Identifying the predictors of severe psychological distress by auto-machine learning methods.

Social stress in daily life and the COVID-19 pandemic have greatly impacted the mental health of the population. Early detection of a predisposition to severe psychological distress is essential for timely interventions. This paper analyzed 4036 samples participating in the 2019-2020 National Health Information Trends Survey (HINTS) and identified 57 candidate predictors of severe psychological distress based on univariate chi-square and t-test analyses. Five machine learning methods, namely logistic regression (LR), automatic generalized linear models (Auto-GLM), automatic random forests (Auto-Random Forests), automatic deep neural networks (Auto-Deep learning) and automatic gradient boosting machines (Auto-GBM), were employed to model synthetic minority oversampling technique-based (SMOTE) resampled data and identify predictors of severe psychological distress. Predictors were evaluated by odds ratios in logistic models and variable importance in the other models. Forty-seven variables were identified as significant predictors of severe psychological distress, including 13 sociodemographic variables and 34 variables related to individual lifestyle and behavioral habits. Among them, new potentially relevant variables related to an individual's level of concern and trust in cancer information, exposure to health care providers, and cancer screening and awareness are included. The performance of each model was evaluated using five-fold cross-validation. The optimal model performance-wise was Auto-GBM with an accuracy of 89.75%, a precision of 89.68%, a recall of 89.31%, an F1-score of 89.48% and an AUC of 95.57%. Significant predictors of severe psychological distress were identified in this study and the value of machine learning methods in predicting severe psychological distress is demonstrated, thereby enhancing pre-prediction and clinical decision-making of severe psychological distress problems.

Fatigue as a Cause of Professional Dissatisfaction Among Chinese Nurses in Intensive Care Unit During COVID-19 Pandemic.

Aim: To clarify the mediating role of burnout and the moderating role of turnover intention in the association between fatigue and job satisfaction among Chinese nurses in intensive care units (ICU) during the COVID-19 pandemic. Methods: A cross-sectional survey of fifteen provinces in China was conducted, using an online questionnaire, from December 2020 to January 2021, during the COVID-19 pandemic. A total of 374 ICU nurses (effective response rate: 71.37%) provided sufficient responses. Sociodemographic factors, job demographic factors, fatigue, burnout, job satisfaction, and turnover intention were assessed using questionnaires. General linear modeling (GLM), hierarchical linear regression (HLR) analysis, and generalized additive modeling (GAM) were performed to examine all the considered research hypotheses. Results: Fatigue was found to be negatively and significantly associated with job satisfaction. Moreover, burnout played a partial mediating role and turnover intention played a moderating role in the relationship between fatigue and job satisfaction. Conclusion: Over time, a state of physical and mental exhaustion and work weariness among Chinese ICU nurses potentially results in job burnout and consequently promotes the level of job dissatisfaction. The results also found that turnover intention played a moderating role in the relationship between burnout and job satisfaction. Specific policies could be considered to eliminate nurses' fatigue and negative attitudes during times of public health emergencies.

Associations between brain gene expression perturbations implicated by COVID-19 and psychiatric disorders.

BACKGROUND: Currently, there is increasing evidence from clinic, epidemiology, as well as neuroimaging, demonstrating neuropsychiatric abnormalities in COVID-19, however, whether there were associations between brain changes caused by COVID-19 and genetic susceptibility of psychiatric disorders was still unknown. METHODS: In this study, we performed a meta-analysis to investigate these associations by combing single-cell RNA sequencing datasets of brain tissues of COVID-19 and genome-wide association study summary statistics of psychiatric disorders. RESULTS: The analysis demonstrated that among ten psychiatric disorders, gene expression perturbations implicated by COVID-19 in excitatory neurons of choroid plexus were significantly associated with schizophrenia. CONCLUSIONS: Our analysis might provide insights for the underlying mechanism of the psychiatric consequence of COVID-19.

