Advances in approved nucleic acid drugs and lipid nanoparticle system.

Nucleic acids, as a next generation of biotechnology drugs, not only can fundamentally treat diseases, but also own significant platform characteristics in view of technology and production. Therefore, nucleic acid-based drugs have broad clinical applications in biomedical fields. However, nucleic acids are degradable and unstable, and have very low intracellular delivery efficiency in vitro and in vivo, which greatly limits their applications. In recent years, ionizable lipid-based lipid nanoparticles have shown promising application potentials and have been successfully applied to COVID-19 (Coronavirus Disease 2019) vaccines in clinic. Lipid nanoparticles demonstrate high in vivo delivery efficiency and good safety profile due to their unique structural and physicochemical properties, which provides many possibilities for their clinical applications for nucleic acid delivery in the future. This review focused on the characteristics of nucleic acid drugs and their delivery barriers, and discussed the approved nucleic acid drugs to illustrate the key aspects of the success of their delivery carrier system. In addition, problems to be solved in the field were highlighted.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.

Advances in approved nucleic acid drugs and lipid nanoparticle system

Nucleic acids, as a next generation of biotechnology drugs, not only can fundamentally treat diseases, but also own significant platform characteristics in view of technology and production. Therefore, nucleic acid-based drugs have broad clinical applications in biomedical fields. However, nucleic acids are degradable and unstable, and have very low intracellular delivery efficiency in vitro and in vivo, which greatly limits their applications. In recent years, ionizable lipid-based lipid nanoparticles have shown promising application potentials and have been successfully applied to COVID-19 (Coronavirus Disease 2019) vaccines in clinic. Lipid nanoparticles demonstrate high in vivo delivery efficiency and good safety profile due to their unique structural and physicochemical properties, which provides many possibilities for their clinical applications for nucleic acid delivery in the future. This review focused on the characteristics of nucleic acid drugs and their delivery barriers, and discussed the approved nucleic acid drugs to illustrate the key aspects of the success of their delivery carrier system. In addition, problems to be solved in the field were highlighted.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.

Redesigning Chronic Care delivery using Mobile Health Technology

Typical management of chronic conditions is through sporadic office visits. But health indicators (such as blood pressure) can fluctuate significantly within a day. The infrequent office visits, however, offer the provider little information about the medical history of the patient between office visits resulting in delayed and sometimes inappropriate interventions. Use of mobile health (mHealth) technology in clinical care can help make appropriate interventions at the patient's location before the worsening condition leads to costlier consequences. mHealth enables patients to remotely upload measurements and providers to continuously monitor these measurements and intervene if necessary. mHealth, therefore, results in bidirectional information flow between providers and patients, thereby reducing information asymmetry. Our study examines redesigning of chronic care delivery using mHealth. It is important to make sure the redesigned delivery process is both efficient (reduces cost) and effective (improves patient health). In this paper, we first present a big picture of the redesigned care delivery process. We then show how this delivery process can improve patient health by analyzing a panel dataset of 1627 patients. We examine the relationship between use of mobile health applications and quality of care delivery for hypertensive patients. We observe the blood pressure readings to decrease with frequency of app usage and time since adoption. With the use of mHealth apps increasing in the post COVID-19 era, our analysis indicates an efficient use of physician's time and an increased role for support-staff under the supervision of the physician. The chronic care delivery process can therefore be redesigned with the help of mHealth, improving patient health and reducing cost for both patients and providers. © 2023 IEEE Computer Society. All rights reserved.

[The predictive value of warning scores for intensive care unit admission in coronavirus disease 2019 patients].

