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The outbreak of COVID-19 pandemic in northern Taiwan led to the implementation of Level 3 alert measures during 2021 and thereby impacted the air quality significantly, which provided an unprecedented opportunity to better understand the control strategies on air pollutants in the future. This study investigated the variations in sources, chemical characteristics and human health risks of PM2.5 comprehensively. The PM2.5 mass concentrations decreased from pre-alert to Level 3 alert by 49.4%, and the inorganic ions, i.e., NH4+, NO3- and SO42-, dropped even more by 71%, 90% and 52%, respectively. Nonetheless, organic matter (OM) and elemental carbon (EC) simply decreased by 36% and 13%, which caused the chemical composition of PM2.5 to change so that the carbonaceous matter in PM2.5 dominated instead of the inorganic ions. Correlation-based hierarchical clustering analysis further showed that PM2.5 was clustered with carbonaceous matter during the Level 3 alert, while that clustered with inorganic ions during both pre-alert and post-alert periods. Moreover, 6 sources of PM2.5 were identified by positive matrix factorization (PMF), in which secondary nitrate (i.e., aging traffic aerosols) exhibited the most significant decrease and yet primary traffic-related emissions, dominated by carbonaceous matter, changed insignificantly. This implied that secondary traffic-related aerosols could be easily controlled when traffic volume declined, while primary traffic source needs more efforts in the future, especially for the reduction of carbonaceous matter. Therefore, cleaner energy for vehicles is still needed. Assessments of both carcinogenic risk and non-carcinogenic risk induced by the trace elements in PM2.5 showed insignificant decrease, which can be attributed to the factories that did not shut down during Level 3 alert. This study serves as a metric to underpin the mitigation strategies of air pollution in the future and highlights the importance of carbonaceous matter for the reduction in PM2.5.
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Context and aims. The purpose of the study was to examine the impact of environmental development in the seashore waters of Maluan Bay on the current situation of sustainable development of coastal villages. Methods. We used SPSS statistical software (ver. 26.0) to analyse the data with statistical verification, Student's t-test and ANOVA, the used the inverview method to solicit opinions on the questionnarie results, and, finally, conducted multivariate inspection and analysis to explore the results. Key results. The development of seashore waters can effectively enhance people's positive perceptions of the current economic, social, environmental and coastal ecological development, and increase their willingness to revisit and purchase property. Also, the insufficient number of security guards in villages can be improved, the environmental awareness of residents and their willingness to participate in decision-making can be enhanced. Conclusions and implications. Providing tourists with better tourism facilities, transportation, hotel and restaurant management and planning will increase leisure opportunities and solve environmental and waste problems such as in this scenic location. It will help achieve the goal of sustainable circular economy of water.
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The world immediately studied Coronavirus Disease 2019 (COVID-19) and raced towards fmding the cure and developing an effective treatment. An automated approach is needed to discover drug candidates and provide those data to facilitate clinical trials in saving time and only focusing on the candidates which potentially become the cure for COVID-19. We propose the Drug Candidates for the Prevention of COVID-19 (DCPC) Database. DCPC Database provides a list of candidates of potential drugs for the prevention of COVID-19 based on disease-drug associations which are automatically discovered from biomedical literature. DCPC database is an integrative structural database, which involves a chemical database repository, such as PubChem and DrugBank to ensure that drug compound candidates have a standard representation of compounds. The database provides keyword-chosen categories and a determination of minimum supported articles for search, a list of drug candidates in the sorted table followed by the detail for each candidate, and a download feature. The keyword category consists of three keywords, they are Chinese herbal compounds, Indian medicinal plants, and Indian medicinal plants & diabetic treatment herbs. Each candidate links to an article in the biomedical literature and to a page of the compound structure visualization. DCPC is freely available at https://dcpc.brin.go.id/dcpc/.
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The world immediately studied Coronavirus Disease 2019 (COVID-19) and raced towards finding the cure and developing an effective treatment. An automated approach is needed to discover drug candidates and provide those data to facilitate clinical trials in saving time and only focusing on the candidates which potentially become the cure for COVID-19. We propose the Drug Candidates for the Prevention of COVID-19 (DCPC) Database. DCPC Database provides a list of candidates of potential drugs for the prevention of COVID-19 based on disease-drug associations which are automatically discovered from biomedical literature. DCPC database is an integrative structural database, which involves a chemical database repository, such as PubChem and DrugBank to ensure that drug compound candidates have a standard representation of compounds. The database provides keyword-chosen categories and a determination of minimum supported articles for search, a list of drug candidates in the sorted table followed by the detail for each candidate, and a download feature. The keyword category consists of three keywords, they are Chinese herbal compounds, Indian medicinal plants/and Indian medicinal plants & diabetic treatment herbs. Each candidate links to an article in the biomedical literature and to a page of the compound structure visualization. DCPC is freely available at https://dcpc.brin.go.id/dcpc/. © 2022 IEEE.
