PddCas: A Polydisperse Droplet Digital CRISPR/Cas-Based Assay for the Rapid and Ultrasensitive Amplification-Free Detection of Viral DNA/RNA.

Clustered regularly interspaced short palindromic repeats (CRISPR)-based assays have been an emerging diagnostic technology for pathogen diagnosis. In this work, we developed a polydisperse droplet digital CRISPR-Cas-based assay (PddCas) for the rapid and ultrasensitive amplification-free detection of viral DNA/RNA with minimum instruments. LbaCas12a and LbuCas13a were used for the direct detection of viral DNA and RNA, respectively. The reaction mixtures were partitioned with a common vortex mixer to generate picoliter-scale polydisperse droplets in several seconds. The limit of detection (LoD) for the target DNA and RNA is approximately 100 aM and 10 aM, respectively, which is about 3 × 104-105 fold more sensitive than corresponding bulk CRISPR assays. We applied the PddCas to successfully detect severe acute respiratory syndrome coronavirus (SARS-CoV-2) and human papillomavirus type 18 (HPV 18) in clinical samples. For the 23 HPV 18-suspected cervical epithelial cell samples and 32 nasopharyngeal swabs for SARS-CoV-2, 100% sensitivity and 100% specificity were demonstrated. The dual-gene virus detection with PddCas was also established and verified. Therefore, PddCas has potential for point-of-care application and is envisioned to be readily deployed for frequent testing as part of an integrated public health surveillance program.

Upregulation of PD-L1 by SARS-CoV-2 promotes immune evasion.

Patients with severe COVID-19 often suffer from lymphopenia, which is linked to T-cell sequestration, cytokine storm, and mortality. However, it remains largely unknown how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces lymphopenia. Here, we studied the transcriptomic profile and epigenomic alterations involved in cytokine production by SARS-CoV-2-infected cells. We adopted a reverse time-order gene coexpression network approach to analyze time-series RNA-sequencing data, revealing epigenetic modifications at the late stage of viral egress. Furthermore, we identified SARS-CoV-2-activated nuclear factor-κB (NF-κB) and interferon regulatory factor 1 (IRF1) pathways contributing to viral infection and COVID-19 severity through epigenetic analysis of H3K4me3 chromatin immunoprecipitation sequencing. Cross-referencing our transcriptomic and epigenomic data sets revealed that coupling NF-κB and IRF1 pathways mediate programmed death ligand-1 (PD-L1) immunosuppressive programs. Interestingly, we observed higher PD-L1 expression in Omicron-infected cells than SARS-CoV-2 infected cells. Blocking PD-L1 at an early stage of virally-infected AAV-hACE2 mice significantly recovered lymphocyte counts and lowered inflammatory cytokine levels. Our findings indicate that targeting the SARS-CoV-2-mediated NF-κB and IRF1-PD-L1 axis may represent an alternative strategy to reduce COVID-19 severity.

Using an untargeted metabolomics approach to analyze serum metabolites in COVID-19 patients with nucleic acid turning negative.

Background: The coronavirus disease of 2019 (COVID-19) is a severe public health issue that has infected millions of people. The effective prevention and control of COVID-19 has resulted in a considerable increase in the number of cured cases. However, little research has been done on a complete metabonomic examination of metabolic alterations in COVID-19 patients following treatment. The current project pursues rigorously to characterize the variation of serum metabolites between healthy controls and COVID-19 patients with nucleic acid turning negative via untargeted metabolomics. Methods: The metabolic difference between 20 COVID-19 patients (CT ≥ 35) and 20 healthy controls were investigated utilizing untargeted metabolomics analysis employing High-resolution UHPLC-MS/MS. COVID-19 patients' fundamental clinical indicators, as well as health controls, were also collected. Results: Out of the 714 metabolites identified, 203 still significantly differed between COVID-19 patients and healthy controls, including multiple amino acids, fatty acids, and glycerophospholipids. The clinical indexes including monocytes, lymphocytes, albumin concentration, total bilirubin and direct bilirubin have also differed between our two groups of participators. Conclusion: Our results clearly showed that in COVID-19 patients with nucleic acid turning negative, their metabolism was still dysregulated in amino acid metabolism and lipid metabolism, which could be the mechanism of long-COVID and calls for specific post-treatment care to help COVID-19 patients recover.