To evaluate the predictive value of early warning scores for intensive care unit (ICU) admission in patients with coronavirus disease 2019 (COVID-19). For COVID-19 patients who were admitted to Shijiazhuang People's Hospital from January 2021 to February 2021, national early warning score (NEWS), national early warning score 2 (NEWS2), rapid emergency medicine score (REMS), quick sepsis-related organ failure (qSOFA), altered consciousness, blood urea nitrogen, respiratory rate, blood pressure, and age-65 (CURB-65) were used to evaluate the inpatient condition and the predictive value for ICU admission. A total of 368 patients were included, and 32 patients (8.7%) were transferred to the ICU. The median age was 49.0 (34.0,61.0) years. The scores of NEWS, NEWS2, REMS, and CURB-65 were 1 (0, 2), 1 (0, 2), 4 (2, 6) and 0 (0, 1), respectively. The receiver operating characteristic (ROC) cure (AUC) was used to evaluate the predictive value in detecting patients who are at risk of being transferred to the ICU. Area under the ROC AUC of NEWS was 0.756, sensitivity 65.6%, and specificity 71.3%. ROC AUC of NEWS2 was 0.732, sensitivity 62.5%, and specificity 61.3%. ROC AUC of REMS was 0.787, sensitivity 84.4%, and specificity 64.6%. ROC AUC of CURB-65 was 0.814, sensitivity 81.3%, and specificity 76.8%. The predictive value of NEWS and NEWS2 combined with age were significantly improved. The ROC AUC of NEWS combined with age was 0.885, sensitivity 85.1%, and specificity 75.0%. The ROC AUC of NEWS2 combined with age was 0.883, sensitivity 84.2%, and specificity 75.0%. NEWS and NEWS2 combined with age can be used as a predictive tool for whether COVID-19 patients will be admitted to the ICU.

Spatiotemporal characteristics of ozone and the formation sensitivity over the Fenwei Plain.

High surface ozone (O3) levels affect human and environmental health. The Fenwei Plain (FWP), one of the critical regions for China's "Blue Sky Protection Campaign", has reported severe O3 pollution. This study investigates the spatiotemporal properties and the causes of O3 pollution over the FWP using high-resolution data from the TROPOspheric Monitoring Instrument (TROPOMI) from 2019 to 2021. This study characterizes spatial and temporal variations in O3 concentration by linking O3 columns and surface monitoring using a trained deep forest machine learning model. O3 concentrations in summer were 2-3 times higher than those found in winter due to higher temperatures and greater solar irradiation. The spatial distributions of O3 correlate with the solar radiation showing decreased trends from the northeastern to the southwestern FWP, with the highest O3 values in Shanxi Province and the lowest in Shaanxi Province. For urban areas, croplands and grasslands, the O3 photochemistry in summer is NOx-limited or in the transitional regime, while it is VOC-limited in winter and other seasons. Reducing NOx emissions would be effective for decreasing O3 levels in summer, while VOC reductions are necessary for winter. The annual cycle in vegetated areas included both NOx-limited and transitional regimes, indicating the importance of NOx controls to protect ecosystems. The O3 response to limiting precursors shown here is of importance for optimizing control strategies and is illustrated by emission changes during the 2020 COVID-19 outbreak.

Global impact of the COVID-19 lockdown on surface concentration and health risk of atmospheric benzene

To curb the spread of the COVID-19 pandemic, many countries around the world imposed an unprecedented lockdown, producing reductions in pollutant emissions. Unfortunately, the lockdown-driven global ambient benzene changes still remain unknown. An ensemble machine-learning model coupled with chemical transport models (CTMs) was applied to estimate global high-resolution ambient benzene levels. Afterwards, the extreme gradient boosting (XGBoost) algorithm was employed to decouple the contributions of meteorology and emission reduction to ambient benzene. The change ratio (Pdew) of the deweathered benzene concentration from the pre-lockdown to lockdown period was in the order of India (-23.6 %) > Europe (-21.9 %) > the United States (-16.2 %) > China (-15.6 %). The detrended change (P∼-) of the deweathered benzene level (change ratio in 2020 - change ratio in 2019) followed the order of India (P∗=-16.2 %) > Europe (P∗=-13.9 %) > China (P∗=-13.3 %) > the United States (P∗=-6.00 %). Emission reductions derived from industrial activities and transportation were major drivers for the benzene decrease during the lockdown period. The highest decreasing ratio of ambient benzene in India might be associated with local serious benzene pollution during the business-as-usual period and restricted transportation after lockdown. Substantial decreases in atmospheric benzene levels had significant health benefits. The global average lifetime carcinogenic risk (LCR) and hazard index (HI) decreased from 4.89×10-7 and 5.90×10-3 to 4.51×10-7 and 5.40×10-3, respectively. China and India showed higher health benefits due to benzene pollution mitigation compared with other countries, highlighting the importance of benzene emission reduction. Copyright: © 2023 Chaohao Ling et al.

