Government on March 9, 2020. Our empirical results show that the negative abnormal returns are significant for both of these pessimistic COVID-19-related events. The negative return on the incident of Princess Diamond persisted for 30 trading days. Moreover, the negative abnormal return of port operations was stronger than maritime transportation after 30 days. Furthermore, we find that the tight border closing policy persisted for only eight trading days. Finally, we find that government policy responses are effective to mitigate negative announcement effects on COVID-related news post the tightened border control.

Determining factors affecting public bike ridership and its spatial change before and after COVID-19.

COVID-19, which has spread since late 2019, has caused drastic changes in transportation use. A few studies have already addressed the relationships between COVID-19 and transportation mode choice. However, in most cases, the analysis has been based on transit ridership during the early phases of the COVID-19 pandemic. In addition, few studies have focused on public bike use before and after COVID-19. This study examines the effect of COVID-19 on the ridership of public bikes and various determining factors of public bike use. An origin-destination (OD) analysis and spatial regression models were used with public bike ridership data from Seoul, Korea. The findings of the analysis can be summarized as follows. First, this study confirms that public parks have significantly influenced the increase in public bike ridership since the COVID-19 outbreak. This finding indicates that outdoor spaces such as riverside parks have played important roles in public bike ridership during the pandemic period. Second, this study finds that accessibility to subway stations strongly impacts the increase in public bike ridership. This means that the demand for public bikes as a connected transportation mode has increased since COVID-19. Third, access to bike lanes has had a significant impact on the increase in public bike ridership. This finding indicates the importance of expanding the public bike infrastructure network. Finally, this study makes policy proposals to promote public bike ridership during the COVID-19 pandemic.

The job of public transport, ride-hailing and delivery drivers: Conditions during the COVID-19 pandemic and implications for a post-pandemic future.

Transport workers were among the most affected by the COVID-19 crisis. In several countries, public transport and delivery drivers were considered essential workers during the pandemic, while the demand changed dramatically. In this context, little is known about the actual effects of the pandemic on the lives of drivers, and whether those effects depend on the type and formality of the corresponding job. In this paper, we analyse the impact of the pandemic on the daily jobs of public transport, ride-hailing, and delivery app drivers: we study changes on working time and income, pandemic-related concerns, and deterioration of job satisfaction, through a survey applied to drivers during the first peak of the pandemic in Santiago, Chile. Probit regressions on job satisfaction identify the main COVID-related experiences that explain variations in subjective perceptions. We then discuss the implications for post-pandemic job relationships, drivers' working conditions and urban mobility. We show that the unstable characteristics of app-based jobs sharpened during the pandemic: Public transport drivers have kept their jobs, with a similar income as in the pre-pandemic situation and keep their social security, whereas ride-hailing and delivery app drivers do not have social security. Several ride-hailing drivers lost their jobs without any compensation, while delivery drivers earn less money per hour, are more exhausted, and express the greatest concerns and largest decrease in their job satisfaction. The COVID-19 crisis has emphasized that the sustainability of post-pandemic passenger and delivery on-demand services needs to rely on formal job regulation and worker protection.

Children's excessive digital media use, mental health problems and the protective role of parenting during COVID-19.

COVID-19's outbreak in March 2020 and the social distancing measures that followed it changed the lives of children worldwide. Studies assessing the pandemic's implications for children have reported an alarming increase in the use of digital media (DM) and warned of its adverse impacts on children's functioning and development. The current study aimed to assess the relationship between excessive and problematic DM use and emotional, behavioral, and academic functioning among Israeli adolescents during COVID-19 and to identify adolescents at elevated risk of developing problematic DM use. Three hundred forty-seven Israeli parent-child dyads (M age = 11.81, SD = 1.41) separately completed measures assessing children's DM use (time and addiction), functioning (academic, social, emotional, and behavioral), behavioral dysregulation, and the parents' parenting practices. The results showed that DM addiction, but not DM use, was related to children's emotional, behavioral, and academic difficulties. Moreover, the results indicated that negative parenting and behavioral dysregulation increased the risk of DM addiction, which in turn increased emotional, behavioral, and academic difficulties. The results underscored parents' role in preventing problematic DM use and highlighted the need to treat DM use and problematic DM use as distinct constructs.

How new ways of working during COVID-19 affect employee well-being via technostress, need for recovery, and work engagement.

COVID-19 led to a surge in employees experiencing New Ways of Working (NWW), as many had to work from home supported by ICT. This paper studies how experiencing NWW during COVID-19 affected job-related affective well-being (JAWS) for a sample of employees of the Dutch working population. Hypotheses are tested using Preacher and Hayes' (Behav Res Methods 40 (3):879-891, 2008) bootstrap method, including technostress, need for recovery and work engagement as serial mediators. The results show that higher levels of NWW relate to higher JAWS, to more feelings of positive well-being (PAWS), and less feelings of negative well-being (NAWS). Much of these relations is indirect, via reduced technostress and need for recovery, and increased work engagement. Distinguishing the separate facets of NWW and their relations to PAWS/NAWS, the results show that NWW facets management of output, access to colleagues and access to information directly relate to less negative well-being. However, as the NWW facet time- and location-independent work negatively relates to feelings of positive well-being, NWW as a bundle of facets is not a set-and-forget strategy. Therefore, this study recommends that NWW be supplemented with regular monitoring of employees' well-being, technostress, need for recovery and work engagement.

PLFace: Progressive learning for face recognition with mask bias.

The outbreak of the COVID-19 coronavirus epidemic has promoted the development of masked face recognition (MFR). Nevertheless, the performance of regular face recognition is severely compromised when the MFR accuracy is blindly pursued. More facts indicate that MFR should be regarded as a mask bias of face recognition rather than an independent task. To mitigate mask bias, we propose a novel Progressive Learning Loss (PLFace) that achieves a progressive training strategy for deep face recognition to learn balanced performance for masked/mask-free faces recognition based on margin losses. Particularly, our PLFace adaptively adjusts the relative importance of masked and mask-free samples during different training stages. In the early stage of training, PLFace mainly learns the feature representations of mask-free samples. At this time, the regular sample embeddings shrink to the prototype. In the later stage of training, PLFace converges on mask-free samples and further focuses on masked samples until the masked sample embeddings are also gathered in the center of the class. The entire training process emphasizes the paradigm that normal samples shrink first and masked samples gather afterward. Extensive experimental results on popular regular and masked face benchmarks demonstrate the superiority of our PLFace over state-of-the-art competitors.

