Understanding the Impact Mechanism of User Behavior Pattern toward Real Estate APP Platforms in the Post-COVID Era: A Quantitative Analysis

While technology factors are the main driver of the booming real estate APP platforms with important implications for user behavior pattern during and post-pandemic contexts, there is a lack of adequate research. In response, this study explores the user behavior pattern of real estate APP platforms to promote user mental health by taking the real estate APP platforms users as the participants based on theory of technology readiness and acceptance model. Data collected from offline surveys are analyzed using PLS-SEM. The results reveal the technology readiness index positively affects individuals' perceived usefulness and satisfaction, ultimately positively affects individuals' continuance intention with real estate APP platforms;satisfaction with real estate APP platforms mediated the relationship between technology readiness index, perceived ease of use, perceived usefulness, and individuals' continuance intention with real estate APP platforms. However, the group comparison finds no significant difference in user behavior patterns by gender. The contribution of this study is to reveal the influence mechanisms of digital technology on users' behavioral patterns toward real estate APP platforms, which can help guide the sustainable development of real estate APP platforms and promote user mental health and wellbeing in the post-COVID era.

Characteristics and outcomes of COVID-19 patients in New York City's public hospital system.

BACKGROUND: New York City (NYC) bore the greatest burden of COVID-19 in the United States early in the pandemic. In this case series, we describe characteristics and outcomes of racially and ethnically diverse patients tested for and hospitalized with COVID-19 in New York City's public hospital system. METHODS: We reviewed the electronic health records of all patients who received a SARS-CoV-2 test between March 5 and April 9, 2020, with follow up through April 16, 2020. The primary outcomes were a positive test, hospitalization, and death. Demographics and comorbidities were also assessed. RESULTS: 22254 patients were tested for SARS-CoV-2. 13442 (61%) were positive; among those, the median age was 52.7 years (interquartile range [IQR] 39.5-64.5), 7481 (56%) were male, 3518 (26%) were Black, and 4593 (34%) were Hispanic. Nearly half (4669, 46%) had at least one chronic disease (27% diabetes, 30% hypertension, and 21% cardiovascular disease). Of those testing positive, 6248 (46%) were hospitalized. The median age was 61.6 years (IQR 49.7-72.9); 3851 (62%) were male, 1950 (31%) were Black, and 2102 (34%) were Hispanic. More than half (3269, 53%) had at least one chronic disease (33% diabetes, 37% hypertension, 24% cardiovascular disease, 11% chronic kidney disease). 1724 (28%) hospitalized patients died. The median age was 71.0 years (IQR 60.0, 80.9); 1087 (63%) were male, 506 (29%) were Black, and 528 (31%) were Hispanic. Chronic diseases were common (35% diabetes, 37% hypertension, 28% cardiovascular disease, 15% chronic kidney disease). Male sex, older age, diabetes, cardiac history, and chronic kidney disease were significantly associated with testing positive, hospitalization, and death. Racial/ethnic disparities were observed across all outcomes. CONCLUSIONS AND RELEVANCE: This is the largest and most racially/ethnically diverse case series of patients tested and hospitalized for COVID-19 in New York City to date. Our findings highlight disparities in outcomes that can inform prevention and testing recommendations.

Self-assembled multiepitope nanovaccine based on NoV P particles induces effective and lasting protection against H3N2 influenza virus.