Screening of Gene Expression Markers for Corona Virus Disease 2019 Through Boruta_MCFS Feature Selection.

Since the first report of SARS-CoV-2 virus in Wuhan, China in December 2019, a global outbreak of Corona Virus Disease 2019 (COVID-19) pandemic has been aroused. In the prevention of this disease, accurate diagnosis of COVID-19 is the center of the problem. However, due to the limitation of detection technology, the test results are impossible to be totally free from pseudo-positive or -negative. Improving the precision of the test results asks for the identification of more biomarkers for COVID-19. On the basis of the expression data of COVID-19 positive and negative samples, we first screened the feature genes through ReliefF, minimal-redundancy-maximum-relevancy, and Boruta_MCFS methods. Thereafter, 36 optimal feature genes were selected through incremental feature selection method based on the random forest classifier, and the enriched biological functions and signaling pathways were revealed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Also, protein-protein interaction network analysis was performed on these feature genes, and the enriched biological functions and signaling pathways of main submodules were analyzed. In addition, whether these 36 feature genes could effectively distinguish positive samples from the negative ones was verified by dimensionality reduction analysis. According to the results, we inferred that the 36 feature genes selected via Boruta_MCFS could be deemed as biomarkers in COVID-19.

[Five patients with novel coronavirus Omicron variant of concern infection].

OBJECTIVE: To analyze clinical characteristics of patients with novel coronavirus Omicron variant of concern infection, and to provide practical data and experience for subsequent clinical treatment. METHODS: A retrospective analysis was performed for the clinical data of 5 cases with novel coronavirus Omicron variant of concern infection treated in the First Hospital of Jiaxing from December 18, 2021 to January 28, 2022. The patients' clinical data were recorded, including gender, age, length of hospital stay, vaccination status, clinical symptoms, laboratory indicators [white blood cell count (WBC), lymphocyte count (LYM), eosinophil count (EOS), hypersensitivity C-reactive protein (hs-CRP), novel coronavirus antibody immunoglobulin (IgG and IgM)], chest CT, treatment course and disease outcome. RESULTS: All 5 patients were male, aged 24-37 years old. Four patients were vaccinated with novel coronavirus vaccine (one patient received 3 doses of the vaccine and 3 patients received only the first 2 doses of the vaccine), and no infection was found in chest CT. Laboratory examination showed that WBC, LYM, EOS and hs-CRP levels were normal, and only showed mild symptoms of upper respiratory tract infection. One patient was not vaccinated with novel coronavirus vaccine, and signs of viral pneumonia could be seen in chest CT, laboratory examination showed that WBC and hs-CRP levels increased, suggesting that bacterial infection, fever, cough, sputum and other respiratory symptoms were obvious, and the treatment time was long. All 5 patients were treated with Chinese medicine Lotus antipyretic and Baihu Yinqiao decoction based on routine antiviral therapy. CONCLUSIONS: Patients with novel coronavirus Omicron variant of concern infection vaccinated with the novel coronavirus vaccine have milder clinical symptoms, with less obvious chest CT findings and faster recovery. Chinese medicine Lotus antipyretic and Baihu Yinqiao decoction has obvious therapeutic effect on such patients.