An automated multi-web platform voting framework to predict misleading information proliferated during COVID-19 outbreak using ensemble method.

The spreading of misleading information on social web platforms has fuelled massive panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. Previous studies mainly relied on a specific web platform to collect crucial evidence to detect fake content. The analysis identifies that retrieving clues from two or more different sources/web platforms gives more reliable prediction and confidence concerning a specific claim. This study proposed a novel multi-web platform voting framework that incorporates 4 sets of novel features: content, linguistic, similarity, and sentiments. The features have been gathered from each web-platforms to validate the news. To validate the fact/claim, a unique source platform is designed to collect relevant clues/headlines from two web platforms (YouTube, Google) based on specific queries and extracted features concerning each clue/headline. The proposed idea is to incorporate a unique platform to assist researchers in gathering relevant and vital evidence from diverse web platforms. After evaluation and validation, it has been identified that the built model is quite intelligent, gives promising results, and effectively predicts misleading information. The model correctly detected about 98% of the COVID misinformation on the constraint Covid-19 fake news dataset. Furthermore, it is observed that it is efficient to gather clues from multiple web platforms for more reliable predictions to validate the news. The suggested work depicts numerous practical applications for health policy-makers and practitioners that could be useful in safeguarding and implicating awareness among society from misleading information dissemination during this pandemic.

Large-scale evaluation of microorganism inactivation by bipolar ionization and photocatalytic devices.

The COVID-19 pandemic has raised awareness in the spread of disease via airborne transmission. As a result, there has been increasing interest in technologies that claim to reduce concentrations of airborne pathogens in indoor environments. The efficacy of many of these emerging technologies is not fully understood, and the testing that has been done is often conducted at a small scale and not representative of applied settings. There is currently no standard test method for evaluating air treatment technologies, making it difficult to compare results across studies or technology types. Here, a consistent testing approach in an operational-scale test chamber with a mock recirculating heating, ventilation, and air conditioning (HVAC) system was used to evaluate the efficacy of bipolar ionization and photocatalytic devices against the non-enveloped bacteriophage MS2 in the air and on surfaces. Statistically significant differences between replicate sets of technology tests and control tests (without technologies active) are apparent after 1 h, ranging to a maximum of 0.88 log10 reduction for the bipolar ionization tests and 1.8 log10 reduction for the photocatalytic device tests. It should be noted that ozone concentrations were elevated above background concentrations in the test chamber during the photocatalytic device testing. No significant differences were observed between control and technology tests in terms of the amount of MS2 deposited or inactivated on surfaces during testing. A standardized, large-scale testing approach, with replicate testing and time-matched control conditions, is necessary for contextualizing laboratory efficacy results, translating them to real-world conditions, and for facilitating technology comparisons.

National culture and the demand for physical money during the first year of the COVID-19 pandemic.

There was a significant increase in the demand for physical money during the COVID-19 pandemic. This stood in stark contrast to the decline in demand witnessed during previous pandemics. However, the change was not uniform and varied significantly between countries. By employing the "national culture" framework to identify the drivers of this variation, this study found that uncertainty avoidance, as well as social norms regarding gratification, played a major role. This suggests that some central banks should hold larger cash reserves to mitigate the risk of uncertainty and that the national culture framework may prove useful in researching the international differences in past, present, and future money demand.

Connectedness between Defi assets and equity markets during COVID-19: A sector analysis.

This paper explores the dynamic connectedness between Defi assets and sector stock markets focused around the COVID-19 pandemic crisis. For that aim, this research applies the TVP-VAR model, and it also computes the optimal weights and hedge ratios for the Defi assets-sector equity portfolios using the DCC-GARCH model. Our main findings reveal that static connectedness is slightly economy- and sector-dependent. Regarding the dynamic connectedness, as expected, the total spillover index changes over time, showing a cruel impact of the global pandemic declaration. Net spillover indices show relevant differences between the Defi assets and certain sectors (net receivers) and sectors such as industrials, materials and information technology (time-varying net transmitters). Finally, the optimal hedge ratios reveal similar levels of coverage in all the periods analyzed, with slight upturns in the cost of such coverage in the crisis period caused by COVID-19.

On the privacy of mental health apps: An empirical investigation and its implications for app development.

An increasing number of mental health services are now offered through mobile health (mHealth) systems, such as in mobile applications (apps). Although there is an unprecedented growth in the adoption of mental health services, partly due to the COVID-19 pandemic, concerns about data privacy risks due to security breaches are also increasing. Whilst some studies have analyzed mHealth apps from different angles, including security, there is relatively little evidence for data privacy issues that may exist in mHealth apps used for mental health services, whose recipients can be particularly vulnerable. This paper reports an empirical study aimed at systematically identifying and understanding data privacy incorporated in mental health apps. We analyzed 27 top-ranked mental health apps from Google Play Store. Our methodology enabled us to perform an in-depth privacy analysis of the apps, covering static and dynamic analysis, data sharing behaviour, server-side tests, privacy impact assessment requests, and privacy policy evaluation. Furthermore, we mapped the findings to the LINDDUN threat taxonomy, describing how threats manifest on the studied apps. The findings reveal important data privacy issues such as unnecessary permissions, insecure cryptography implementations, and leaks of personal data and credentials in logs and web requests. There is also a high risk of user profiling as the apps' development do not provide foolproof mechanisms against linkability, detectability and identifiability. Data sharing among 3rd-parties and advertisers in the current apps' ecosystem aggravates this situation. Based on the empirical findings of this study, we provide recommendations to be considered by different stakeholders of mHealth apps in general and apps developers in particular. We conclude that while developers ought to be more knowledgeable in considering and addressing privacy issues, users and health professionals can also play a role by demanding privacy-friendly apps. Supplementary Information: The online version contains supplementary material available at 10.1007/s10664-022-10236-0.