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In addition to the effect that the COVID-19 pandemic has had on the physical and mental health of individuals, it has also led to a change in the mental and emotional state of many employees. Especially among businesses and private companies, which faced many restrictions due to the special conditions of the pandemic. Therefore, the present study aimed to design an artificial neural network with MLP technique to analyze the relationship between demographic variables, resilience, COVID-19 and burnout in start-ups in Iran. The research method was quantitative. Managers and employees of start-ups formed the statistical population of the study, based on the statistical sample size of the unlimited community, 384 of them were tested. For data gathering, standard questionnaires include of MBI-GS and BRCS and researcher-made questionnaire of stress caused by COVID-19 were used. The validity of the questionnaires was confirmed by a panel of experts and their reliability was confirmed by Cronbach’s alpha coefficient. The number of neurons in the input layer was equal to 10, the number of neurons in the 1st hidden layer was equal to 7, the number of neurons in the output layer was equal to 1, and the number of epochs was equal to 500. 70% of the data were used for training and 30% for testing. In the designed artificial neural network, all experiment data except one were correctly predicted and the obtained MAE error was less than 0.012%. Finally, he precision and correction of the presented model was confirmed by the obtained results. © 2022, Tech Science Press. All rights reserved.
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SESSION TITLE: Post-COVID-19 Outcomes SESSION TYPE: Rapid Fire Original Inv PRESENTED ON: 10/19/2022 11:15 am - 12:15 pm PURPOSE: Minority populations, including non-English language proficient individuals, experience a disproportionate burden of morbidity and mortality from COVID-19.1,2 While these same populations have historically experienced disparities in critical illness, less is known about disparities in post-acute care following critical illness3. Here, we investigate if non-English language proficiency is associated with differential access to dedicated post-COVID-19-clinic care among intensive care unit (ICU) survivors. METHODS: We retrospectively collected demographic (self-identified), clinical, and utilization data from electronic health records for all patients with COVID-19 admitted to an ICU at three Mass General Brigham hospitals between March 11-May 31, 2020. We performed multivariable logistic regression, adjusting for age, gender, race and ethnicity, insurance status, area deprivation index (a marker of geographic socioeconomic deprivation), medical comorbidities, and discharge destination, to examine if non-English language proficiency, defined as “Needs Interpreter” in the medical record, was associated with access to outpatient post-COVID care (composite of dedicated post-ICU pulmonary, neurology, or physical medicine and rehabilitation clinic visit). RESULTS: Of 481 patients in our cohort, 61% (n=292) survived to one month after hospital discharge. The majority (71.2%) were discharged to a facility. Within 12 months after discharge, most patients had at least one primary care visit (84.7%), but far fewer were seen in a dedicated post-COVID clinic (27.1%). In multivariable analyses, non-English language proficiency was associated with no difference in primary care follow up (adjusted OR = 0.83, 95% CI 0.30-2.25, p=0.71), but was associated with decreased odds of a dedicated post-COVID clinic visit (aOR = 0.73, 95% CI 0.61-0.87, p < 0.001). CONCLUSIONS: Although we identified no difference in access to primary care, non-English language proficiency was associated with decreased odds of visiting a dedicated post-COVID clinic. Further research is needed to understand the system, provider, and patient factors contributing to these disparities and how to decrease barriers to subspecialty care among non-English language proficient ICU survivors. CLINICAL IMPLICATIONS: As the number of COVID-19 critical illness survivors increase, it will become increasingly important to not only develop multi-disciplinary interventions to support their recovery, but also ensure equity in access to these services. In our cohort of ICU survivors, we identified no difference in access to primary care according to preferred language language, but decreased odds of access to