Effects of Porcine deltacoronavirus on the transduction pathway of the innate immune signal

Porcine deltacoronavirus (PDCOV) is a new type of pig intestinal coronavirus, which targets pig small intestinal epithelial cells to cause severe enteritis. After infecting the host, PDCoV finishes its proliferation in the host cell by antagonism or escape the innate immune signaling transduction pathway. In order to understand the action mechanism of PDCOV 0n the congenital immune signal transduction pathways, this paper reviews the effects of PDCOV on RLR, Jak-STAT, MAPK and mitochondrial signaling pathway to clarify the relationship between PDCOV and host innate immune signaling transduction pathways in order to provide help for the prevention and treatment of PDCOV infection.

Inactivated SARS-CoV-2 vaccine does not increase the risk of relapse in patients with clinically inactive adult-onset Still's disease.

OBJECTIVE: A succession of cases have reported flares of adult-onset Still's disease (AOSD) after vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raising concerns. We aimed to investigate the impact of inactivated SARS-CoV-2 vaccines on disease activity in patients with AOSD. METHODS: We prospectively enrolled clinically inactive AOSD patients visiting the outpatient clinics of our department. The patients received SARS-CoV-2 vaccines (BBIBPCorV, Sinopharm, Beijing, China) voluntarily. The occurrence of relapse in the participants was recorded during the follow-up period and a propensity score matching (PSM) method was used to compare the relapse rates between vaccinated and unvaccinated patients. Localized and systemic symptoms were assessed in the vaccinated patients. RESULTS: A total of 122 patients with inactive AOSD were included, of which 49.2% (n = 60) voluntarily received the inactivated SARS-CoV-2 vaccine. The relapse rate did not increase significantly in vaccinated patients in comparison with unvaccinated patients (after PSM: 6.8% versus 6.8%), and no relapse occurred within one month after vaccination. No obvious adverse reactions were reported in 75.0% of the participants, and none of the patients reported severe reactions. CONCLUSION: Increased disease activity or relapse following vaccination with inactivated SARS-CoV-2 were rare in patients with inactive AOSD. Local and systemic adverse reactions were found to be mild and self-limiting. These safety profiles of inactivated SARS-CoV-2 vaccines in patients with AOSD may assist in eliminating vaccine hesitancy and increase the vaccination rate against SARS-CoV-2.

A new tractable method for generating human alveolar macrophage-like cells in vitro to study lung inflammatory processes and diseases.

Alveolar macrophages (AMs) are unique lung resident cells that contact airborne pathogens and environmental particulates. The contribution of human AMs (HAMs) to pulmonary diseases remains poorly understood due to the difficulty in accessing them from human donors and their rapid phenotypic change during in vitro culture. Thus, there remains an unmet need for cost-effective methods for generating and/or differentiating primary cells into a HAM phenotype, particularly important for translational and clinical studies. We developed cell culture conditions that mimic the lung alveolar environment in humans using lung lipids, that is, Infasurf (calfactant, natural bovine surfactant) and lung-associated cytokines (granulocyte macrophage colony-stimulating factor, transforming growth factor-ß, and interleukin 10) that facilitate the conversion of blood-obtained monocytes to an AM-like (AML) phenotype and function in tissue culture. Similar to HAM, AML cells are particularly susceptible to both Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. This study reveals the importance of alveolar space components in the development and maintenance of HAM phenotype and function and provides a readily accessible model to study HAM in infectious and inflammatory disease processes, as well as therapies and vaccines.IMPORTANCEMillions die annually from respiratory disorders. Lower respiratory track gas-exchanging alveoli maintain a precarious balance between fighting invaders and minimizing tissue damage. Key players herein are resident AMs. However, there are no easily accessible in vitro models of HAMs, presenting a huge scientific challenge. Here, we present a novel model for generating AML cells based on differentiating blood monocytes in a defined lung component cocktail. This model is non-invasive, significantly less costly than performing a bronchoalveolar lavage, yields more AML cells than HAMs per donor, and retains their phenotype in culture. We have applied this model to early studies of M. tuberculosis and SARS-CoV-2. This model will significantly advance respiratory biology research.

Experiences of maintaining awake prone positioning in non-intubated patients with COVID-19: A qualitative study.