Investigation on the effectiveness of ventilation dilution on mitigating COVID-19 patients' secondary airway damage due to exposure to disinfectants.

Chlorine-containing disinfectants are widely used in hospitals to prevent hospital-acquired severe acute respiratory syndrome coronavirus 2 infection. Meanwhile, ventilation is a simple but effective means to maintain clean air. It is essential to explore the exposure level and health effects of coronavirus disease 2019 patients' inhalation exposure to by-products of chloride-containing disinfectants under frequent surface disinfection and understand the role of ventilation in mitigating subsequent airway damage. We determined ventilation dilution performance and indoor air quality of two intensive care unit wards of the largest temporary hospital constructed in China, Leishenshan Hospital. The chloride inhalation exposure levels, and health risks indicated by interleukin-6 and D-dimer test results of 32 patients were analysed. The mean ± standard deviation values of the outdoor air change rate in the two intensive care unit wards were 8.8 ± 1.5 h-1 (Intensive care unit 1) and 4.1 ± 1.4 h-1 (Intensive care unit 2). The median carbon dioxide and fine particulate matter concentrations were 480 ppm and 19 µg/m3 for intensive care unit 1, and 567 ppm and 21 µg/m3 for intensive care unit 2, all of which were around the average levels of those in permanent hospitals (579 ppm and 21 µg/m3). Of these patients, the median (lower quartile, upper quartile) chloride exposure time and calculated dose were 26.66 (2.89, 57.21) h and 0.357 (0.008, 1.317) mg, respectively. A statistically significant positive correlation was observed between interleukin-6 and D-dimer concentrations. To conclude, ventilation helped maintain ward air cleanliness and health risks were not observed.

Novel ciprofloxacin and norfloxacin-tetrazole hybrids as potential antibacterial and antiviral agents: Targeting S. aureus topoisomerase and SARS-CoV-2-MPro.

This study was designed to synthesize hybridizing molecules from ciprofloxacin and norfloxacin by enhancing their biological activity with tetrazoles. The synthesized compounds were investigated in the interaction with the target enzyme of fluoroquinolones (DNA gyrase) and COVID-19 main protease using molecular similarity, molecular docking, and QSAR studies. A QSAR study was carried out to explore the antibacterial activity of our compounds over Staphylococcus aureus a QSAR study, using descriptors obtained from the docking with DNA gyrase, in combination with steric type descriptors, was done obtaining suitable statistical parameters ( R 2 = 87.00 , Q L M O 2 = 71.67 , and Q E X T 2 = 73.49 ) to support our results. The binding interaction of our compounds with CoV-2-Mpro was done by molecular docking and were compared with different covalent and non-covalent inhibitors of this enzyme. For the docking studies we used several crystallographic structures of the CoV-2-Mpro. The interaction energy values and binding mode with several key residues, by our compounds, support the capability of them to be CoV-2-Mpro inhibitors. The characterization of the compounds was completed using FT-IR, 1H-NMR, 13C-NMR, 19F-NMR and HRMS spectroscopic methods. The results showed that compounds 1, 4, 5, 10 and 12 had the potential to be further studied as new antibacterial and antiviral compounds.

Acute Inflammatory Diseases of the Central Nervous System After SARS-CoV-2 Vaccination.

BACKGROUND AND OBJECTIVES: Acute inflammatory CNS diseases include neuromyelitis optica spectrum disorders (NMOSDs) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Both MOGAD and acute disseminated encephalomyelitis (ADEM) have been reported after vaccination. Consequently, the mass SARS-CoV-2 vaccination program could result in increased rates of these conditions. We described the features of patients presenting with new acute CNS demyelination resembling NMOSDs or MOGAD within 8 weeks of SARS-CoV-2 vaccination. METHODS: The study included a prospective case series of patients referred to highly specialized NMOSD services in the UK from the introduction of SARS-CoV-2 vaccination program up to May 2022. Twenty-five patients presented with new optic neuritis (ON) and/or transverse myelitis (TM) ± other CNS inflammation within 8 weeks of vaccination with either AstraZeneca (ChAdOx1S) or Pfizer (BNT162b2) vaccines. Their clinical records and paraclinical investigations including MRI scans were reviewed. Serologic testing for antibodies to myelin oligodendrocyte glycoprotein (MOG) and aquaporin 4 (AQP4) was performed using live cell-based assays. Patients' outcomes were graded good, moderate, or poor based on the last clinical assessment. RESULTS: Of 25 patients identified (median age 38 years, 14 female), 12 (48%) had MOG antibodies (MOGIgG+), 2 (8%) had aquaporin 4 antibodies (AQP4IgG+), and 11 (44%) had neither. Twelve of 14 (86%) antibody-positive patients received the ChAdOx1S vaccine. MOGIgG+ patients presented most commonly with TM (10/12, 83%), frequently in combination with ADEM-like brain/brainstem lesions (6/12, 50%). Transverse myelitis was longitudinally extensive in 7 of the 10 patients. A peak in new MOGAD cases in Spring 2021 was attributable to postvaccine cases. Both AQP4IgG+ patients presented with brain lesions and TM. Four of 6 (67%) seronegative ChAdOx1S recipients experienced longitudinally extensive TM (LETM) compared with 1 of 5 (20%) of the BNT162b2 group, and facial nerve inflammation was reported only in ChAdOx1S recipients (2/5, 40%). Guillain-Barre syndrome was confirmed in 1 seronegative ChAdOx1S recipient and suspected in another. DISCUSSION: ChAdOx1S was associated with 12/14 antibody-positive cases, the majority MOGAD. MOGAD patients presented atypically, only 2 with isolated ON (1 after BNT162b2 vaccine) but with frequent ADEM-like brain lesions and LETM. Within the seronegative group, phenotypic differences were observed between ChAdOx1S and BNT162b2 recipients. These observations might support a causative role of the ChAdOx1S vaccine in inflammatory CNS disease and particularly MOGAD. Further study of this cohort could provide insights into vaccine-associated immunopathology.

The impact of COVID-19 and working from home on the workspace retained at the main location office space and the future use of satellite offices.