Extenics in Face Recognition

Face recognition is facing a new challenge, which was resulted from the contradiction between face recognition and the necessity to wear masks during the COVID-19. This article introduces extenics in face recognition (EFR) for solving the contradiction and constructs a facial model for psychology analysis to help the patients suffering from mental disorders. Moreover, a 2D-3D scene transformation model is integrated with EFR to fuse the virtual scene and real scene. Perspective fusions of EFR with EEG are also explained utilizing the five-layer intelligence theory for fighting against the COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

[Establishment and preliminary application of quantitative real-time PCR assay for the detection of SARS-CoV-2 subgenomic nucleocapsid RNA].

Objective: To establish a rapid and specific quantitative real-time PCR (qPCR) method for the detection of SARS-CoV-2 subgenomic nucleocapsid RNA (SgN) in patients with COVID-19 or environmental samples. Methods: The qPCR assay was established by designing specific primers and TaqMan probe based on the SARS-CoV-2 genomic sequence in Global Initiative of Sharing All Influenza Data (GISAID) database. The reaction conditions were optimized by using different annealing temperature, different primers and probe concentrations and the standard curve was established. Further, the specificity, sensitivity and repeatability were also assessed. The established SgN and genomic RNA (gRNA) qPCR assays were both applied to detect 21 environmental samples and 351 clinical samples containing 48 recovered patients. In the specimens with both positive gRNA and positive SgN, 25 specimens were inoculated on cells. Results: The primers and probes of SgN had good specificity for SARS-CoV-2. The minimum detection limit of the preliminarily established qPCR detection method for SgN was 1.5×102 copies/ml, with a coefficient of variation less than 1%. The positive rate of gRNA in 372 samples was 97.04% (361/372). The positive rates of SgN in positive environmental samples and positive clinical samples were 36.84% (7/19) and 49.42% (169/342), respectively. The positive rate and copy number of SgN in Wild strain were lower than those of SARS-CoV-2 Delta strain. Among the 25 SgN positive samples, 12 samples within 5 days of sampling time were all isolated with virus; 13 samples sampled for more than 12 days had no cytopathic effect. Conclusion: A qPCR method for the detection of SARS-CoV-2 SgN has been successfully established. The sensitivity, specificity and repeatability of this method are good.

Longitudinal Assessment for Anxiety and Depression among Frontline Medical Staff at a Specialized Hospital to Admit Patients with COVID-19

Longitudinal alterations of mental health problems still lack clarity among frontline medical staff treating patients with coronavirus disease 2019 (COVID-19). Mental health surveys were conducted from February 19 to 23 (n = 222), from March 3 to 10 (n = 364), from March 15 to 22 (n = 446), and from March 25 to April 3 (n = 174), 2020, of medical staff working at medical staff at a specializ ed hospital to admit patients with COVID-19 in China. The rate of reporting anxiety remained unchanged within 6 weeks, but the rate of reporting depression increased at week 3 and remained unchanged afterwards. Age was an independent risk factor for symptoms of anxiety and depression, and working days were independent risk factors for symptoms of depression. These results highlight the importance of dynamic assessment. Copyright © 2022, Universidade de Sao Paulo. Museu de Zoologia. All rights reserved.

