Integrated bioinformatics to identify potential key biomarkers for COVID-19-related chronic urticaria.

Background: A lot of studies have revealed that chronic urticaria (CU) is closely linked with COVID-19. However, there is a lack of further study at the gene level. This research is aimed to investigate the molecular mechanism of COVID-19-related CU via bioinformatic ways. Methods: The RNA expression profile datasets of CU (GSE72540) and COVID-19 (GSE164805) were used for the training data and GSE57178 for the verification data. After recognizing the shared differently expressed genes (DEGs) of COVID-19 and CU, genes enrichment, WGCNA, PPI network, and immune infiltration analyses were performed. In addition, machine learning LASSO regression was employed to identify key genes from hub genes. Finally, the networks, gene-TF-miRNA-lncRNA, and drug-gene, of key genes were constructed, and RNA expression analysis was utilized for verification. Results: We recognized 322 shared DEGs, and the functional analyses displayed that they mainly participated in immunomodulation of COVID-19-related CU. 9 hub genes (CD86, FCGR3A, AIF1, CD163, CCL4, TNF, CYBB, MMP9, and CCL3) were explored through the WGCNA and PPI network. Moreover, FCGR3A, TNF, and CCL3 were further identified as key genes via LASSO regression analysis, and the ROC curves confirmed the dependability of their diagnostic value. Furthermore, our results showed that the key genes were significantly associated with the primary infiltration cells of CU and COVID-19, such as mast cells and macrophages M0. In addition, the key gene-TF-miRNA-lncRNA network was constructed, which contained 46 regulation axes. And most lncRNAs of the network were proved to be a significant expression in CU. Finally, the key gene-drug interaction network, including 84 possible therapeutical medicines, was developed, and their protein-protein docking might make this prediction more feasible. Conclusions: To sum up, FCGR3A, TNF, and CCL3 might be potential biomarkers for COVID-19-related CU, and the common pathways and related molecules we explored in this study might provide new ideas for further mechanistic research.

Effect of a Functional Phospholipid Metabolome-Protein Association Pathway on the Mechanism of COVID-19 Disease Progression.

This study aimed to explore the clinical practice of phospholipid metabolic pathways in COVID-19. In this study, 48 COVID-19 patients and 17 healthy controls were included. Patients were divided into mild (n=40) and severe (n=8) according to their severity. Phospholipid metabolites, TCA circulating metabolites, eicosanoid metabolites, and closely associated enzymes and transfer proteins were detected in the plasma of all individuals using metabolomics and proteomics assays, respectively. 30 of the 33 metabolites found differed significantly (P<0.05) between patients and healthy controls (P<0.05), with D-dimmer significantly correlated with all of the lysophospholipid metabolites (LysoPE, LysoPC, LysoPI and LPA). In particular, we found that phosphatidylinositol (PI) and phosphatidylcholine (PC) could identify patients from healthy controls (AUC 0.771 and 0.745, respectively) and that the severity of the patients could be determined (AUC 0.663 and 0.809, respectively). The last measurement before discharge also revealed significant changes in both PI and PC. For the first time, our study explores the significance of the phospholipid metabolic system in COVID-19 patients. Based on molecular pathway mechanisms, three important phospholipid pathways related to Ceramide-Malate acid (Cer-SM), Lysophospholipid (LPs), and membrane function were established. Clinical values discovered included the role of Cer in maintaining the inflammatory internal environment, the modulation of procoagulant LPA by upstream fibrinolytic metabolites, and the role of PI and PC in predicting disease aggravation.

From Static to Dynamic: A Review on the Role of Mucus Heterogeneity in Particle and Microbial Transport.

Mucus layers (McLs) are on the front line of the human defense system that protect us from foreign abiotic/biotic particles (e.g., airborne virus SARS-CoV-2) and lubricates our organs. Recently, the impact of McLs on human health (e.g., nutrient absorption and drug delivery) and diseases (e.g., infections and cancers) has been studied extensively, yet their mechanisms are still not fully understood due to their high variety among organs and individuals. We characterize these variances as the heterogeneity of McLs, which lies in the thickness, composition, and physiology, making the systematic research on the roles of McLs in human health and diseases very challenging. To advance mucosal organoids and develop effective drug delivery systems, a comprehensive understanding of McLs' heterogeneity and how it impacts mucus physiology is urgently needed. When the role of airway mucus in the penetration and transmission of coronavirus (CoV) is considered, this understanding may also enable a better explanation and prediction of the CoV's behavior. Hence, in this Review, we summarize the variances of McLs among organs, health conditions, and experimental settings as well as recent advances in experimental measurements, data analysis, and model development for simulations.