There exists a substantial amount of research on the impact that the COVID-19 pandemic has had on significant changes in the location at which work takes place, especially working from home (WFH). There has been, however, very little systematic consideration given to the relationship between the substantial increase in WFH and the responses taken by organisations in reviewing their office (workspace) capacity needs in the future, including a switch of the mix of utilising workspace in the main office(s) and satellite office locations. The main aim of this paper is to explore the extent to which levels of working from home and increased use of rented satellite office space will be linked to changes in the amount of workspace required at the main office that was used pre-COVID-19. Using data from 459 businesses for three periods for pre-COVID-19, April 2022 (25 months after the outbreak of the pandemic) and stated intentions for 2023, we develop a random effects regression model for the Greater Sydney Metropolitan Area in which we identify some of the influences on the downsizing or not of the main office(s) work space, and comment on what we see as the most likely scenario for WFH and work space in the main office and rented satellite office space under the 'next normal'. The findings can be used to inform future commuting travel as well as changes in land use activity at specific locations, including possible reallocation of existing office space to other activity uses.

Voltammetric determination of Molnupiravir used in treatment of the COVID-19 at magnetite nanoparticle modified carbon paste electrode.

To reduce the progression of the viral process in patients infected with COVID-19, new treatments and drug active substances are needed. One of these drugs is Molnupiravir (MNP) which has a direct antiviral effect and has also proven to be highly effective in reducing the azopharyngeal SARS-CoV-2 infectious virus and viral RNA. Due to the importance and frequent use of this drug in the treatment of COVID-19, its accurate, quick, and cheap detection in pharmaceutical or biological samples is crucial. In this work, electrochemical behavior and sensitive voltammetric determination of MNP are described using a magnetite nanoparticle modified carbon paste electrode (Fe3O4@CPE) for the first time. Fe3O4 nanoparticles (NPs) were characterized by recording their transmission electron microscopy (TEM) images, energy dispersive X-ray (EDX), and X-ray diffraction (XRD) spectra. Cyclic voltammetric measurements showed that MNP was irreversibly oxidized at Fe3O4@CPE at 760 mV in pH 2.0 Britton Robinson buffer solution (BRBS). The peak current of MNP was increased approximately threefold at Fe3O4@CPE compared to bare CPE due to a good electrocatalytic efficiency of Fe3O4 NPs. According to differential pulse voltammetric studies, the fabricated electrode exhibited a linear range (LR) between 0.25 and 750 µM with sensitivity and limit of detection (LOD) of 4591.0 µA mM-1 cm-2 and 0.05 µM, respectively. On the other hand, although lower sensitivity (327.3 µA mM-1 cm-2) was obtained from CV compared to DPV, a wider linear calibration curve between 0.25 and 1500 µM was obtained in CV. Studies performed in tablet samples confirmed that the Fe3O4@CPE exhibits high applicability for selective and accurate voltammetric determination of MNP in real samples.

Integration of machine learning prediction and heuristic optimization for mask delivery in COVID-19.

The novel coronavirus pneumonia (COVID-19) has created huge demands for medical masks that need to be delivered to a lot of demand points to protect citizens. The efficiency of delivery is critical to the prevention and control of the epidemic. However, the huge demands for masks and massive number of demand points scattered make the problem highly complex. Moreover, the actual demands are often obtained late, and hence the time duration for solution calculation and mask delivery is often very limited. Based on our practical experience of medical mask delivery in response to COVID-19 in China, we present a hybrid machine learning and heuristic optimization method, which uses a deep learning model to predict the demand of each region, schedules first-echelon vehicles to pre-distribute the predicted number of masks from depot(s) to regional facilities in advance, reassigns demand points among different regions to balance the deviations of predicted demands from actual demands, and finally routes second-echelon vehicles to efficiently deliver masks to the demand points in each region. For the subproblems of demand point reassignment and two-batch routing whose complexities are significantly lower, we propose variable neighborhood tabu search heuristics to efficiently solve them. Application of the proposed method in emergency mask delivery in three megacities in China during the peak of COVID-19 demonstrated its significant performance advantages over other methods without pre-distribution or reassignment. We also discuss key success factors and lessons learned to facilitate the extension of our method to a wider range of problems.

Cov-TransNet: Dual branch fusion network with transformer for COVID-19 infection segmentation.

Segmentation of COVID-19 infection is a challenging task due to the blurred boundaries and low contrast between the infected and the non-infected areas in COVID-19 CT images, especially for small infection regions. COV-TransNet is presented to achieve high-precision segmentation of COVID-19 infection regions in this paper. The proposed segmentation network is composed of the auxiliary branch and the backbone branch. The auxiliary branch network adopts transformer to provide global information, helping the convolution layers in backbone branch to learn specific local features better. A multi-scale feature attention module is introduced to capture contextual information and adaptively enhance feature representations. Specially, a high internal resolution is maintained during the attention calculation process. Moreover, feature activation module can effectively reduce the loss of valid information during sampling. The proposed network can take full advantage of different depth and multi-scale features to achieve high sensitivity for identifying lesions of varied sizes and locations. We experiment on several datasets of the COVID-19 lesion segmentation task, including COVID-19-CT-Seg, UESTC-COVID-19, MosMedData and COVID-19-MedSeg. Comprehensive results demonstrate that COV-TransNet outperforms the existing state-of-the-art segmentation methods and achieves better segmentation performance for multi-scale lesions.

Student academic performance in non-lecture physiology topics following the abrupt change from traditional on-site teaching to online teaching during COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, pre-clerkship medical education, including all physiology classes, was obliged to change to online teaching due to limitations of on-site (face-to-face) classes. However, the effectiveness of online teaching in non-lecture physiology topics during the COVID-19 pandemic has not been thoroughly investigated. METHOD: We conducted a prospective study to evaluate the students' academic achievement and opinions on online teaching during the COVID-19 academic year. Academic achievement of 312 students in the COVID-19 year was compared with that of 299 students in the pre-COVID-19 year. Student opinions regarding social interactions and the preferred learning method were also collected. RESULTS: We found that student academic achievement in the non-lecture physiology topics, assessed by summative scores, was 4.80±0.92 percent higher in the pre-COVID-19 year than in the COVID-19 year (P < 0.01, Cohen's d = 0.42). Students rated that online classes tended to reduce their interactions with peers and teachers; however, students preferred online learning over traditional on-site learning. CONCLUSIONS: This study pointed out that students' academic performance related to the physiology topics taught by online non-lecture methods during the COVID-19 pandemic was lower than their performance when the topics were taught by the traditional (on-site) methods, although students reported that they preferred the online teaching. Hence, we suggest that medical teachers should deliberately plan and utilise a variety of tools and techniques when developing online non-lecture classes to preserve the interactivity of the classes, which might overcome this gap in students' academic performance.