Associations between brain gene expression perturbations implicated by COVID-19 and psychiatric disorders

Background Currently, there is increasing evidence from clinic, epidemiology, as well as neuroimaging, demonstrating neuropsychiatric abnormalities in COVID-19, however, whether there were associations between brain changes caused by COVID-19 and genetic susceptibility of psychiatric disorders was still unknown. Methods In this study, we performed a meta-analysis to investigate these associations by combing single-cell RNA sequencing datasets of brain tissues of COVID-19 and genome-wide association study summary statistics of psychiatric disorders. Results The analysis demonstrated that among ten psychiatric disorders, gene expression perturbations implicated by COVID-19 in excitatory neurons of choroid plexus were significantly associated with schizophrenia. Conclusions Our analysis might provide insights for the underlying mechanism of the psychiatric consequence of COVID-19.

Symptoms and Quality of Life Characteristics of Family Therapy Patients Infected with Omicron in China ——a Retrospective Observational Study (preprint)

Objectives To describe the clinical symptoms and quality of life characteristics of family therapy patients after infection with omicron in China.Methods We conducted a survey of 732 Chinese residents and screened 526 patients who had been infected with Omicron. These patients received treatment at home and have recovered. We conducted a retrospective survey of symptoms and quality of life in these patients.Results Fever is the most common symptom with an incidence of 88.97% among Omicron infected individuals treated at home, and followed by cough, headache, rhinobyon, and weakness. During the acute phase after infection with omicron, the sleep quality and appetite of patients decrease to varying degrees. What’s more, physical fatigue in infected individuals was significantly more severe than in uninfected individuals. It took about 2 to 3days to recover from symptoms in the acute phase for patients with mild symptoms of Omicron treated at home, however it took 1 to 2 months to recover from fatigue and other syndromes of Omicron.Conclusion Fever is the most typical symptom of Omicron infected patients undergoing home treatment. COVID-19 has a negative impact on sleep quality and appetite, and has a short-term impact on work and learning.

Comparative transcriptomic analyzes of human lung epithelial cells infected with wild-type SARS-CoV-2 and its variant with a 12-bp missing in the E gene.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused a global outbreak of coronavirus disease 2019 (COVID-19) pandemic. To elucidate the mechanism of SARS-CoV-2 replication and immunogenicity, we performed a comparative transcriptome profile of mRNA and long non-coding RNAs (lncRNAs) in human lung epithelial cells infected with the SARS-CoV-2 wild-type strain (8X) and the variant with a 12-bp deletion in the E gene (F8). In total, 3,966 differentially expressed genes (DEGs) and 110 differentially expressed lncRNA (DE-lncRNA) candidates were identified. Of these, 94 DEGs and 32 DE-lncRNAs were found between samples infected with F8 and 8X. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzes revealed that pathways such as the TNF signaling pathway and viral protein interaction with cytokine and cytokine receptor were involved. Furthermore, we constructed a lncRNA-protein-coding gene co-expression interaction network. The KEGG analysis of the co-expressed genes showed that these differentially expressed lncRNAs were enriched in pathways related to the immune response, which might explain the different replication and immunogenicity properties of the 8X and F8 strains. These results provide a useful resource for studying the pathogenesis of SARS-CoV-2 variants.

Comparative transcriptomic analyzes of human lung epithelial cells infected with wild-type SARS-CoV-2 and its variant with a 12-bp missing in the E gene

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused a global outbreak of coronavirus disease 2019 (COVID-19) pandemic. To elucidate the mechanism of SARS-CoV-2 replication and immunogenicity, we performed a comparative transcriptome profile of mRNA and long non-coding RNAs (lncRNAs) in human lung epithelial cells infected with the SARS-CoV-2 wild-type strain (8X) and the variant with a 12-bp deletion in the E gene (F8). In total, 3,966 differentially expressed genes (DEGs) and 110 differentially expressed lncRNA (DE-lncRNA) candidates were identified. Of these, 94 DEGs and 32 DE-lncRNAs were found between samples infected with F8 and 8X. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzes revealed that pathways such as the TNF signaling pathway and viral protein interaction with cytokine and cytokine receptor were involved. Furthermore, we constructed a lncRNA-protein-coding gene co-expression interaction network. The KEGG analysis of the co-expressed genes showed that these differentially expressed lncRNAs were enriched in pathways related to the immune response, which might explain the different replication and immunogenicity properties of the 8X and F8 strains. These results provide a useful resource for studying the pathogenesis of SARS-CoV-2 variants.

Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China

Exploring the spatial network structure of tourism flow and its influencing factors is of great significance to the transmission of characteristic culture and the sustainable development of tourism in tourist destinations, especially in backward rural areas. Taking Qiandongnan Miao and Dong Autonomous Prefecture (hereinafter referred to as Qiandongnan Prefecture) as an example, this paper adopts social network analysis and Quadratic Assignment Procedure regression analysis to study the network structural characteristics and influencing factors of tourism flow using online travel blog data. The results show that: (1) There are seasonal changes in tourism flow, but the attractions that tourists pay attention to do not change with the seasons. (2) The tightness of the tourism flow network structure is poor. The core nodes are unevenly distributed, and there are obvious structural holes. (3) The density of the tourism flow network is low. There is a clear core–periphery structure in the network, and the core area has a weak driving effect on the periphery area. There are more cohesive subgroups in the network, but the degree of connectedness between the subgroups varies greatly. (4) Geographical adjacency, transportation accessibility, and tourism resource endowment influence tourism flow network structure. The study found that the influencing factors of tourism flow in rural areas are different from those in urban areas. These results provide useful information for the marketing and development of tourism management departments in rural areas.

Inclusive leadership and emotional labor strategies of frontline medical staff: Regulatory focus as a mediator

In this study we examined inclusive leadership as an important factor in promoting the emotional labor strategies of frontline medical staff, and investigated the role of work regulatory focus as a mediator in this relationship. Data were collected from 52 supervisors and 231 frontline medical staff employed at 15 hospitals in China. We found that inclusive leadership inspired frontline medical staff to engage more in deep acting than in surface acting. Further, work regulatory focus played a mediating role in the relationship between inclusive leadership and subordinates' emotional labor strategy. Promotion focus positively affected deep acting and negatively affected surface acting, and prevention focus positively affected both surface acting and deep acting. Theoretical and practical management implications are discussed.

Establishment of a Rapid Typing Method for Coronavirus Disease 2019 Mutant Strains Based on PARMS Technology.

Purpose: This study aims to establish a competitive allele-specific PCR based on penta-primer amplification refractory mutation system (PARMS) technology to detect the key mutation sites of variant of concern (VOC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus for rapid typing. Methods: Competitive allele-specific primers and universal primers were designed for the key gene mutation sites N501Y, E484K, L452R, and K417N of SARS-CoV-2 VOCs, respectively.Using the principle of allele-specific polymerase chain reaction and fluorescence energy resonance transfer, different VOCs can be differentiated. Results: Using reverse transcribed cDNA of different VOCs as specimens, through double-blind detection, different VOC types can be effectively identified, with an accuracy rate of 100%. Through the identification and detection of different VOCs, effective differentiation can be achieved. Conclusions: The system has high specificity and sensitivity, with a detection limit of 1.28 copies/reaction.PARMS technology is fast, efficient, and low-cost. It is used for the identification and detection of the popular SARS-CoV-2 VOCs, which is helpful for the rapid and accurate prevention and control of COVID-19 epidemic.

Effect of the App-Based Video Guidance on Prenatal Pelvic Floor Muscle Training Combined with Global Postural Re-education for Stress Urinary Incontinence Prevention: A Protocol for a Multicenter, Randomized Controlled Trial.

BACKGROUND: As the effectiveness on stress urinary incontinence (SUI) prevention of pelvic floor muscle training (PFMT) for pregnant women has been inconclusive, we are planning to conduct a trial to evaluate a video program designed for prevention of SUI developed through combining PFMT with global postural reeducation (GPR). METHODS: As a randomized controlled trial, eligible participants will be randomized (1:1) into an exercise group and a control group to perform PFMT regularly following video guidance or with no intervention, respectively. The experimental stage will be from the 16th gestation week (GW) to the 12th month postpartum, with eight appointments at the 16th, 28th, 37th GW, delivery, the 6th week and the 3rd, 6th, and 12th month postpartum. Data will be collected regarding urinary leakage symptoms, the stress test, the modified Oxford Scale, pelvic floor ultrasound, perineal laceration classification at delivery, neonatal Apgar score, and questionnaires (PISQ-12, ICIQ-UI SF, I-QOL, OABSS). The primary outcome is the occurrence of the symptomatic SUI and positive stress test at the 6th week postpartum. DISCUSSION: This protocol is anticipated to evaluate the efficacy of the intervention via video app for the design of a future randomized control trial (RCT). TRIAL REGISTRATION: The trial has been registered at Chinese Clinical Trial Registry (registration number: ChiCTR2000029618).