BACKGROUND: Patient compliance is crucial to maintaining the awake prone position, which has been found to be intolerable by several patients. Addressing patients' compliance while being treated with awake prone positioning and prolonging its duration may be prerequisites for further research. AIMS: This study was conducted to explore the personal experiences of non-intubated patients during the implementation of awake prone positioning. STUDY DESIGN: We conducted a qualitative study recruiting a purposive sample of twelve adult patients diagnosed with COVID-19 who were previously treated with awake prone positioning. They were recruited from an intermediate care unit (that provides pre- and post-intensive care) in a COVID-19-designated hospital in Nanjing, China from July 15, 2021, to September 20, 2021. Data were collected through individual in-depth interviews and then analysed using Colaizzi's phenomenological method. RESULTS: Content analysis of the interviews revealed two main themes, each containing three and four sub-themes, respectively, as follows: (1) barriers to the implementation of awake prone positioning, including (i) generalised discomfort, (ii) a lack of both understanding and trust, and (iii) low satisfaction with the implementation plan; (2) factors promoting the implementation of awake prone positioning, including (i) health education and supervision, (ii) self-motivation and support from healthcare staff and family members, (iii) finding a comfortable position and having access to entertainment, and (iv) symptom improvement. CONCLUSIONS: Healthcare staff should clarify the mechanism underlying the effectiveness of the awake prone position to patients to eliminate any doubts that they may have. Psychological support and appropriate supervision should be emphasised. Pain relief programmes should also be established, including the use of a comfortable prone posture in conjunction with access to entertainment. Finally, individualised awake prone positioning protocols should be formulated according to patients' living habits and attempted in combination with out-of-bed activities. These measures may help to enhance the experience and compliance of patients undergoing the treatment. RELEVANCE TO CLINICAL PRACTICE: For future instances involving the implementation of awake prone positioning, several measures should be established and implemented alongside it, including a health education programme, supervision programme, support system, and pain relief programme. Personalisation should also be considered during its implementation. These measures may help to enhance the compliance of patients and prolong the duration of the awake prone position.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance.

Navigating Radiation Therapy During COVID-19 Using YouTube as a Source of Information.

The COVID-19 pandemic brought considerable change to the practice of radiotherapy. In the meantime, patients are increasingly turning to online resources for health information, with YouTube being one of the biggest platforms. However, little is known about what information is being disseminated to cancer patients about radiotherapy in the context of COVID-19. Therefore, this study aims to characterize and assess YouTube videos on radiotherapy during COVID-19. A YouTube search using the terms "Radiation therapy COVID-19", "Radiation therapy coronavirus", "Radiotherapy COVID-19", and "Radiotherapy coronavirus" was completed using a clear-cache web browser. The top 50 videos were collected from each search. After applying pre-determined exclusion criteria, each video was assessed for general parameters, source, and content. Two raters were used to ensure interrater reliability. One hundred five unique videos resulted from the four searches. Ninety-eight per cent were published in the last year. The median video length was 6 min and 54 s, and the median number of views was 570. Most videos were from the USA (58%). The majority of videos were published by a commercial channel (31%), non-profit organization (28%), or healthcare facility (26%). Forty-two per cent of the videos covered a topic related to radiotherapy during the pandemic. Bias was identified in 6% of videos. YouTube information on radiotherapy during COVID-19 is non-specific and can be misleading. The results of this study highlight the need for healthcare providers to proactively address patient information needs and guide them to appropriate sources of information.

Online Education and Subjective Well-Being in China: Multiple Mediating Roles of Social Class Mobility and Social Tolerance

(1) Background: Online education has developed into a new form of education. However, the relationship between online education and subjective well-being has seldom been extensively studied in the literature. Thus, this study provides quantitative evidence regarding the effect of online education on subjective well-being. (2) Objective: The objective of this study was to reveal the net effect of online education on subjective well-being and explore the mediating roles of social class mobility and social tolerance between online education and subjective well-being. (3) Methods: Based on the 2019 China Comprehensive Social Survey data, the "counterfactual framework” was constructed using the propensity score matching method, and 1029 matched samples were analyzed. (4) Results: Online education is significantly positively correlated with subjective well-being (average treatment effect on the treated, ATT = 0.189, p < 0.01). Social class mobility and social tolerance serially mediate the relationship of online education and subjective well-being (the intermediary role of social class mobility is 0.0163;the mediating role of social tolerance is 0.0064). (5) Conclusion: This study confirms the positive predictive effect of online education on subjective well-being and affirms the multiple mediating roles of social class mobility and social tolerance between online education and subjective well-being.