Implications of time and space factors related with youth substance use prevention: a conceptual review and case study of the Icelandic Prevention Model being implemented in the context of the COVID-19 pandemic.

PURPOSE: This research examines the implementation of the Icelandic Prevention Model (IPM) in Canada to identify opportunities revealed by the COVID-19 pandemic to re-design our social eco-system to promote wellbeing. This paper has two objectives: 1) to provide a conceptual review of research that applies the bioecological model to youth substance use prevention with a focus on the concepts of time and physical space use and 2) to describe a case study that examines the implementation of the IPM in Canada within the context of the COVID-19 pandemic. METHOD: Study data were collected through semi-structured qualitative interviews with key stakeholders involved in implementing the IPM. RESULTS: Findings are organized within three over-arching themes derived from a thematic analysis: 1) Issues that influence time and space use patterns and youth substance use, 2) Family and community cohesion and influences on developmental context and time use and 3) Opportunities presented by the pandemic that can promote youth wellbeing. CONCLUSION: We apply the findings to research on the IPM as well as the pandemic to examine opportunities that may support primary prevention and overall youth wellbeing. We use the concepts of time and space as a foundation to discuss implications for policy and practice going forward.

The effect of government support on Bureaucracy, COVID-19 resilience and export intensity: Evidence from North Africa.

The literature on the imperativeness of government support for firm survival since the onset of COVID-19 is vast, but scholars have scarcely considered the impact of such assistance on managers' time, nor the extent to which support measures induce resilience and export activity. Accordingly, this study assesses the impact of government support on (1) bureaucracy and (2) resilience using data from 535 Moroccan SMEs. It further evaluates the influence of resilience on direct versus indirect exports, and espouses the institutional voids, resource-based and strategy-creation view to explain the associations through a contingency lens. The results demonstrate that (1) government support increases bureaucracy which, (2) surprisingly triggers and enhances resilience. Furthermore, (3) resilience has a positive impact on direct exports but (4) adversely affects indirect exports. Theoretically, the findings acquiesce extant calls for measurement specificity in export performance. Practically, stakeholders' attention is drawn to the value of managers' time well spent.

Quantitative resilience assessment of the network-level metro rail service's responses to the COVID-19 pandemic.

The metro rail system has proven to be the most efficient high-capacity carriers. During the unprecedented coronavirus disease 2019 (COVID-19) challenge, non-pharmaceutical interventions become a widely adopted strategy to limit physical movements and interactions. For situational awareness and decision support, data-driven analytics about serviceability are invaluable to metro agencies and decision-makers of cities. This paper presents a data-driven analytical framework that quantitatively evaluates COVID-19-caused resilience performance of metro rails. Several characteristics (e.g., vulnerability, robustness, rapidity, and degree to return) of the metro system's responses to the disturbance were identified and modeled with multivariate multiple regression. The applicability and rationality of the resilience evaluation model were validated by the metro transit data of the United States. The preliminary results disclosed that metro rail transit encountered more vulnerability (90.6%) in passenger trips than motorbus and light rail (around 70%). A set of statistical models were employed to disentangle the effect of socio-demographic variables and COVID-19-related factors on the metro transit. The disclosed emerging knowledge of resilience provides an in-depth understanding of mobility trends for the public and time-sensitive decision support for the policy effects, to further improve the service and management of the metro system under the spread of the epidemic.

Modeling the impact of child vaccination (5-11 y) on overall COVID-19 related hospitalizations and mortality in a context of omicron variant predominance and different vaccination coverage paces in Brazil.

Background: Developing countries have experienced significant COVID-19 disease burden. With the emergence of new variants, particularly omicron, the disease burden in children has increased. When the first COVID-19 vaccine was approved for use in children aged 5-11 years of age, very few countries recommended vaccination due to limited risk-benefit evidence for vaccination of this population. In Brazil, ranking second in the global COVID-19 death toll, the childhood COVID-19 disease burden increased significantly in early 2022. This prompted a risk-benefit assessment of the introduction and scaling-up of COVID-19 vaccination of children. Methods: To estimate the potential impact of vaccinating children aged 5-11 years with mRNA-based COVID-19 vaccine in the context of omicron dominance, we developed a discrete-time SEIR-like model stratified in age groups, considering a three-month time horizon. We considered three scenarios: No vaccination, slow, and maximum vaccination paces. In each scenario, we estimated the potential reduction in total COVID-19 cases, hospitalizations, deaths, hospitalization costs, and potential years of life lost, considering the absence of vaccination as the base-case scenario. Findings: We estimated that vaccinating at a maximum pace could prevent, between mid-January and April 2022, about 26,000 COVID-19 hospitalizations, and 4200 deaths in all age groups; of which 5400 hospitalizations and 410 deaths in children aged 5-11 years. Continuing vaccination at a slow/current pace would prevent 1450 deaths and 9700 COVID-19 hospitalizations in all age groups in this same time period; of which 180 deaths and 2390 hospitalizations in children only. Interpretation: Maximum vaccination of children results in a significant reduction of COVID-19 hospitalizations and deaths and should be enforced in developing countries with significant disease incidence in children. Funding: This manuscript was funded by the Brazilian Council for Scientific and Technology Development (CNPq - Process # 402834/2020-8).

Optimal Ensemble learning model for COVID-19 detection using chest X-ray images.