Study on electron beam radiation sterilization process for disposable medical protective clothing

The outbreak of COVID-19 has led to a sharp increase in the demand for disposable medical protective clothing in the short term. In order to shorten the marketing cycle, a large number of domestic disposable medical protective clothing products have been sterilized by electron beam irradiation, which is more efficient than ethylene oxide sterilization. However, the performance of such clothing must adhere to strict requirements and the process parameters of this sterilization method still lack systematic data support. In order to ensure the reliability of electron beam sterilization of disposable medical protective clothing, research on a corresponding process was carried out. Typical disposable medical protective clothing available on the market made of polypropylene (PP) and coated with polyethylene (PE) was selected as the material studied. An appropriate method was selected to establish the corresponding sterilization dose with reference to the standard methods—“Disposable medical protective clothing irradiation sterilization emergency specification (temporary)”and“ISO 11137-2:2013 Sterilization of health care products—Radiation—Part 2: Establishing the sterilization dose.”The change in material properties after irradiation sterilization with different absorbed doses was studied. Based on the obtained parameters, an algorithm for the average absorbed dose on irradiation by an irradiation electron linac was proposed. Results showed that absorbed doses of 20.3 kGy and 31.5 kGy allowed the products to achieve sterility assurance levels of 10−3 and 10−6, respectively. The material performance of the products after irradiation at 25.0 kGy, 30.0 kGy and 35.0 kGy were able to meet national standard requirements such as elongation at break, breaking strength, impermeability, and filtration efficiency. Thus, a satisfactory electron beam irradiation sterilization process for medical disposable protective clothing has been established. © 2021 The authors.

Detecting False Claims in Low-Resource Regions: A Case Study of Caribbean Islands

The COVID-19 pandemic has created severe threats to global health control. In particular, misinformation circulated on social media and news outlets has undermined public trust in government and health agencies. This problem is further exacerbated in developing countries or low-resource regions where the news may not be equipped with abundant English fact-checking information. This poses a question: "are existing computational solutions toward misinformation also effective in low-resource regions?" In this paper, to answer this question, we make the first attempt to detect COVID 19 misinformation in English, Spanish, and Haitian French populated in the Caribbean region, using the fact-checked claims in US-English. We started by collecting a dataset of real & false claims in the Caribbean region. Then we trained several classification and language models on COVID-19 from high-resource language regions and transferred this knowledge to the Caribbean claim dataset. The experimental results show the limitations of current false claim detection in low-resource regions and encourage further research toward the detection of multi-lingual false claims in long tail.

Visualization Analysis of Spatiotemporal Data of COVID-19

Aiming at the problem of COVID-19 epidemic data visualization, this paper proposes a spatiotemporal visualization analysis method based on the technology of scraping crawler and visualization, and carries on the visualization analysis and research, intuitively shows the development and change of the epidemic situation in different countries and regions, and excavates its spatiotemporal variation rules. Firstly, we use scrapy crawler framework to collect COVID-19 epidemic data;then, the collected data were cleaned and processed to construct a spatiotemporal data set of COVID-19 epidemic;finally, pyecharts is used to analyze the dataset data visually. The results showed the changes and trends of epidemic situation in different countries and regions, and provided reference for epidemic prevention and control. © 2021 IEEE.

Practices of Using Blockchain Technology in e-Learning

The COVID-19 pandemic has led online learning mode to be extremely popular all over the world. It is conceivable that people will gradually adapt to the convenience and low-cost advantages of e-learning mode, even for a long time after the end of the pandemic. However, the e-learning mode has relatively low credibility in the traditional academic and degree certification education system. Applying blockchain technology on e-learning system can help to solve the lack of credit system in the education field. We propose a blockchain-enhanced e-learning ecosystem that can provide functions such as learning behavior recording, degree certificate verificating, courseware resource protecting, transaction book tracking, and cross-institutional recognizing of academic qualifications, which can effectively help build an online education credit system, for some major educational application scenarios, such as inter-institutional lifelong education, inter-disciplinary education, and modern vocational education system. © 2021 ACM.

Cross-lingual COVID-19 Fake News Detection

The COVID-19 pandemic poses a great threat to global public health. Meanwhile, there is massive misinformation associated with the pandemic which advocates unfounded or unscientific claims. Even major social media and news outlets have made an extra effort in debunking COVID-19 misinformation, most of the fact-checking information is in English, whereas some unmoderated COVID-19 misinformation is still circulating in other languages, threatening the health of less-informed people in immigrant communities and developing countries. In this paper, we make the first attempt to detect COVID-19 misinformation in a low-resource language (Chinese) only using the fact-checked news in a high-resource language (English). We start by curating a Chinese realfake news dataset according to existing fact-checking information. Then, we propose a deep learning framework named CrossFake to jointly encode the cross-lingual news body texts and capture the news content as much as possible. Empirical results on our dataset demonstrate the effectiveness of CorssFake under the cross-lingual setting and it also outperforms several monolingual and cross-lingual fake news detectors. The dataset is available at https://github.com/YingtongDou/CrossFake. © 2021 IEEE.