Increase in Indoor Inhalant Allergen Sensitivity During the COVID-19 Pandemic in South China: A Cross-Sectional Study from 2017 to 2020.

PURPOSE: Public health measures during COVID-19 have led to an unprecedented change in social lifestyle which might have an impact on the allergen sensitization in population. We sought to explore the prevalence patterns of serum inhalant and food allergen-specific IgE (sIgE) sensitization and serum total immunoglobulin E (tIgE) level among patients with clinical symptoms of suspected allergic diseases before and during the COVID-19 pandemic in south China. PATIENTS AND METHODS: A large epidemiology study was conducted on the prevalence patterns of sIgE sensitization and serum tIgE level among 13,715 patients with allergic symptoms in south China from 2017 to 2020. Chi-square test and Fisher exact test were used to test statistical significance of allergen sensitization difference among years. Logistic regression was performed to assess the magnitudes of the differences among years by adjusted odds ratios and 95% confidence intervals. RESULTS: The number of hospital visits for patients with suspected allergy symptoms decreased during COVID-19. The positive rates of indoor inhalant allergens (house dust mites, German cockroach, dog dander) and tIgE increased significantly in 2020, while no significant differences were found in food allergens (egg white, milk, soya bean, shrimp) before and during the COVID-19 pandemic. The odds of sIgE positives in indoor inhalant allergens and tIgE positive for 2017 and 2020 were all larger than 1.00. After grouping by age and gender, there were significant differences in the positive rates of indoor inhalant allergens and tIgE when comparing 2020 with 2017. CONCLUSION: The prevalence of sensitization increased significantly to indoor inhalant allergens but not to food allergens in south China during the COVID-19 pandemic.

Sentiment-aware jump forecasting

This study models the return distributions of the Shanghai Security Composite Index (SSCI) by adding sentiment-aware variables (attention, sentiment, and disagreement), which may affect the jump intensity dynamics or changing the jump size variance, into the GARJI model of Maheu and McCurdy (2004). Textual analysis with some state-of-art machine-learning and deep-learning algorithms is used to select investor sentiment-aware variables with better performance. The extended models (GARJI-sentiment models), which incorporate the sentiment-aware variables into GARJI model, have better forecasting powers on volatilities and extreme events than the benchmark GARJI model. The significant influence of sentiment-aware variables on the jumps and conditional variances implies bounded rationality of investors. Our case study further provides some evidence that Black Swan events, including the implementation of the circuit breaker rule and the lockdown of Wuhan during the COVID-19 epidemic, could affect market jump risks and conditional variances by influencing the sentiment-aware variables, especially investor attention.

Trade liberalization induced profitability enhancement? The impact of intermediate input imports on firm profitability

Using the detailed data on production and transaction of Chinese manufacturing firms, we investigate how the input tariff liberalization affects firm profitability and explore the underlying channels of this effect. We find that input tariff reduction significantly increases firms’ profitability. Our finding is robust to a variety of specifications. We further find that the quality upgrading of imported intermediate inputs and the reduction of inventory costs are the main reasons for the profit-enhancing effect of input tariff reduction. Our study has important policy implications for the economic growth in the long run and the economic recovery during the epidemic of COVID-19.

Krebs Von den Lungen-6 as a predictive indicator for the risk of secondary pulmonary fibrosis and its reversibility in COVID-19 patients.

Dysregulated immune response and abnormal repairment could cause secondary pulmonary fibrosis of varying severity in COVID-19, especially for the elders. The Krebs Von den Lungen-6 (KL-6) as a sensitive marker reflects the degree of fibrosis and this study will focus on analyzing the evaluative efficacy and predictive role of KL-6 in COVID-19 secondary pulmonary fibrosis. The study lasted more than three months and included total 289 COVID-19 patients who were divided into moderate (n=226) and severe groups (n=63) according to the severity of illness. Clinical information such as inflammation indicators, radiological results and lung function tests were collected. The time points of nucleic acid test were also recorded. Furthermore, based on Chest radiology detection, it was identified that 80 (27.7%) patients developed reversible pulmonary fibrosis and 34 (11.8%) patients developed irreversible pulmonary fibrosis. Receiver operating characteristic (ROC) curve analysis shows that KL-6 could diagnose the severity of COVID-19 (AUC=0.862) and predict the occurrence of pulmonary fibrosis (AUC = 0.741) and irreversible pulmonary fibrosis (AUC=0.872). Importantly, the cross-correlation analysis demonstrates that KL-6 rises earlier than the development of lung radiology fibrosis, thus also illuminating the predictive function of KL-6. We set specific values (505U/mL and 674U/mL) for KL-6 in order to assess the risk of pulmonary fibrosis after SARS-CoV-2 infection. The survival curves for days in hospital show that the higher the KL-6 levels, the longer the hospital stay (P<0.0001). In conclusion, KL-6 could be used as an important predictor to evaluate the secondary pulmonary fibrosis degree for COVID-19.