Global Dynamics of Porcine Enteric Coronavirus PEDV Epidemiology, Evolution, and Transmission.

With a possible origin from bats, the alphacoronavirus Porcine epidemic diarrhea virus (PEDV) causes significant hazards and widespread epidemics in the swine population. However, the ecology, evolution, and spread of PEDV are still unclear. Here, from 149,869 fecal and intestinal tissue samples of pigs collected in an 11-year survey, we identified PEDV as the most dominant virus in diarrheal animals. Global whole genomic and evolutionary analyses of 672 PEDV strains revealed the fast-evolving PEDV genotype 2 (G2) strains as the main epidemic viruses worldwide, which seems to correlate with the use of G2-targeting vaccines. The evolving pattern of the G2 viruses presents geographic bias as they evolve tachytely in South Korea but undergo the highest recombination in China. Therefore, we clustered six PEDV haplotypes in China, whereas South Korea held five haplotypes, including a unique haplotype G. In addition, an assessment of the spatiotemporal spread route of PEDV indicates Germany and Japan as the primary hubs for PEDV dissemination in Europe and Asia, respectively. Overall, our findings provide novel insights into the epidemiology, evolution, and transmission of PEDV, and thus may lay a foundation for the prevention and control of PEDV and other coronaviruses.

Waterproofing performance of polypropylene - concrete wall of underground silo under combined compressive stress and water pressure.

Safe, economical and high-quality storage of huge amount of grain for a longer duration under COVID-19 is a challenge and underground storage is a good alternative due to stable temperature, less cooling consumption and better pest control effect. However, the underground silo has very high requirement of waterproof and the performance of underground silo under combined compression and water pressure was rarely studied. In this study, a new composite structure, polypropylene - concrete wall (PPCW) for underground silo was proposed. Total three PPCWs with different size were manufactured to test the waterproofing features under joint effect of compression and hydropower of water. The strains, lateral displacement and cracking conditions of PPCWs were investigated. According to the experimental results, the PP board and concrete presented very good performance of interaction working under compression. The maximum water pressure of the specimens with stud spacing of 250mm increased by about 15.7% compared with that of the specimens with stud spacing of 350mm. The welding and strength of PP board has the greatest influence on the ultimate performance of PPCW. Based on the empirical coefficient method of concrete flat-slab and tested results, a new modified method was proposed to predict the bending moment at mid-span of PPCW by using an adjustment coefficient, R m . Considering this experimental case only, the adopting a R m = 0.64 could control the relative errors between test and analysis under 15.6%.

Metabolomic analysis of porcine intestinal epithelial cells during swine acute diarrhea syndrome coronavirus infection.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an enveloped, positive single-stranded RNA virus belonging to Coronaviridae family, Orthocoronavirinae subfamily, Alphacoronavirus genus. As one of the main causes of swine diarrhea, SADS-CoV has brought huge losses to the pig industry. Although we have a basic understanding of SADS-CoV, the research on the pathogenicity and interactions between host and virus are still limited, especially the metabolic changes induced by SADS-CoV infection. Here, we utilized a combination of untargeted metabolomics and lipomics to analyze the metabolic alteration in SADS-CoV infected cells. Significant changes were observed in 1257 of 2225 metabolites identified in untargeted metabolomics, while the number of lipomics was 435 out of 868. Metabolic pathway enrichment analysis showed that amino acid metabolism, tricarboxylic acid (TCA) cycle and ferroptosis were disrupted during viral infection, suggesting that these metabolic pathways may partake in pathological processes related to SADS-CoV pathogenesis. Collectively, our findings gain insights into the cellular metabolic disorder during SADS-CoV infection, offer a valuable resource for further exploration of the relationship between virus and host metabolic activities, and provide potential targets for the development of antiviral drugs.

A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19).