Multi-modal Information Fusion-powered Regional Covid-19 Epidemic Forecasting

With the current raging spread of the COVID19, early forecasting of the future epidemic trend is of great significance to public health security. The COVID-19 is virulent and spreads widely. An outbreak in one region often triggers the spread of others, and regions with relatively close association would show a strong correlation in the spread of the epidemic. In the real world, many factors affect the spread of the outbreak between regions. These factors exist in the form of multimodal data, such as the time-series data of the epidemic, the geographic relationship, and the strength of social contacts between regions. However, most of the current work only uses historical epidemic data or single-modal geographic location data to forecast the spread of the epidemic, ignoring the correlation and complementarity in multi-modal data and its impact on the disease spread between regions. In this paper, we propose a Multimodal InformatioN fusion COVID-19 Epidemic forecasting model (MINE). It fuses inter-regional and intra-regional multi-modal information to capture the temporal and spatial relevance of the COVID-19 spread in different regions. Extensive experimental results show that the proposed method achieves the best results compared to state-of-art methods on benchmark datasets. © 2021 IEEE.

First nosocomial cluster of COVID-19 due to the Delta variant in a major acute care hospital in Singapore: investigations and outbreak response.

OBJECTIVES: The first large nosocomial cluster of coronavirus disease 2019 (COVID-19) in Singapore in April 2021 led to partial closure of a major acute care hospital. This study examined factors associated with infection among patients, staff and visitors; investigated the possible role of aerosol-based transmission; evaluated the effectiveness of BNT162.b2 and mRNA1273 vaccines; and described the successful containment of the cluster. METHODS: Close contacts of patients with COVID-19 and the affected ward were identified and underwent surveillance for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Patient, staff and visitor cohorts were constructed and factors associated with infection were evaluated. Phylogenetic analysis of patient samples was performed. Ward air exhaust filters were tested for SARS-CoV-2. RESULTS: In total, there were 47 cases, comprising 29 patients, nine staff, six visitors and three household contacts. All infections were of the Delta variant. Ventilation studies showed turbulent air flow and swabs from air exhaust filters were positive for SARS-CoV-2. Vaccine breakthrough infections were seen in both patients and staff. Among patients, vaccination was associated with a 79% lower odds of infection with COVID-19 (adjusted odds ratio 0.21, 95% confidence interval 0.05-0.95). CONCLUSIONS: This cluster occurred despite enhancement of infection control measures that the hospital had undertaken at the onset of the COVID-19 pandemic. It was brought under control rapidly through case isolation, extensive contact tracing and quarantine measures, and led to enhanced use of hospital personal protective equipment, introduction of routine rostered testing of inpatients and staff, and changes in hospital infrastructure to improve ventilation within general wards.

Development and validation of a competency evaluation model for hospital infection prevention and control practitioners in the post-pandemic era: a mixed methods study.

BACKGROUND: During the coronavirus disease 2019 pandemic, the management of nosocomial infections became even more crucial. There is an urgent need to develop a competency model for healthcare practitioners to combat public health emergencies. AIM: To determine practitioners' competency in hospital infection prevention and control measures. METHODS: A theoretical framework was developed based on a literature review, key informant interviews, the Delphi method and a questionnaire survey. These items were evaluated based on response rate, maximum score, minimum score and mean score. Factor analyses, both exploratory and confirmatory, were used to determine the structure of the competency model. RESULTS: The effective response rate for the questionnaire was 88.29%, and Cronbach's α-coefficient was 0.964. Factor analysis revealed a Kaiser-Meyer-Olkin score of 0.945. Bartlett's test gave a χ2-value of 10523.439 (df=435; P<0.001). After exploratory factor analysis, the five-factor model was retained, four items were deleted and a five-dimensional, 26-item scale was obtained. The new structure's confirmatory factor analysis revealed high goodness of fit (comparative fit index=0.921; Tucker-Lewis index=0.911; standardized root mean square residual=0.053; root mean square error of approximation=0.044). CONCLUSION: The proposed scale is a useful tool to assess the competency of hospital infection prevention and control practitioners, which can help hospitals to improve infection prevention and control.