post-COVID clinics among survivors with non English language proficiency, pointing towards a need for further research to understand and mitigate these disparities. DISCLOSURES: No relevant relationships by George Alba No relevant relationships by Lisa Bebell No relevant relationships by Leslie Chang No relevant relationships by Nupur Dandawate No relevant relationships by Alexander Gavralidis No relevant relationships by Patrick Gordan no disclosure on file for Kathryn Hibbert;No relevant relationships by Cher Huang No relevant relationships by Sirus Jesudasen no disclosure on file for Aran Kadar;no disclosure on file for Peggy Lai;No relevant relationships by Emily Moin No relevant relationships by Daniel Okin Consultant relationship with United Therapeutics Please note: 1 day Added 04/03/2022 by Alison Witkin, value=Consulting fee
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On analyzing the results of cell-based assays, we have previously shown that perilla (Perilla frutescens) leaf extract (PLE), a food supplement and orally deliverable traditional Chinese medicine approved by the Taiwan Food and Drug Administration, effectively inhibits SARS-CoV-2 by directly targeting virions. PLE was also found to modulate virus-induced cytokine expression levels. In this study, we explored the anti-SARS-CoV-2 activity of PLE in a hamster model by examining viral loads and virus-induced immunopathology in lung tissues. Experimental animals were intranasally challenged with different SARS-CoV-2 doses. Jugular blood samples and lung tissue specimens were obtained in the acute disease stage (3-4 post-infection days). As expected, SARS-CoV-2 induced lung inflammation and hemorrhagic effusions in the alveoli and perivascular areas;additionally, it increased the expression of several immune markers of lung injury - including lung Ki67-positive cells, Iba-1-positive macrophages, and myeloperoxidase-positive neutrophils. Virus-induced lung alterations were significantly attenuated by orally administered PLE. In addition, pretreatment of hamsters with PLE significantly reduced viral loads and immune marker expression. A purified active fraction of PLE was found to confer higher antiviral protection. Notably, PLE prevented SARS-CoV-2-induced increase in serum markers of liver and kidney function as well as the decrease in serum high-density lipoprotein and total cholesterol levels in a dose-dependent fashion. Differently from lung pathology, monitoring of serum biomarkers in Syrian hamsters may allow a more humane assessment of the novel drugs with potential anti-SARS-CoV-2 activity. Our results expand prior research by confirming that PLE may exert an in vivo therapeutic activity against SARS-CoV-2 by attenuating viral loads and lung tissue inflammation, which may pave the way for future clinical applications.
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The rampageous transmission of SARS-CoV-2 has been devastatingly impacting human life and public health since late 2019. The waves of pandemic events caused by distinct coronaviruses at present and over the past decades have prompted the need to develop broad-spectrum antiviral drugs against them. In this study, our Pentarlandir ultrapure and potent tannic acids (UPPTA) showed activities against two coronaviral strains, SARSCoV-2 and HCoV-OC43, the earliest-known coronaviruses. The mode of inhibition of Pentarlandir UPPTA is likely to act on 3-chymotrypsin-like protease (3CLpro) to prevent viral replication, as supported by results of biochemical analysis, a 3CLpro assay, and a "gain-of-function" 3CLpro overexpressed cell-based method. Even in the 3CLpro overexpressed environment, Pentarlandir UPPTA remained its antiviral characteristic. Utilizing cell-based virucidal and cytotoxicity assays, the 50% effective concentrations (EC50) and 50% cytotoxicity concentration (CC50) of Pentarlandir UPPTA were determined to be similar to 0.5 and 52.5 mu M against SARS-CoV-2, while they were 1.3 and 205.9 mu M against HCoV-OC43, respectively. In the pharmacokinetic studies, Pentarlandir UPPTA was distributable at a high level to the lung tissue with no accumulation in the body, although the distribution was affected by the food effect. With further investigation in toxicology, Pentarlandir UPPTA demonstrated an overall safe toxicology profile. Taking these findings together, Pentarlandir UPPTA is considered to be a safe and efficacious pancoronal antiviral drug candidate that has been advanced to clinical development.