Coronavirus disease 2019 (COVID-19), beginning in December 2019, has spread worldwide, leading to the death of millions. Owing to the absence of definitive treatment, vaccination against COVID-19 emerged as an effective strategy against the spread of the pandemic. Acceptance of the COVID-19 vaccine has advanced considerably, and vaccine-related research has significantly increased over the past three years. This study aimed to evaluate the content and external characteristics of COVID-19 vaccine-related literature for tracking research trends related to the global COVID-19 vaccine with the means of bibliometrics and visualization maps. A total of 18,285 records in 3499 journals were retrieved in the Web of Science Core Collection database and included in the final analysis. China was the first to focus on COVID-19 vaccine research, while European and American countries started late but developed rapidly. The USA and the UK are the top contributors to COVID-19 vaccine development, with the largest number of publications. The University of Washington and Harvard Medical School were the leading institutions, while Krammer, F. from Icahn School of Medicine at Mount Sinai was the author most active and influential to the topic. The New England Journal of Medicine had the highest number of citations and the highest TLS, and was the most cited and influential journal in the field of COVID-19 vaccine research. COVID-19 vaccine research topics and hotspots focused on populations' attitudes towards vaccination, immunity-related information analysis of spike proteins, the effectiveness and side effects of the COVID-19 vaccine, and the public management of epidemic transmission. The findings of this study provide the global status, research hotspots and potential trends in the field of COVID-19 vaccine research, which will assist researchers in mastering the knowledge structure, and evaluating and guiding future developmental directions of COVID-19 vaccine.

Evaluation of COVID-19 vaccines in primary prevention against infections and reduction in severity of illness following the outbreak of SARS-CoV-2 omicron variant in Shanghai.

Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessen the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Data sources: Data from 153,544 COVID-19 patients admitted to the Shanghai "Four-Leaf Clover" Fangcang makeshift shelter hospital were collected using a structured electronic questionnaire, which was then merged with electronic medical records of the hospital. For healthy controls, data on vaccination status and other information were obtained from 228 community-based residents, using the same structured electronic questionnaire. Methods: To investigate whether inactivated vaccines were effective in protecting against SARS-CoV-2 virus, we estimated the odds ratio (OR) of the vaccination by comparing cases and matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied multivariate stepwise logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in the COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Results: Of the 153,544 COVID-19 patients included in the analysis, the mean age was 41.59 years and 90,830 were males (59.2%). Of the study cohort, 118,124 patients had been vaccinated (76.9%) and 143,225 were asymptomatic patients (93.3%). Of the 10,319 symptomatic patients, 10,031 (97.2%), 281 (2.7%), and 7 (0.1%) experienced mild, moderate, and severe infections, respectively. Hypertension (8.7%) and diabetes (3.0%) accounted for the majority of comorbidities. There is no evidence that the vaccination helped protect from infections (OR = 0.82, p = 0.613). Vaccination, however, offered a small but significant protection against symptomatic infections (RR = 0.92, p < 0.001) and halved the risk of moderate/severe infections (OR = 0.48, 95% CI: 0.37-0.61). Older age (≥60 years) and malignant tumors were significantly associated with moderate/severe infections. Conclusion: Inactivated COVID-19 vaccines helped provide small but significant protection against symptomatic infections and halved the risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking the SARS-CoV-2 Omicron Variant community spread.

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states and phenotypes, and has helped elucidate biological processes, such as those occurring during the development of complex organisms, and improved our understanding of disease states, such as cancer, diabetes, and coronavirus disease 2019 (COVID-19). Deep learning, a recent advance of artificial intelligence that has been used to address many problems involving large datasets, has also emerged as a promising tool for scRNA-seq data analysis, as it has a capacity to extract informative and compact features from noisy, heterogeneous, and high-dimensional scRNA-seq data to improve downstream analysis. The present review aims at surveying recently developed deep learning techniques in scRNA-seq data analysis, identifying key steps within the scRNA-seq data analysis pipeline that have been advanced by deep learning, and explaining the benefits of deep learning over more conventional analytic tools. Finally, we summarize the challenges in current deep learning approaches faced within scRNA-seq data and discuss potential directions for improvements in deep learning algorithms for scRNA-seq data analysis.

Network-Based Data Analysis Reveals Ion Channel-Related Gene Features in COVID-19: A Bioinformatic Approach.