COVID-19 pandemic is the main outbreak in the world, which has shown a bad impact on people's lives in more than 150 countries. The major steps in fighting COVID-19 are identifying the affected patients as early as possible and locating them with special care. Images from radiology and radiography are among the most effective tools for determining a patient's ailment. Recent studies have shown detailed abnormalities of affected patients with COVID-19 in the chest radiograms. The purpose of this work is to present a COVID-19 detection system with three key steps: "(i) preprocessing, (ii) Feature extraction, (iii) Classification." Originally, the input image is given to the preprocessing step as its input, extracting the deep features and texture features from the preprocessed image. Particularly, it extracts the deep features by inceptionv3. Then, the features like proposed Local Vector Patterns (LVP) and Local Binary Pattern (LBP) are extracted from the preprocessed image. Moreover, the extracted features are subjected to the proposed ensemble model based classification phase, including Support Vector Machine (SVM), Convolutional Neural Network (CNN), Optimized Neural Network (NN), and Random Forest (RF). A novel Self Adaptive Kill Herd Optimization (SAKHO) approach is used to properly tune the weight of NN to improve classification accuracy and precision. The performance of the proposed method is then compared to the performance of the conventional approaches using a variety of metrics, including recall, FNR, MCC, FDR, Thread score, FPR, precision, FOR, accuracy, specificity, NPV, FMS, and sensitivity, accordingly.

Interference reduction isothermal nucleic acid amplification strategy for COVID-19 variant detection.

Common reference methods for COVID-19 variant diagnosis include viral sequencing and PCR-based methods. However, sequencing is tedious, expensive, and time-consuming, while PCR-based methods have high risk of insensitive detection in variant-prone regions and are susceptible to potential background signal interference in biological samples. Here, we report a loop-mediated interference reduction isothermal nucleic acid amplification (LM-IR-INA) strategy for highly sensitive single-base mutation detection in viral variants. This strategy exploits the advantages of nicking endonuclease-mediated isothermal amplification, luminescent iridium(III) probes, and time-resolved emission spectroscopy (TRES). Using the LM-IR-INA strategy, we established a luminescence platform for diagnosing COVID-19 D796Y single-base substitution detection with a detection limit of 2.01 × 105 copies/µL in a linear range of 6.01 × 105 to 3.76 × 108 copies/µL and an excellent specificity with a variant/wild-type ratio of significantly less than 0.0625%. The developed TRES-based method was also successfully applied to detect D796Y single-base substitution sequence in complicated biological samples, including throat and blood, and was a superior to steady-state technique. LM-IR-INA was also demonstrated for detecting the single-base substitution D614G as well as the multiple-base mutation H69/V70del without mutual interference, indicating that this approach has the potential to be used as a universal viral variant detection strategy.

CRISPR-Cas12a coupled with universal gold nanoparticle strand-displacement probe for rapid and sensitive visual SARS-CoV-2 detection.

Point of care (POC) diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are particularly significant for preventing transmission of coronavirus disease 2019 (COVID-19) by any user at any given time and place. CRISPR/Cas-assisted SARS-CoV-2 assays are viewed as supplemental to RT-PCR due to simple operation, convenient use and low cost. However, most current CRISPR molecular diagnostics based on fluorescence measurement increased the difficulty of POC test with need of the additional light sources. Some instrument-free visual detection with the naked eye has limitations in probe universality. Herein, we developed a universal, rapid, sensitive and specific SARS-CoV-2 POC test that combines the outstanding DNase activity of Cas12a with universal AuNPs strand-displacement probe. The oligo trigger, which is the switch the AuNPs of the strand-displacement probe, is declined as a result of Cas12a recognition and digestion. The amount of released AuNPs produced color change which can be visual with the naked eye and assessed by UV-Vis spectrometer for quantitative detection. Furthermore, a low-cost hand warmer is used as an incubator for the visual assay, enabling an instrument-free, visual SARS-CoV-2 detection within 20 min. A real coronavirus GX/P2V instead of SARS-CoV-2 were chosen for practical application validation. After rapid virus RNA extraction and RT-PCR amplification, a minimum of 2.7 × 102 copies/mL was obtained successfully. The modular design can be applied to many nucleic acid detection applications, such as viruses, bacteria, species, etc., by simply modifying the crRNA, showing great potential in POC diagnosis.

The choice between business travel and video conferencing after COVID-19 - Insights from a choice experiment among frequent travelers.

COVID-19 has accelerated the substitution of videoconferencing for business travel. However, little research exists about the decision-making behavior of business travelers considering virtual alternatives. We fill this gap by reconceptualizing the decision-making process and investigating the fundamental choice between face-to-face (FtF) and virtual communication (VC) using an adaptive choice-based conjoint analysis. We argue that the process of decision making of business travelers is distinct to that of leisure travelers, as the fundamental decision between FtF and VC occurs prior to subsequent travel decisions. We show that the purpose of the meeting, the character of the message, and the location of the meeting are the decision attributes of greatest importance. Using a novel methodology we present a holistic decision model that increases the theoretical understanding of business traveler decision-making and provide practitioners with comprehensive insights relevant to travel policy development, and executives in the business travel market with guidance with management decisions.

Antecedent, behaviour, and consequence (a-b-c) of deploying the contact tracing app in response to COVID-19: Evidence from Europe.

In response to the current coronavirus (COVID-19) pandemic, countries have or intend to deploy contact tracing apps as a way of containing and or reducing the community spread of the virus. Whilst a few studies have so far been conducted on the acceptability of the app, little is known about the antecedent, behaviour, and consequence (a-b-c) of deploying the app and its success thereof. This study, therefore, proposes and validates an integrated a-b-c and technology acceptance model of deploying the contract tracing app in four European countries. The study adopts a quantitative approach and uses publicly available cross country survey data from the Center for Open Science. An extract of 2512 data is analysed using SEM-PLS. The results confirmed the integrated a-b-c and technology acceptance model that underpins the study and revealed that the chance of achieving a positive outcome with citizens complying with recommendations of the app was only 17.1 % or R2 = 0.171 (±0.020) whilst the chance of negative consequent or deviant response of uninstallation of the app by the citizens was 54.3 % or R2 = 0.543 (±0.021). The results have huge implications for governments and public health institutions in their attempt to deploy the contract tracing app.

How can infectious medical waste be forecasted and transported during the COVID-19 pandemic? A hybrid two-stage method.