The Effects of Investment in Major Construction Projects on Regional Economic Growth Quality: A Difference-In-Differences Analysis Based on PPP Policy

The investment in Major Construction Projects (MCPs) has a counter-cyclical impact on quantitative GDP increases during the recession period. However, its impact on the quality of economic growth is still unknown. Based on the data of prefecture-level cities in China from 2008 to 2017, we construct an economic Quality Growth Index (QGI) including sustainable development factors and take the PPP (Public–Private Partnership projects) policy as a quasi-natural experiment to design a Difference-In-Differences (DID) strategy for the first time to estimate the effects of the MCPs investment on the sustainable development of regional economies. We find that the MCPs investment can significantly improve the quality of regional economic growth. The MCPs investment can improve the quality of regional economic growth by enhancing innovation and entrepreneurship at the regional levels. Our findings may provide empirical evidence to support the policy of increasing investment into infrastructure constructions to promote sustainable development in the current economic recession under the COVID-19 pandemic.

Mortality in patients with COVID-19 requiring extracorporeal membrane oxygenation: A meta-analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic and significant public health issue. The effectiveness of extracorporeal membrane oxygenation (ECMO) in treating COVID-19 patients has been called into question. AIM: To conduct a meta-analysis on the mortality of COVID-19 patients who require ECMO. METHODS: This analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes 2020 (PRISMA) and has been registered at the International Prospective Register of Systematic Reviews (number CRD42020227414). A quality assessment for all the included articles was performed by the Newcastle-Ottawa Scale (NOS). Studies with tenor more COVID-19 patients undergoing ECMO were included. The random-effects model was used to obtain the pooled incidence of mortality in COVID-19 patients receiving ECMO. The source of heterogeneity was investigated using subgroup and sensitivity analyses. RESULTS: We identified 18 articles with 1494 COVID-19 patients who were receiving ECMO. The score of the quality assessment ranged from 5 to 8 on the NOS. The majority of patients received veno-venous ECMO (93.7%). Overall mortality was estimated to be 0.31 [95% confidence interval (CI): 0.24-0.39; I 2 = 84.8%] based on random-effect pooled estimates. There were significant differences in mortality between location groups (33.0% vs 55.0% vs 37.0% vs 18.0%, P < 0.001), setting groups (28.0% vs 34.0%, P < 0.001), sample size (37.0% vs 31.0%, P < 0.001), and NOS groups (39.0% vs 19.0%, P < 0.001). However, both subgroup analyses based on location, setting, and sample size, and sensitivity analysis failed to identify the source of heterogeneity. The funnel plot indicated no evident asymmetry, and the Egger's (P = 0.95) and Begg's (P = 0.14) tests also revealed no significant publication bias. CONCLUSION: With more resource assessment and risk-benefit analysis, our data reveal that ECMO might be a feasible and effective treatment for COVID-19 patients.

Development and validation of a clinical prediction model to estimate the risk of critical patients with COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. This study was aimed to develop and validate a prediction model based on clinical features to estimate the risk of patients with COVID-19 at admission progressing to critical patients. Patients admitted to the hospital between January 16, 2020, and March 10, 2020, were retrospectively enrolled, and they were observed for at least 14 days after admission to determine whether they developed into severe pneumonia. According to the clinical symptoms, all patients were divided into four groups: mild, normal, severe, and critical. A total of 390 patients with COVID-19 pneumonia were identified, including 212 severe patients and 178 nonsevere patients. The least absolute shrinkage and selection operator (LASSO) regression reduced the variables in the model to 6, which are age, number of comorbidities, computed tomography severity score, lymphocyte count, aspartate aminotransferase, and albumin. The area under curve of the model in the training set is 0.898, and the specificity and sensitivity were 89.7% and 75.5%. The prediction model, nomogram might be useful to access the onset of severe and critical illness among COVID-19 patients at admission, which is instructive for clinical diagnosis.

The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19.