Coronavirus disease 2019 (COVID-19) seriously threatens human health and has been disseminated worldwide. Although there are several treatments for COVID-19, its control is currently suboptimal. Therefore, the development of novel strategies to treat COVID-19 is necessary. Ion channels are located on the membranes of all excitable cells and many intracellular organelles and are key components involved in various biological processes. They are a target of interest when searching for drug targets. This study aimed to reveal the relevant molecular features of ion channel genes in COVID-19 based on bioinformatic analyses. The RNA-sequencing data of patients with COVID-19 and healthy subjects (GSE152418 and GSE171110 datasets) were obtained from the Gene Expression Omnibus (GEO) database. Ion channel genes were selected from the Hugo Gene Nomenclature Committee (HGNC) database. The RStudio software was used to process the data based on the corresponding R language package to identify ion channel-associated differentially expressed genes (DEGs). Based on the DEGs, Gene Ontology (GO) functional and pathway enrichment analyses were performed using the Enrichr web tool. The STRING database was used to generate a protein-protein interaction (PPI) network, and the Cytoscape software was used to screen for hub genes in the PPI network based on the cytoHubba plug-in. Transcription factors (TF)-DEG, DEG-microRNA (miRNA) and DEG-disease association networks were constructed using the NetworkAnalyst web tool. Finally, the screened hub genes as drug targets were subjected to enrichment analysis based on the DSigDB using the Enrichr web tool to identify potential therapeutic agents for COVID-19. A total of 29 ion channel-associated DEGs were identified. GO functional analysis showed that the DEGs were integral components of the plasma membrane and were mainly involved in inorganic cation transmembrane transport and ion channel activity functions. Pathway analysis showed that the DEGs were mainly involved in nicotine addiction, calcium regulation in the cardiac cell and neuronal system pathways. The top 10 hub genes screened based on the PPI network included KCNA2, KCNJ4, CACNA1A, CACNA1E, NALCN, KCNA5, CACNA2D1, TRPC1, TRPM3 and KCNN3. The TF-DEG and DEG-miRNA networks revealed significant TFs (FOXC1, GATA2, HINFP, USF2, JUN and NFKB1) and miRNAs (hsa-mir-146a-5p, hsa-mir-27a-3p, hsa-mir-335-5p, hsa-let-7b-5p and hsa-mir-129-2-3p). Gene-disease association network analysis revealed that the DEGs were closely associated with intellectual disability and cerebellar ataxia. Drug-target enrichment analysis showed that the relevant drugs targeting the hub genes CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5 were gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine. The results of this study provide a valuable basis for exploring the mechanisms of ion channel genes in COVID-19 and clues for developing therapeutic strategies for COVID-19.

Clinical characteristics of pediatric cases infected with the SARS-CoV-2 Omicron variant in a tertiary children's medical center in Shanghai, China.

BACKGROUND: The number of pediatric cases of infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has increased. Here, we describe the clinical characteristics of children in a tertiary children's medical center in Shanghai. METHODS: A total of 676 pediatric coronavirus disease 2019 (COVID-19) cases caused by the Omicron variant who were admitted to the Shanghai Children's Medical Center from March 28 to April 30, 2022 were enrolled in this single-center, prospective, observational real-world study. Patient demographics and clinical characteristics, especially COVID-19 vaccine status, were assessed. RESULTS: Children of all ages appeared susceptible to the SARS-CoV-2 Omicron variant, with no significant difference between sexes. A high SARS-CoV-2 viral load upon admission was associated with leukocytopenia, neutropenia, and thrombocytopenia (P = 0.003, P = 0.021, and P = 0.017, respectively) but not with physical symptoms or radiographic chest abnormalities. Univariable linear regression models indicated that comorbidities (P = 0.001) were associated with a longer time until viral clearance, and increasing age (P < 0.001) and two doses of COVID-19 vaccine (P = 0.001) were associated with a shorter time to viral clearance. Multivariable analysis revealed an independent effect of comorbidities (P < 0.001) and age (P = 0.003). The interaction effect between age and comorbidity showed that the negative association between age and time to virus clearance remained significant only in patients without underlying diseases (P < 0.001). CONCLUSION: This study describes the clinical characteristics of children infected with the Omicron variant of SARS-CoV-2 and calls for additional studies to evaluate the effectiveness and safety of vaccination against COVID-19 in children.

Boron nitride nanocage as drug delivery systems for chloroquine, as an effective drug for treatment of coronavirus disease: A DFT study

Graphical Research has shown that chloroquine (CQ) can effectively help control COVID-19 infection. B24N24 nanocage is a drug delivery system. Thus, through density functional theory, the present study analyzed pristine nanocage-CQ interaction and CQ interaction with Si- and Al -doped nanocage. The findings revealed that nanocage doping, particularly with Si and Al, yields more satisfactory drug delivery for CQ due to their greater electronic and energetic characteristics with CQ.

Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated or newly incident in the period after acute SARS-CoV-2 infection. Most studies have examined these conditions individually without providing evidence on co-occurring conditions. In this study, we leveraged the electronic health record data of two large cohorts, INSIGHT and OneFlorida+, from the national Patient-Centered Clinical Research Network. We created a development cohort from INSIGHT and a validation cohort from OneFlorida+ including 20,881 and 13,724 patients, respectively, who were SARS-CoV-2 infected, and we investigated their newly incident diagnoses 30-180 days after a documented SARS-CoV-2 infection. Through machine learning analysis of over 137 symptoms and conditions, we identified four reproducible PASC subphenotypes, dominated by cardiac and renal (including 33.75% and 25.43% of the patients in the development and validation cohorts); respiratory, sleep and anxiety (32.75% and 38.48%); musculoskeletal and nervous system (23.37% and 23.35%); and digestive and respiratory system (10.14% and 12.74%) sequelae. These subphenotypes were associated with distinct patient demographics, underlying conditions before SARS-CoV-2 infection and acute infection phase severity. Our study provides insights into the heterogeneity of PASC and may inform stratified decision-making in the management of PASC conditions.

COVID-19 vaccine affects neither prothrombotic antibody profile nor thrombosis in primary antiphospholipid syndrome: a prospective study.

OBJECTIVE: To explore whether inactivated COVID-19 vaccine influences the profile of prothrombotic autoantibodies and induces thrombotic events in primary antiphospholipid syndrome (APS) patients. METHODS: We enrolled 39 primary APS patients who received two doses of inactivated SARS-CoV-2 vaccine (BBIBPCorV, Sinopharm, Beijing, China) voluntarily in this prospective cohort. Prothrombotic autoantibodies were determined before vaccination and four weeks after the 2nd dose of vaccination. Thrombotic disorders were evaluated via hospital site visits and assessments. RESULTS: There was no significant difference in the presence of all eleven autoantibodies detected before and four weeks after vaccination: for aCL, IgG (14 vs. 16, P= 0.64), IgM (13 vs. 19, P= 0.34), IgA (2 vs. 3, P= 0.64); anti-ß2GP1, IgG (12 vs. 12, P= 1.00), IgM (5 vs. 8, P= 0.36), IgA (4 vs. 3, P= 0.69); aPS/PT IgG (13 vs. 16, P= 0.48), IgM (17 vs. 22, P= 0.26); LAC (22 vs. 28, P= 0.16); aPF4-heparin (0 vs. 0, P= 1.00), and antinuclear antibody (ANA) (23 vs. 26, P= 0.48). Notably, the distribution of aPL profile in pre- and post- vaccination cohort was not affected by SARS-CoV-2 vaccination: for patients with low-risk aPL profile (11 vs. 10, P= 0.799) and patients with high-risk aPL profile (28 vs. 29, P= 0.799), respectively. Furthermore, no case exhibited symptoms of the thrombotic disorder during a minimum follow-up period of 12 weeks. There was no adjustment to the ongoing treatment regimens following SARS-CoV-2 vaccination. CONCLUSIONS: Inactivated SARS-CoV-2 vaccine does not influence the profile of antiphospholipid antibodies and anti-PF4-heparin antibodies nor induces thrombotic events in primary APS patients.

User Satisfaction Study for Sustainability of YouTube Content Quality: Focusing on Ski Technology

The purpose of this study is to find a way to maintain the sustainability of YouTube quality by identifying the relationship between user satisfaction, perceived achievement, and continuous use intention of YouTube content quality that provides ski technology information. Moreover, with the recent emergence of the recent emergence of COVID-19, face-to-face activities have been limited and skiing technique is commonly conveyed through YouTube. Therefore, it is urgent to develop and provide meaningful skiing technique content and information to YouTube users. To this end, this study focuses on YouTube content on ski techniques provided by the Education Committee of Korea Ski Instructors Association. The subjects of this study were 322 individuals who watched five YouTube videos produced by the Education Committee at High1, Yongpyeong, Phoenix Park, and Welli Hilli 4 ski resorts located in Gangwon-do from November 2021 to March 2022. Frequency analysis, Cronbach's alpha, and correlation analysis were performed using SPSSWIN 24.0. In addition, AMOS 24.0 was used for confirmatory factor analysis and structural equation model analysis for hypothesis validation. All statistical significance levels were set to p < 0.05. The findings support the suitability of the research model.