ACE2 in the Gut: The Center of the 2019-nCoV Infected Pathology.

The 2019-nCoV is a rapidly contagious pneumonia caused by the recently discovered coronavirus. Although generally the most noticeable symptoms are concentrated in the lungs, the disorders in the gastrointestinal tract are of great importance in the diagnosis of 2019-nCoV. The angiotensin-converting enzyme 2 (ACE2), an important regulator of many physiological functions, including blood pressure and nutrients absorption, is recently identified as a vital entry for 2019-nCoV to enter host cells. In this review, we summarize its functions both physiologically and pathologically. We also elaborate its conflicting roles from the clews of contemporary researches, which may provide significant indications for pharmacological investigations and clinical uses.

Network-based analysis revealed significant interactions between risk genes of severe COVID-19 and host genes interacted with SARS-CoV-2 proteins.

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.git). By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes that had the highest network proximity with each other, with a hub gene HNRNPK identified. Among these genes, 14 of them were identified to be differentially expressed in RNA-seq data from severe COVID-19 cases. Besides, by expression enrichment analysis in single-cell RNA-seq data, compared with mild COVID-19, these genes were significantly enriched in macrophage, T cell and epithelial cell for severe COVID-19. Meanwhile, 74 pathways were significantly enriched. Our analysis provided insights for the underlying genetic etiology of severe COVID-19 from the perspective of network biology.

Comparing and integrating US COVID-19 data from multiple sources with anomaly detection and repairing

Over the past few months, the outbreak of Coronavirus disease (COVID-19) has been expanding over the world. A reliable and accurate dataset of the cases is vital for scientists to conduct related research and policy-makers to make better decisions. We collect the United States COVID-19 daily reported data from four open sources: the New York Times, the COVID-19 Data Repository by Johns Hopkins University, the COVID Tracking Project at the Atlantic, and the USAFacts, then compare the similarities and differences among them. To obtain reliable data for further analysis, we first examine the cyclical pattern and the following anomalies, which frequently occur in the reported cases: (1) the order dependencies violation, (2) the point or period anomalies, and (3) the issue of reporting delay. To address these detected issues, we propose the corresponding repairing methods and procedures if corrections are necessary. In addition, we integrate the COVID-19 reported cases with the county-level auxiliary information of the local features from official sources, such as health infrastructure, demographic, socioeconomic, and environmental information, which are also essential for understanding the spread of the virus. [ABSTRACT FROM AUTHOR] Copyright of Journal of Applied Statistics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Association of T lymphocytes level and clinical severity in patients of COVID-19 in Shenzhen China

To explore the correlation between T lymphocytes and clinical severity in patients of COVID-19. A total of 183 COVID-19 patients were recruited in Shenzhen Third People's Hospital from January 11 to February 16, 2020. According to the clinical classification criteria, they were divided into severe group (46 cases) and non-severe (137cases). T lymphocyte counts, lymphocyte subpopulation, IL-6 levels, and clinical outcomes were compared between the two groups. Compared with the non-severe group, the lymphocyte count, T lymphocyte count, T lymphocyte percentage, CD4+ T lymphocyte count, CD4+ T lymphocyte percentage, CD8+ T lymphocyte count, and CD8+ T lymphocyte percentage were lower in the severe group (p < 0.05). Compared with the non-severe group, IL-6 were higher in the severe group (p < 0.05). Compared with admission, the T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count were significantly increased upon discharge in severe patients, non-severe patients and all patients. Multivariate Logsitic regression analysis showed CD4+ T lymphocyte count (OR −0.011;95% CI −0.041 to −0.001;p = 0.011), CD8+ T lymphocyte count (OR −0.14;95% CI −0.048 to −0.003;p = 0.013) were closely correlated with the clinical severity in patients of COVID-19. Multivariate Logsitic regression analysis also showed CD4+ T lymphocyte count (OR −0.012;95% CI −3.177 to 0.261;p = 0.021), CD8+ T lymphocyte count (OR −0.019;95% CI −5.852 to 0.115;p = 0.004) were independent predictors of disease progressing to the composite endpoint. Subgroup analysis for critically ill patients: The T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count remained low in the death patients. The T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count recovered soon in the discharged patients. In the event of COVID-19 infection, the T-lymphoid system is the primary activated immune system. The T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes continued to be low may be significantly related to the deterioration of the disease, and may indicate a poor prognosis. [ABSTRACT FROM AUTHOR] Copyright of European Journal of Inflammation (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Domestication of wild animals may provide a springboard for rapid variation of coronavirus.