BACKGROUND: This study intends to establish a combined prediction model that integrates the clinical symptoms,the lung lesion volume, and the radiomics features of patients with COVID-19, resulting in a new model to predict the severity of COVID-19. METHODS: The clinical data of 386 patients with COVID-19 at several hospitals, as well as images of certain patients during their hospitalization, were collected retrospectively to create a database of patients with COVID-19 pneumonia. The contour of lungs and lesion locations may be retrieved from CT scans using a CT-image-based quantitative discrimination and trend analysis method for COVID-19 and the Mask R-CNN deep neural network model to create 3D data of lung lesions. The quantitative COVID-19 factors were then determined, on which the diagnosis of the development of the patients' symptoms could be established. Then, using an artificial neural network, a prediction model of the severity of COVID-19 was constructed by combining characteristic imaging features on CT slices with clinical factors. ANN neural network was used for training, and tenfold cross-validation was used to verify the prediction model. The diagnostic performance of this model is verified by the receiver operating characteristic (ROC) curve. RESULTS: CT radiomics features extraction and analysis based on a deep neural network can detect COVID-19 patients with an 86% sensitivity and an 85% specificity. According to the ROC curve, the constructed severity prediction model indicates that the AUC of patients with severe COVID-19 is 0.761, with sensitivity and specificity of 79.1% and 73.1%, respectively. CONCLUSIONS: The combined prediction model for severe COVID-19 pneumonia, which is based on deep learning and integrates clinical aspects, pulmonary lesion volume, and radiomics features of patients, has a remarkable differential ability for predicting the course of disease in COVID-19 patients. This may assist in the early prevention of severe COVID-19 symptoms.

Human urinary kallidinogenase in acute ischemic stroke: A single-arm, multicenter, phase IV study (RESK study).

AIMS: Human urinary kallidinogenase (HUK) has shown favorable efficacies in acute ischemic stroke (AIS) treatment. We sought confirmation of the safety and efficacy of HUK for AIS in a large population. METHODS: RESK study enrolled patients with AIS of anterior circulation to receive HUK infusion. The primary endpoint was the incidence of treatment-emergent adverse events (AEs). Secondary endpoints assessed neurological and functional improvements and stroke recurrent rate. RESULTS: Of 1206 eligible patients, 1202 patients received at least one dose of HUK infusion and 983 (81.5%) completed the study. The incidence of treatment-emergent AEs and serious AEs were 55.99% and 2.41%, respectively. Pre-specified AEs of special interest occurred in 21.71% of patients, but the majority were mild and unrelated to therapy. Hypertension, age, treatment time, and drug combination were identified to be associated with drug-related blood pressure reduction. Neurological and functional evaluations revealed favorable outcomes from baseline to post-treatment assessment. The cumulative recurrence rate of stroke was 2.50% during the 90-day assessment. CONCLUSION: HUK had an acceptable safety and tolerability profile in AIS patients. Besides, HUK demonstrated the neurological and functional improvements in AIS, further confirming its clinical efficacy in a real-world large population.

NK cell receptor and ligand composition influences the clearance of SARS-CoV-2.

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

Correlation Analysis between the Viral Load and the Progression of COVID-19.

OBJECTIVES: This study is aimed at exploring the relationship of the viral load of coronavirus disease 2019 (COVID-19) with lymphocyte count, neutrophil count, and C-reactive protein (CRP) and investigating the dynamic change of patients' viral load during the conversion from mild COVID-19 to severe COVID-19, so as to clarify the correlation between the viral load and progression of COVID-19. METHODS: This paper included 38 COVID-19 patients admitted to the First Hospital of Jiaxing from January 28, 2020, to March 6, 2020, and they were clinically classified according to the Guidelines on the Novel Coronavirus-Infected Pneumonia Diagnosis and Treatment. According to the instructions of the Nucleic Acid Detection Kit for the 2019 novel coronavirus (SARS-CoV-2), respiratory tract specimens (throat swabs) were collected from patients for nucleic acid testing. Patients' lymphocyte count and neutrophil count were determined by blood routine examination, and CRP was measured by biochemical test. RESULTS: The results of our study suggested that the cycle threshold (Ct) value of Nucleocapsid protein (N) gene examined by nucleic acid test was markedly positively correlated with lymphocyte count (p = 0.0445, R 2 = 0.1203), but negatively correlated with neutrophil count (p = 0.0446, R 2 = 0.1167) and CRP (p = 0.0393, R 2 = 0.1261), which indicated that patients with a higher viral load tended to have lower lymphocyte count but higher neutrophil count and CRP. Additionally, we detected the dynamic change of Ct value in patients who developed into a severe case, finding that viral load of 3 patients increased before disease progression, whereas this phenomenon was not found in 2 patients with underlying diseases. CONCLUSION: The results of this study demonstrated that viral load of SARS-CoV-2 is significantly negatively correlated with lymphocyte count, but markedly positively correlated with neutrophil count and CRP. The rise of viral load is very likely to be the key factor leading to the overloading of the body's immune response and resulting in the disease progression into severe disease.