Predictive effects of IgA and IgG combination to assess pulmonary exudation progression in COVID-19 patients.

Our study intended to longitudinally explore the prediction effect of immunoglobulin A (IgA) on pulmonary exudation progression in COVID-19 patients. The serum IgA was tested with chemiluminescence method. Autoregressive moving average model was used to extrapolate the IgA levels before hospital admission. The positive rate of IgA and IgG in our cohort was 97% and 79.0%, respectively. In this study, the IgA levels peaks within 10-15 days after admission, while the IgG levels peaks at admission. We found that the time difference between their peaks was about 10 days. Viral RNA detection results showed that the positive rate in sputum and feces were the highest. Blood gas analysis showed that deterioration of hypoxia with the enlargement of pulmonary exudation area. And alveolar-arterial oxygen difference and oxygenation index were correlated with IgA and IgG. The results of biopsy showed that the epithelium of lung was exfoliated and the mucosa was edematous. In severe COVID-19 patients, the combination of IgA and IgG can predict the progress of pulmonary lesions and is closely related to hypoxemia and both also play an important defense role in invasion and destruction of bronchial and alveolar epithelium by SARS-CoV-2.

The development and deployment of a model for hospital-level COVID-19 associated patient demand intervals from consistent estimators (DICE).

Hospitals commonly project demand for their services by combining their historical share of regional demand with forecasts of total regional demand. Hospital-specific forecasts of demand that provide prediction intervals, rather than point estimates, may facilitate better managerial decisions, especially when demand overage and underage are associated with high, asymmetric costs. Regional point forecasts of patient demand are commonly available, e.g., for the number of people requiring hospitalization due to an epidemic such as COVID-19. However, even in this common setting, no probabilistic, consistent, computationally tractable forecast is available for the fraction of patients in a region that a particular institution should expect. We introduce such a forecast, DICE (Demand Intervals from Consistent Estimators). We describe its development and deployment at an academic medical center in California during the 'second wave' of COVID-19 in the Unite States. We show that DICE is consistent under mild assumptions and suitable for use with perfect, biased and unbiased regional forecasts. We evaluate its performance on empirical data from a large academic medical center as well as on synthetic data.

Heparin-binding protein levels correlate with aggravation and multiorgan damage in severe COVID-19.

BACKGROUND: Critically ill coronavirus disease 2019 (COVID-19) patients may suffer persistent systemic inflammation and multiple organ failure, leading to a poor prognosis. RESEARCH QUESTION: To examine the relevance of the novel inflammatory factor heparin-binding protein (HBP) in critically ill COVID-19 patients, and evaluate the correlation of the biomarker with disease progression. STUDY DESIGN AND METHODS: 18 critically ill COVID-19 patients who suffered from respiratory failure and sepsis, including 12 cases who experienced a rapidly deteriorating clinical condition and six cases without deterioration, were investigated. They were compared with 15 age- and sex- matched COVID-19-negative patients with respiratory failure. Clinical data were collected and HBP levels were investigated. RESULTS: HBP was significantly increased in critically ill COVID-19 patients following disease aggravation and tracked with disease progression. HBP elevation preceded the clinical manifestations for up to 5 days and was closely correlated with patients' pulmonary ventilation and perfusion status. INTERPRETATION: HBP levels are associated with COVID-19 disease progression in critically ill patients. As a potential mediator of disease aggravation and multiple organ injuries that are triggered by continuing inflammation and oxygen deficits, HBP warrants further study as a disease biomarker and potential therapeutic target.

Investigation of the Status of Nurses Returning to Work After Recovering From COVID-19 and Influencing Factors.

BACKGROUND: More than 3000 medical personnel in China had been infected with coronavirus disease-2019 (COVID-19). We report on 75 previously infected nurses who returned to work. PURPOSE: The aim was to understand the adaptation status of nurses after recovering from COVID-19 and returning to work. METHODS: Data were collected online via the Work Adaptation Scale and the Psychological Capital Scale, and the related influencing factors were analyzed. RESULTS: The social integration and task mastery scores were highest, and the clear roles and cultural adaptation scores were low. The self-efficacy and hope scores were highest, but the resilience and optimism scores were not high. Psychological capital was positively correlated with work adaptation (P < .01). CONCLUSIONS: To ensure the quality and safety of nursing care, nurse managers should adopt effective intervention measures to address the physical and mental health of returning nurses and improve their levels of psychological capital and adaptability.