Current seasonal influenza vaccines confer only limited coverage of virus strains due to the frequent genetic and antigenic variability of influenza virus (IV). Epitope vaccines that accurately target conserved domains provide a promising approach to increase the breadth of protection; however, poor immunogenicity greatly hinders their application. The protruding (P) domain of the norovirus (NoV), which can self-assemble into a 24-mer particle called the NoV P particle, offers an ideal antigen presentation platform. In this study, a multiepitope nanovaccine displaying influenza epitopes (HMN-PP) was constructed based on the NoV P particle nanoplatform. Large amounts of HMN-PP were easily expressed in Escherichia coli in soluble form. Animal experiments showed that the adjuvanted HMN-PP nanovaccine induced epitope-specific antibodies and haemagglutinin (HA)-specific neutralizing antibodies, and the antibodies could persist for at least three months after the last immunization. Furthermore, HMN-PP induced matrix protein 2 extracellular domain (M2e)-specific antibody-dependent cell-mediated cytotoxicity, CD4+ and CD8+ T-cell responses, and a nucleoprotein (NP)-specific cytotoxic T lymphocyte (CTL) response. These results indicated that the combination of a multiepitope vaccine and self-assembled NoV P particles may be an ideal and effective vaccine strategy for highly variable viruses such as IV and SARS-CoV-2. Electronic Supplementary Material: Supplementary material is available in the online version of this article at 10.1007/s12274-023-5395-6.

[Medication law and mechanism of traditional Chinese medicine in prevention and treatment of epidemic diseases: based on traditional Chinese medicine theory of cold pestilence].

Epidemic diseases have caused huge harm to the society. Traditional Chinese medicine(TCM) has made great contributions to the prevention and treatment of them. It is of great reference value for fighting diseases and developing drugs to explore the medication law and mechanism of TCM under TCM theory. In this study, the relationship between the TCM theory of cold pestilence and modern epidemic diseases was investigated. Particularly, the the relationship of coronavirus disease 2019(COVID-19), severe acute respiratory syndrome(SARS), and influenza A(H1 N1) with the cold pestilence was identified and analyzed. The roles of TCM theory of cold pestilence in preventing and treating modern epidemic diseases were discussed. Then, through data mining and textual research, prescriptions for the treatment of cold pestilence were collected from major databases and relevant ancient books, and their medication laws were examined through analysis of high-frequency medicinals and medicinal pairs, association rules analysis, and cluster analysis. For example, the prescriptions with high confidence levels were identified: "Glycyrrhizae Radix et Rhizoma-Bupleuri Radix-Paeoniae Radix Alba" "Glycyrrhizae Radix et Rhizoma-Pinelliae Rhizoma-Bupleuri Radix", and TCM treatment methods with them were analyzed by clustering analysis to yield the medicinal combinations: "Zingiberis Rhizoma-Aconiti Lateralis Radix Praeparata-Ginseng Radix et Rhizoma" "Poria-Atractylodis Macrocephalae Rhizoma" "Cinnamomi Ramulus-Asari Radix et Rhizoma" "Citri Reticulatae Pericarpium-Perillae Folium" "Pinelliae Rhizoma-Magnoliae Officinalis Cortex-Atractylodis Rhizoma" "Paeoniae Radix Alba-Angelicae Sinensis Radix-Glycyrrhizae Radix et Rhizoma-Bupleuri Radix-Scutellariae Radix-Rhizoma Zingiberis Recens" "Ephedrae Herba-Armeniacae Semen Amarum-Gypsum Fibrosum" "Chuanxiong Rhizoma-Notopterygii Rhizoma et Radix-Angelicae Dahuricae Radix-Platycodonis Radix-Saposhnikoviae Radix". Then, according to the medication law for cold pestilence, the antiviral active components of medium-frequency and high-frequency medicinals were retrieved. It was found that these components exerted the antiviral effect by inhibiting virus replication, regulating virus proteins and antiviral signals, and suppressing protease activity. Based on network pharmacology, the mechanisms of the medicinals against severe acute respiratory syndrome coronavirus(SARS-CoV), 2019 novel coronavirus(2019-nCoV), and H1 N1 virus were explored. It was determined that the key targets were tumor necrosis factor(TNF), endothelial growth factor A(VEGFA), serum creatinine(SRC), epidermal growth factor receptor(EGFR), matrix metalloproteinase 9(MMP9), mitogen-activated protein kinase 14(MAPK14), and prostaglandin-endoperoxide synthase 2(PTGS2), which were involved the mitogen-activated protein kinase(MAPK) pathway, advanced glycation end-products(AGE)-receptor for AGE(RAGE) pathway, COVID-19 pathway, and mTOR pathway. This paper elucidated the medication law and mechanism of TCM for the prevention and treatment of epidemic diseases under the guidance of TCM theory of cold pestilence, in order to build a bridge between the theory and modern epidemic diseases and provide reference TCM methods for the prevention and treatment of modern epidemic diseases and ideas for the application of data mining to TCM treatment of modern diseases.