Metallomics for the Screening of COVID-19 and Metallodrug Development

The COVID-19 pandemic has led to severe threat globally. As a result, scientists are increasing their efforts in developing testing methods, antiviral drugs, and vaccines, to diagnose, treat, and defend against COVID-19 respectively. Although RT-PCR and antigen tests are used for the screening of COVID-19, there are many disadvantages including high cost, long processing time, and false-negative results. With the exception of supportive care, no specific treatment for COVID-19 has been established. Metallomics focuses on the systematic study of the interactions and functional connections of metallic/metalloid ions and their species with genes, proteins, metabolites, and other biomolecules within organisms and ecosystems. It has been applied in the screening of various cancers, neurodegenerative diseases, and viral infections and metallodrug development with the advantages of high throughput, low risk of cross-infection, low cost, and ready availability. Therefore, we proposed the use of metallomics for the screening and metallodrug development of COVID-19. An operational work scheme is also presented.

Establishment and application to environment sample test of novel coronavirus

Background: Since the COVID-19 outbreak, the existence of SARS-CoV-2 virus in the air and objects surface has been proved, how to detect the novel coronavirus effectively and accurately has become the current focus. a detection method for new coronavirus in environmental sample should be established to provide basis for the protection and disinfection of novel coronavirus in the future. Methods: Environmental samples were collected primarily from isolation rooms for COVID-19 patients. In the environmental samples, the air samples are collected by bioaerosol samplers. For objects surface samples, a cotton swab was moistened with the collection liquid, and then used to wipe the surface of the object once. Results: In total, we collected 46 air samples, one of these samples' testing results was positive, which from the corridor closed to isolation rooms, and 107 object surface samples, four of these samples' testing results were positive and three were weak positive which from bathroom in the isolation rooms. Conclusions: The detection method of the novel coronavirus in environmental samples was established successfully, which provides a basis for environmental disinfection and control of the spread of new coronavirus pneumonia. And this indicated that medical staff should strengthen personal protection, strictly implement infection prevention control measures. © 2021 AME Publishing Company. All rights reserved.

Application of a crisis management nursing system in the novel coronavirus pneumonia epidemic

Objective: To explore the application of a nursing crisis management system in the novel coronavirus pneumonia epidemic. Methods: A retrospective nursing method was implemented. A total of 280 cases of patients were diagnosed with coronavirus pneumonia in the isolation ward of our hospital. The 280 cases of newly diagnosed pneumonia were divided into two groups: The nursing crisis management system group (n=150, the nursing crisis management was given) and the non-nursing crisis management system (n=130, routine nursing management was given). The psychological status (profile of mood states (POMS) score) of nursing staff before and after the implementation of the nursing crisis management, the psychological status of patients after the implementation of nursing crisis management (POMS score), emotion, cognition, behavior severity, patients' satisfaction with nursing, treatment compliance (Morisky Medication Compliance Scale (MMAS) score) of patients, the rate of cure of patients and the infection rate of nursing staff were compared. Results: Compared with the non-nursing crisis management system group, the POMS scores of patients and nurses in the nursing crisis management system group decreased (all P<0.05). Compared with the non-nursing crisis management system group, the emotional, cognitive and behavioral scores of patients in the nursing crisis management system group were lower, while the MMAS score, satisfaction with nursing and cure rate were significantly increased (all P<0.05). The 142 nursing staff did not catch coronavirus. Conclusion: During the novel coronavirus pneumonia outbreak and the current normal epidemic prevention and control periods, our crisis management mode was introduced into nursing work. The construction of the nursing crisis management mode under the epidemic situation can improve the psychological state and improve the management efficiency of the patients and nurses. The patients' satisfaction is high and the treatment compliance is good.