Coronaviruses have spread widely among humans and other animals, but not all coronaviruses carried by specific animals can directly infect other kinds of animals. Viruses from most animal hosts need an intermediate host before they can spread widely among humans. Under natural conditions, coronaviruses do not rapidly change from infecting wild animals as intermediate hosts and to spreading widely among humans. The intermediate host might be the animals captured or bred for the purpose of cross-breeding with domesticated species for improvement of the breed. These animals differ from wild animals at the environmental and genetic levels. It is an important direction to study the semi-wild animals domesticated by humans in search for intermediate hosts of viruses widely spread among humans.

Clinical characteristics and predictive value of lower CD4+T cell level in patients with moderate and severe COVID-19: a multicenter retrospective study.

BACKGROUND: In December 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, Hubei, China. Moreover, it has become a global pandemic. This is of great value in describing the clinical symptoms of COVID-19 patients in detail and looking for markers which are significant to predict the prognosis of COVID-19 patients. METHODS: In this multicenter, retrospective study, 476 patients with COVID-19 were enrolled from a consecutive series. After screening, a total of 395 patients were included in this study. All-cause death was the primary endpoint. All patients were followed up from admission till discharge or death. RESULTS: The main symptoms observed in the study included fever on admission, cough, fatigue, and shortness of breath. The most common comorbidities were hypertension and diabetes mellitus. Patients with lower CD4+T cell level were older and more often male compared to those with higher CD4+T cell level. Reduced CD8+T cell level was an indicator of the severity of COVID-19. Both decreased CD4+T [HR:13.659; 95%CI: 3.235-57.671] and CD8+T [HR: 10.883; 95%CI: 3.277-36.145] cell levels were associated with in-hospital death in COVID-19 patients, but only the decrease of CD4+T cell level was an independent predictor of in-hospital death in COVID-19 patients. CONCLUSIONS: Reductions in lymphocytes and lymphocyte subsets were common in COVID-19 patients, especially in severe cases of COVID-19. It was the CD8+T cell level, not the CD4+T cell level, that reflected the severity of the patient's disease. Only reduced CD4+T cell level was independently associated with increased in-hospital death in COVID-19 patients. TRIAL REGISTRATION: Prognostic Factors of Patients With COVID-19, NCT04292964 . Registered 03 March 2020. Retrospectively registered.

Clinical characteristics and fatal outcomes of hypertension in patients with severe COVID-19.

The aim of this study is to investigate clinical characteristics and fatal outcomes of hypertension as well as the role of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEI/ARB) use in patients with severe coronavirus disease 2019 (COVID-19). A total of 220 (female: 51.8%) patients with severe COVID-19 were included. The mean age of included patients was 59.5 years and 70 (31.8%) patients had a history of hypertension. There were 23 patients (32.9%) receiving ACEI/ARB therapy. Patients with hypertension were older and had more comorbidities, and were more likely to suffer from severe inflammatory response and acute cardiac injury. Moreover, patients with hypertension were associated with significantly higher risk of in-hospital mortality than patients without hypertension. After adjustment of potential confounders, the independent correlation was still observed. In addition, ACEI/ARB users were associated with lower level of high-sensitivity cardiac troponin I and creatinine kinase-myocardial band, and lower risk of acute cardiac injury than ACEI/ARB non-users. In conclusion, patients with hypertension were more likely to suffer from severe inflammatory response, acute cardiac injury and had high risk of in-hospital mortality in severe COVID-19. The use of ACEI/ARB may protect patients with COVID-19 from acute cardiac injury.