Coronavirus Disease 2019 and Hospital Readmissions: Patient Characteristics and Socioeconomic Factors Associated With Readmissions in an Urban Safety-Net Hospital System.

BACKGROUND: It is not yet known whether socioeconomic factors (ie, social determinants of health) are associated with readmission following hospitalization for coronavirus disease 2019 (COVID-19). METHODS: We conducted a retrospective cohort study of 6191 adult patients hospitalized with COVID-19 in a large New York City safety-net hospital system between March 1 and June 1, 2020. Associations between 30-day readmission and selected demographic characteristics, socioeconomic factors, prior health care utilization, and relevant features of the index hospitalization were analyzed using a multivariable generalized estimating equation model. RESULTS: The readmission rate was 7.3%, with a median of 7 days between discharge and readmission. The following were risk factors for readmission: age 65 and older [adjusted odds ratio (aOR): 1.32; 95% confidence interval (CI): 1.13-1.55], history of homelessness, (aOR: 2.03 95% CI: 1.49-2.77), baseline coronary artery disease (aOR: 1.68; 95% CI: 1.34-2.10), congestive heart failure (aOR: 1.34; 95% CI: 1.20-1.49), cancer (aOR: 1.68; 95% CI: 1.26-2.24), chronic kidney disease (aOR: 1.74; 95% CI: 1.46-2.07). Patients' sex, race/ethnicity, insurance, and presence of obesity were not associated with increased odds of readmission. A longer length of stay (aOR: 0.98; 95% CI: 0.97-1.00) and use of noninvasive supplemental oxygen (aOR: 0.68; 95% CI: 0.56-0.83) was associated with lower odds of readmission. Upon readmission, 18.4% of patients required intensive care, and 13.7% expired. CONCLUSION: We have found some factors associated with increased odds of readmission among patients hospitalized with COVID-19. Awareness of these risk factors, including patients' social determinants of health, may ultimately help to reduce readmission rates.

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.

A Pervasive Respiratory Monitoring Sensor for COVID-19 Pandemic.

Goal: The SARS-CoV-2 viral infection could cause severe acute respiratory syndrome, disturbing the regular breathing and leading to continuous coughing. Automatic respiration monitoring systems could provide the necessary metrics and warnings for timely intervention, especially for those with mild symptoms. Current respiration detection systems are expensive and too obtrusive for any large-scale deployment. Thus, a low-cost pervasive ambient sensor is proposed. Methods: We will posit a barometer on the working desk and develop a novel signal processing algorithm with a sparsity-based filter to remove the similar-frequency noise. Three modes (coughing, breathing and others) will be conducted to detect coughing and estimate different respiration rates. Results: The proposed system achieved 97.33% accuracy of cough detection and 98.98% specificity of respiration rate estimation. Conclusions: This system could be used as an effective screening tool for detecting subjects suffering from COVID-19 symptoms and enable large scale monitoring of patients diagnosed with or recovering.

Race, Ethnicity, and Age Trends in Persons Who Died from COVID-19 - United States, May-August 2020.

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System† (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.

Is oseltamivir suitable for fighting against COVID-19: In silico assessment, in vitro and retrospective study.