The Relationship Among Organizational Identity, Psychological Resilience and Work Engagement of the First-Line Nurses in the Prevention and Control of COVID-19 Based on Structural Equation Model.

PURPOSE: To explore how the organizational identity and psychological resilience affect work engagement of the front-line nurses in the prevention and control of coronavirus disease 2019 (COVID-19) and to establish the relationship model based on these factors. MATERIAL AND METHODS: Convenience sampling was applied to collect questionnaire samples from 216 nurses (from 12 cities in 6 provinces). General information questionnaires, organizational identity scale (OIQ), psychological resilience scale (CD-RISC), and Utrecht Work Engagement Scale (UWES) were used as tools for data collection. RESULTS: Both organizational identification and psychological resilience had a positive impact on work engagement (r=0.457~0.669). The structural equation model indicated that psychological resilience had a significant partial mediating effect on the relationship between organizational identity and work engagement; the mediating effect value was 0.25, the overall effect value of work engagement was 0.73, and the mediating effect accounted for 34.2%. CONCLUSION: Our results revealed that organizational identity could directly affect nursing. It can also indirectly affect nurses' work engagement through the intermediary role of psychological resilience. In face of the COVID-19 epidemic, hospitals and nursing managers could improve the level of nurses' job involvement by improving organizational identity, which in turn may have a positive effect on psychological resilience.

Transmission Potential of Asymptomatic and Paucisymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infections: A 3-Family Cluster Study in China.

Data concerning the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in asymptomatic and paucisymptomatic patients are lacking. We report a 3-family cluster of infections involving asymptomatic and paucisymptomatic transmission. Eight of 15 (53%) members from 3 families were confirmed with SARS-CoV-2 infection. Of 8 patients, 3 were asymptomatic and 1 was paucisymptomatic. An asymptomatic mother transmitted the virus to her son, and a paucisymptomatic father transmitted the virus to his 3-month-old daughter. SARS-CoV-2 was detected in the environment of 1 household. The complete genomes of SARS-CoV-2 from the patients were > 99.9% identical and were clustered with other SARS-CoV-2 sequences reported from China and other countries.

A study on clinical effect of Arbidol combined with adjuvant therapy on COVID-19.

This study aims to explore the clinical effect of Arbidol (ARB) combined with adjuvant therapy on patients with coronavirus disease 2019 (COVID-19). The study included 62 patients with COVID-19 admitted to the First Hospital of Jiaxing from January to March 2020, and all patients were divided into the test group and the control group according to whether they received ARB during hospitalization. Various indexes in the two groups before and after treatment were observed and recorded, including fever, cough, hypodynamia, nasal obstruction, nasal discharge, diarrhea, C-reactive protein (CRP), procalcitonin (PCT), blood routine indexes, blood biochemical indexes, time to achieve negative virus nucleic acid, and so on. The fever and cough in the test group were relieved markedly faster than those in the control group (P < .05); there was no obvious difference between the two groups concerning the percentage of patients with abnormal CRP, PCT, blood routine indexes, aspartate aminotransferase, and alanine aminotransferase (P > .05); the time for two consecutive negative nucleic acid tests in the test group were shorter than that in the control group; the hospitalization period of the patients in the test group and control group were (16.5 ± 7.14) days and (18.55 ± 7.52) days, respectively. ARB combined with adjuvant therapy might be able to relieve the fever of COVID-19 sufferers faster and accelerate the cure time to some degree, hence it's recommended for further research clinically.