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Background: Oncology Care Model (OCM) requires cancer programs to provide depression screening during each care episode to meet the quality measure benchmark of 85% screening rate. This quality improvement (QI) project aims to assess 1) key strategies to integrate systemwide depression screening into routine cancer care, and 2) early outcomes of depression screening implementation. Methods: A mixed method study design was used to assess strategies to implement routine depression screening in a southeast comprehensive cancer center between July 2019 and December 2020. Two top high-volume hematological oncology clinics that covers sixty percent of ambulatory care participated in the depression screening implementation. Data were collected using 1) depression screening completion rate during OCM performance periods, 2) needs assessment to identify barriers and facilitators of implementation, and 3) semi-structured interviews to assess staff and provider feedback on sustainable implementation strategies. Data were analyzed using descriptive analysis for quantitative outcomes and thematic analysis for qualitative outcomes. Results: A total of 64 hematological oncology providers (n = 22) and staff (n = 42) participated in the depression screening implementation training during three OCM performance periods. Depression screening rate of total ambulatory oncology care increased from 12% (OCM-PR 5, Jul-Dec 19), to 51% (OCM-PR 6, Jan-Jun 20) to 77% (OCM-PR 7, Jul-Dec 20) after the two top-volume clinics integrated depression screening into clinic intake process. Themes emerged from needs assessment revealed multi-level implementation strategies including 1) patient education and psycho-oncological care, 2) staff training and practice modification, 3) provider education & interdisciplinary Care, 4) leadership, administration, and staffing support, and 5) clinical informatics collaboration to build the infrastructure for integrating depression screen with clinic intake in the electronic medical record (EMR). Feedback from staff and provider interviews indicated high receptiveness and buy-in, especially during the COVID-19 pandemic to improve timely identification and triage of patients with depressive symptoms across all oncology care services. Conclusions: Depression screening is a key component of quality comprehensive cancer care that aims to provide timely identification and triage of cancer patients needing follow-up psychosocial care. Early implementation outcomes revealed significant improvement in depression screening completion rate after two clinics adopted depression screening into intake process. Further investigation is needed to refine system-wide implementation strategies across all ambulatory oncology sites and to assess long-term implementation outcomes meet the psychosocial care needs of cancer patients.
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The highly infectious and serious nature of coronavirus disease 2019 (COVID-19) has highlighted the need for hospital space disinfection technology and the prevention of human exposure to pathogenic environments. This research developed novel chlorine dioxide (ClO2) sterilization technology to reduce bacteria and viruses in the air and on surfaces. A smart sterilization robot system was also developed to spray disinfectants in operating theaters or patients' rooms, designed according to the results of controlled experiments and the requirements for hospital disinfection. The system was built incorporated a semi-automatic remote-controlled module and an automatic intelligent disinfection function;that is, it could operate independently according to specific epidemic prevention strategies, which were implemented using a combination of Internet of Things (IoT) applications and a gesture recognition function. The elimination of Escherichia coli (E. coli) bacteria on sample plates was 99.8 % effective. This paper reviews the evolution of various disinfection technologies and describes a disinfection robot system in detail.
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Purpose: The aims of this study are to (1) evaluate physicians and nurses' perspectives on patient safety culture amid the COVID-19 pandemic and (2) integrate the emotional exhaustion of physicians and nurses into an evaluation of patient safety culture to provide insights into appropriate implications for medical care. Design/methodology/approach: Patient safety culture was assessed with the Chinese version of the Safety Attitudes Questionnaire. Confirmatory factor analysis was conducted to validate the structure of the data (i.e. reliability and validity), and Pearson's correlation analysis was performed to identify relationships between safety-related dimensions. Findings: Safety climate was strongly associated with working conditions and teamwork climate. In addition, working conditions was highly correlated with perceptions of management and job satisfaction, respectively. It is worth noting that the stress and emotional exhaustion of the physicians and nurses during this epidemic were high and needed attention. Practical implications: For healthcare managers and practitioners, team-building activities, power of public opinions, IoT-focused service, and Employee Assistance Programs are important implications for inspiring the patient safety-oriented culture during the period of the COVID-19 pandemic. Originality/value: This paper considers the role of emotional state into patient safety instrument, a much less understood but equally important dimension in the field of patient safety. © 2021, Emerald Publishing Limited.
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In December 2019, the novel coronavirus 2019-nCoV, which has caused the latest public health emergency of international concern, began to spread with exponential speed around the whole world. To further the understanding of how media technologies contribute to knowledge management for a pandemic outbreak communication (POC), this paper, through Key-route main path analysis (MPA), investigates the research literature on POC. This paper found that studies on the main paths mainly focus on public cognition at the beginning and later the attention is transferred to how to fight against the outbreak and thus reveals the changing role of media technologies in knowledge management. To examine the dynamic structure of communication between government and public, this study relies on the “enactment” perspective to shed light on how the government makes sense of the media technologies and the circumstances of the pandemic to further knowledge management in POC. © Operational Research Society 2021.