BACKGROUND: Oseltamivir is a first-line antiviral drug, especially in primary hospitals. During the ongoing outbreak of coronavirus disease 2019 (COVID-19), most patients with COVID-19 who are symptomatic have used oseltamivir. Considering its popular and important role as an antiviral drug, it is necessary to evaluate oseltamivir in the treatment of COVID-19. OBJECTIVE: To evaluate the effect of oseltamivir against COVID-19. METHODS: Swiss-model was used to construct the structure of the N-terminal RNA-binding domain (NRBD) of the nucleoprotein (NC), papain-like protease (PLpro), and RNA-directed RNA polymerase (RdRp) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). TM-align program was performed to compare the structure of the viral proteins with the structure of the neuraminidase of influenza A. Molecular docking was used to analyze the theoretical possibility of effective binding of oseltamivir with the active centers of the viral proteins. In vitro study was used to evaluate the antiviral efficiency of oseltamivir against SARS-CoV-2. By clinical case analysis, we statistically evaluated whether the history of oseltamivir use influenced the progression of the disease. RESULTS: The structures of NRBD, PLpro, and RdRp were built successfully. The results from TM-align suggested that the S protein, NRBD, 3C-like protease (3CLpro), PLPrO, and RdRp were structurally similar to the influenza A neuraminidase, with TM-scores of 0.30077, 0.19254, 0.28766, 0.30666, and 0.34047, respectively. Interestingly, the active center of 3CL pro was found to be similar to the active center from the neuraminidase of influenza A. Through an analysis of molecular docking, we discovered that oseltamivir carboxylic acid was more favorable to bind to the active site of 3CLpro effectively, but its inhibitory effect was not strong compared with the positive group. Finally, we used in vitro study and retrospective case analysis to verify our speculations. We found that oseltamivir is ineffective against SARS-CoV-2 in vitro study and the clinical use of oseltamivir did not improve the patients' symptoms and signs and did not slow the disease progression. CONCLUSIONS: We consider that oseltamivir isn't suitable for the treatment of COVID-19. During the outbreak of novel coronavirus, when oseltamivir is not effective for the patients after they take it, health workers should be highly vigilant about the possibility of COVID-19.

[Thoughts and suggestions on analysis of death cases report during COVID-19 epidemic].

It is an essential task to discuss the death cases for clinicians. During the emergent public events, the report and analysis of death cases is of far-reaching significance. The epidemic of coronavirus disease 2019(COVID-19) has brought huge losses to China, and the medical system has been sustaining tremendous pressure. The best weapon to defeat the epidemic is medical data and related scientific research, of which the systematic analysis and efficient use of death cases is a key step. Based on the incomplete record of death case report, the lack of humanistic perspective and patient report, every department and institution is facing great challenge in terms of data management. Given that the relevant systems need to be improved, and that the integration of standardized reports and clinical research is not mature,as well as other problems, we put forward several methodological suggestions: ① Establish national medical and health data center and improve relevant laws and regulations. ② Increase investment in medical data management and start data collection and analysis as early as possible during the epidemic. ③ Refine the content of death case report and promote the standardization of report. ④ Pay close attention to the report of death cases, review, summary and analysis. More importantly, we should continue to build and improve platforms and programs related to disease control, carry out epidemic-associated scientific research, enhance the managing efficiency of public health data, elevate the anti-risk capability of our medical system, and promote the steady progress of the health China strategy.

[Thoughts and suggestions on arrangement, analysis and summary of medical data during COVID-19 epidemic].

The analysis and utilization of clinical scientific research data is an effective means to promote the progress of diagnosis and treatment, and a key step in the development of medical sciences. During the epidemic of coronavirus disease 2019(COVID-19), how to transform the limited diagnostic data into clinical research resources has attracted much attention. Based on the low efficiency of data collection and extraction, the inconsistency of data analysis, the irregularity of data report and the high timeliness of data update during the epidemic, this paper briefly analyzed the background and reasons of data application under the current situation, and then discusses the problems and feasible solutions of clinical data applications under the epidemic situation and, more importantly, for future medical clinical research methods. We put forward several methodological suggestions: ① gradually improve the medical big data model and establish the national medical health data center; ② improve the scientific research literacy of medical staff and popularize the basic skills and knowledge of GCP; ③ promote a scientific, networked and shared data collection and management mode; ④ use the mixed research method and collective analysis to improve the efficiency of clinical data analysis; ⑤ pay attention to narration of the medical feelings and emphasize the humanistic data of clinical medicine. It is expected to promote the standardized and reasonable use of clinical scientific research data, the rigorous integration of expert opinions, and ultimately the development of big data for national health care.