The COVID-19 pandemic has caused an unforeseen collapse of infectious medical waste (IMW) and an abrupt smite of the conveying chain. Hospitals and related treatment centers face great challenges during the pandemic because mismanagement may lead to more severe life threats and enlarge environmental pollution. Opportune forecasting and transportation route optimization, therefore, are crucial to coping with social stress meritoriously. All related hospitals and medical waste treatment centers (MWTCs) should make decisions in perspective to reduce the economic pressure and infection risk immensely. This study proposes a hybrid dynamic method, as follows: first to forecast confirmed cases via infectious disease modeling and analyze the association between IMW outflows and cases; next to construct a model through time-varying factors and the lagging factor to predict the waste quantity; and then to optimize the transportation network route from hospitals to MWTCs. For demonstration intentions, the established methodology is employed to an illustrative example. Based on the obtained results, in finding the process of decision making, cost becomes the common concern of decision-makers. Actually, the infection risk among publics has to be considered simultaneously. Therefore, realizing early warning and safe waste management has an immensely positive effect on epidemic stabilization and lifetime health.

Trace determination of the hydrogen sulfide biomarker thiosulfate in human urine by HPLC coupled with element selective ICPMS/MS detection.

Hydrogen sulfide is a toxic gas but also established as a naturally occurring gaseous signaling molecule in humans, playing key physiological roles with particular involvement in lung disease including COVID-19. Thiosulfate is the conventional biomarker of hydrogen sulfide and is excreted in human urine at low micromolar levels. Thiosulfate is amenable to detection by the element-selective inductively coupled plasma tandem mass spectrometry (ICPMS/MS), but sulfur speciation in human samples at trace levels is challenging due to the high complexity of human sulfur metabolome and the utility of this detector under such settings has not been demonstrated. We report a method for thiosulfate determination in human urine at trace physiological levels by HPLC-ICPMS/MS. The method involved one-step derivatization to improve chromatographic behavior followed by direct injection. The instrumental limit of detection was 1.4 µg S L-1 (0.02 µM or 0.1 pmol). In a group of samples from volunteers (n = 24), measured thiosulfate concentrations in the diluted urine matrix were down to 8.0 µg S L-1 with a signal-to-noise ratio >10. The method was validated for recovery (80-110%), repeatability (RSD% <5%), and linearity (r2 = 0.9999, at a tested working concentration range of 0.01-1.0 mg S L-1), and the accuracy was assessed by comparing with HPLC-ESIMS/MS which showed agreement within ±20%. This work demonstrates the applicability of HPLC-ICPMS/MS for sulfur speciation at trace levels in a matrix with complex sulfur metabolome as human urine and provides a sensitive method for the determination of the hydrogen sulfide biomarker.

COVID-19 subphenotypes at hospital admission are associated with mortality: a cross-sectional study.

BACKGROUND: We have an incomplete understanding of COVID-19 characteristics at hospital presentation and whether underlying subphenotypes are associated with clinical outcomes and therapeutic responses. METHODS: For this cross-sectional study, we extracted electronic health data from adults hospitalized between 1 March and 30 August 2020 with a PCR-confirmed diagnosis of COVID-19 at five New York City Hospitals. We obtained clinical and laboratory data from the first 24 h of the patient's hospitalization. Treatment with tocilizumab and convalescent plasma was assessed over hospitalization. The primary outcome was mortality; secondary outcomes included intubation, intensive care unit (ICU) admission and length of stay (LOS). First, we employed latent class analysis (LCA) to identify COVID-19 subphenotypes on admission without consideration of outcomes and assigned each patient to a subphenotype. We then performed robust Poisson regression to examine associations between COVID-19 subphenotype assignment and outcome. We explored whether the COVID-19 subphenotypes had a differential response to tocilizumab and convalescent plasma therapies. RESULTS: A total of 4620 patients were included. LCA identified six subphenotypes, which were distinct by level of inflammation, clinical and laboratory derangements and ranged from a hypoinflammatory subphenotype with the fewest derangements to a hyperinflammatory with multiorgan dysfunction subphenotypes. Multivariable regression analyses found differences in risk for mortality, intubation, ICU admission and LOS, as compared to the hypoinflammatory subphenotype. For example, in multivariable analyses the moderate inflammation with fever subphenotype had 3.29 times the risk of mortality (95% CI 2.05, 5.28), while the hyperinflammatory with multiorgan failure subphenotype had 17.87 times the risk of mortality (95% CI 11.56, 27.63), as compared to the hypoinflammatory subphenotype. Exploratory analyses suggested that subphenotypes may differential respond to convalescent plasma or tocilizumab therapy. CONCLUSION: COVID-19 subphenotype at hospital admission may predict risk for mortality, ICU admission and intubation and differential response to treatment.KEY MESSAGEThis cross-sectional study of COVID patients admitted to the Mount Sinai Health System, identified six distinct COVID subphenotypes on admission. Subphenotypes correlated with ICU admission, intubation, mortality and differential response to treatment.

Remotely Administered Resilience- and Wisdom-Focused Intervention to Reduce Perceived Stress and Loneliness: Pilot Controlled Clinical Trial in Older Adults.

OBJECTIVE: Older adults are vulnerable to perceived stress and loneliness, exacerbated by the COVID-19 pandemic. We previously reported inverse relationships between loneliness/perceived stress and wisdom/resilience. There are few evidence-based tele-health interventions for older adults. We tested a new remotely-administered manualized resilience- and wisdom-focused behavioral intervention to reduce perceived stress and loneliness in older adults. METHODS: This pilot controlled clinical trial used a multiple-phase-change single-case experimental design, with three successive 6-week phases: control, intervention, and follow-up periods. The intervention included six once-a-week one-hour sessions. Participants were 20 adults >65 years, without dementia. RESULTS: All 20 participants completed every session. The study indicated feasibility and acceptability of the intervention. While the sample was too small for demonstrating efficacy, there was a reduction (small-to-medium effect size) in perceived stress and loneliness, and increase in resilience, happiness, and components of wisdom and positive perceptions of aging. CONCLUSION: These preliminary data support feasibility, acceptability, and possible efficacy of a remotely-administered resilience- and wisdom-focused intervention in older adults to reduce stress and loneliness.

"Don't Just Study our Distress, Do Something": Implementing and Evaluating a Modified Stepped-Care Model for Health Care Worker Mental Health During the COVID-19 Pandemic.

OBJECTIVE: Throughout the COVID-19 pandemic, there have been concerns about the mental health of health care workers (HCW). Although numerous studies have investigated the level of distress among HCW, few studies have explored programs to improve their mental well-being. In this paper, we describe the implementation and evaluation of a program to support the mental health of HCW at University Health Network (UHN), Canada's largest healthcare network. METHODS: Using a quality improvement approach, we conducted a needs assessment and then created and evaluated a modified stepped-care model to address HCW mental health during the pandemic. This included: online resources focused on psychoeducation and self-management, access to online support and psychotherapeutic groups, and self-referral for individual care from a psychologist or psychiatrist. We used ongoing mixed-methods evaluation, combining quantitative and qualitative analysis, to improve program quality. RESULTS: The program is ongoing, running continuously throughout the pandemic. We present data up to November 30, 2021. There were over 12,000 hits to the UHN's COVID mental health intranet web page, which included self-management resources and information on group support. One hundred and sixty-six people self-referred for individual psychological or psychiatric care. The mean wait time from referral to initial appointment was 5.4 days, with an average of seven appointments for each service user. The majority had moderate to severe symptoms of depression and anxiety at referral, with over 20% expressing thoughts of self-harm or suicide. Post-care user feedback, collected through self-report surveys and semistructured interviews, indicated that the program is effective and valued. CONCLUSIONS: Development of a high-quality internal mental health support for HCW program is feasible, effective, and highly valued. By using early and frequent feedback from multiple perspectives and stakeholders to address demand and implement changes responsively, the program was adjusted to meet HCW mental health needs as the pandemic evolved.

Qualitative Olfactory Dysfunction and COVID-19: An Evidence-Based Review with Recommendations for the Clinician.

BACKGROUND: Nearly 40% of patients who experience smell loss during SARS-CoV-2 infection may develop qualitative olfactory dysfunction, most commonly parosmia. Our evidence-based review summarizes the evolving literature and offers recommendations for the clinician on the management of patients experiencing parosmia associated with COVID-19. METHODS: We performed a systematic search using independent queries in PubMed, Embase, Ovid, and Cochrane databases, then categorized articles according to themes that emerged regarding epidemiology, effect on quality of life, disease progression, prognosis, pathophysiology, diagnosis, and treatment of parosmia. RESULTS: We identified 123 unique references meeting eligibility and performed title and abstract review with 2 independent reviewers, with 74 articles undergoing full-text review. An inductive approach to thematic development provided 7 central themes regarding qualitative olfactory dysfunction following COVID-19. CONCLUSIONS: While other respiratory viruses are known to cause qualitative olfactory disturbances, the incidence of parosmia following COVID-19 is notable, and correlates negatively with age. The presence of parosmia predicts persistent quantitative olfactory dysfunction. Onset can occur months after infection, and symptoms may persist for well over 7 months. Affected patients report increased anxiety and decreased quality of life. Structured olfactory training with essential oils is the preferred treatment, where parosmia predicts recovery of aspects of quantitative smell loss when undergoing training. There is limited evidence that nasal corticosteroids may accelerate recovery of olfactory function. Patients should be prepared for the possibility that symptoms may persist for years, and providers should guide them to resources for coping with their psychosocial burden.

Being a health care professional in the ICU serving patients with covid-19: A qualitative study.

BACKGROUND: The COVID-19 pandemic has placed a great deal of strain on healthcare providers across the world. There has been no research into the experiences of health care providers in Turkey caring for hospitalized patients with COVID-19 in the ICU. OBJECTIVES: To explain the experiences of health care providers who provide services to patients with Covid-19 in an intensive care unit. METHODS: This study used a phenomenological approach to recruit 15 participants (10 nurses and 5 physicians). The data was gathered through semi-structured in-depth interviews conducted face-to-face. RESULTS: The four primary themes that came up in the results were COVID-19: the unidentified enemy, front-line struggle, psychological struggle, and invasion of social life. CONCLUSION: During the epidemic, health care providers encountered several psychological, physical, social, and professional difficulties. All health care personnel must receive information and skills training on what to do in crisis and risk circumstances such as infectious disease, decision-making, anxiety management, and problem-solving during pandemics.

Influence of right ventricular structure and function on hospital outcomes in COVID-19 patients.

BACKGROUND: The impact of the right ventricular (RV) structure and function on the in-hospital outcomes in patients with COVID-19 infection has not been rigorously investigated. OBJECTIVES: The main aim of our study was to investigate in-hospital outcomes including mortality, ICU admission, mechanical ventilation, pressor support, associated with RV dilatation, and RV systolic dysfunction in COVID-19 patients without a history of pulmonary hypertension. METHODS: It was a single academic tertiary center, retrospective cohort study of 997 PCR-confirmed COVID-19 patients. One hundred ninty-four of those patients did not have a history of pulmonary hypertension and underwent transthoracic echocardiography at the request of the treating physicians for clinical indications. Clinical endpoints which included mortality, ICU admission, need for mechanical ventilation or pressor support were abstracted from the electronic charts. RESULTS: Patients' mean age was 68+/-16 years old and 42% of the study population were females. COPD was reported in 13% of the study population, whereas asthma was 10%, and CAD was 25%. The mean BMI was 29.8+/-9.5 kg/m2. Overall mortality was 27%, 46% in ICU patients, and 9% in the rest of the cohort. There were no significant differences in co-morbidities between expired patients and the survivors. A total of 19% of patients had evidence of RV dilatation and 17% manifested decreased RV systolic function. RV dilatation or decreased RV systolic function were noted in 24% of the total study population. RV dilatation was significantly more common in expired patients (15% vs 29%, p = 0.026) and was associated with increased mortality in patients treated in the ICU (HR 2.966, 95%CI 1.067-8.243, p = 0.037), who did not need require positive pressure ventilation, IV pressor support or acute hemodialysis. CONCLUSIONS: In hospitalized COVID-19 patients without a history of pulmonary hypertension, RV dilatation is associated with a 2-fold increase in inpatient mortality and a 3-fold increase in ICU mortality.