Establishment of a triplex TaqMan quantitative real-time PCR assay for simultaneous detection of Cymbidium mosaic virus, Odontoglossum ringspot virus and Cymbidium ringspot virus.

Orchids are significant ornamental plants whose viral infection results in substantial economic damage. Cymbidium mosaic virus (CymMV), Odontoglossum ringspot virus (ORSV), and Cymbidium ringspot virus (CymRSV) represent three important and prevalent orchid viruses. The detection system proposed in this study uses a triplex TaqMan quantitative real-time PCR assay to identify CymMV, ORSV, and CymRSV in a simultaneous manner. We designed specific primers and probes for CymMV, ORSV, and CymRSV, with amplified sequences of 156 bp, 148 bp, and 145 bp, respectively. The minimum detection limit of the triplex qRT-PCR assay for CymMV and CymRSV was 1 copy/assay, and the minimum detection limit was 10 copies/assay for ORSV. The minimum stable detection limits for CymMV, ORSV, and CymRSV were 10, 102, and 102 copies/assay, respectively. Therefore, this system exhibited higher sensitivity (approximately 10 to 104-fold) than RT-PCR. The intra-and interassay CVs of Cq values are less than 0.55 and 0.95%, respectively, indicating that the triplex assay is highly reliable and accurate. In addition, 66 samples from five different orchid genera were analyzed using the established assay and gene chip. The detection results demonstrated that the triplex probe qRT-PCR demonstrated higher sensitivity than the gene chip, indicating that the triplex real-time PCR assay could be used for the detection of field samples. Our findings suggest that the triplex real-time RT-PCR detection system represents a rapid, simple, and accurate tool for detecting CymMV, ORSV, and CymRSV on orchids.

Development of Porcine Monoclonal Antibodies with In Vitro Neutralizing Activity against Classical Swine Fever Virus from C-Strain E2-Specific Single B Cells.

Neutralizing antibodies (nAbs) can be used before or after infection to prevent or treat viral diseases. However, there are few efficacious nAbs against classical swine fever virus (CSFV) that have been produced, especially the porcine-originated nAbs. In this study, we generated three porcine monoclonal antibodies (mAbs) with in vitro neutralizing activity against CSFV, aiming to facilitate the development of passive antibody vaccines or antiviral drugs against CSFV that offer the advantages of stability and low immunogenicity. Pigs were immunized with the C-strain E2 (CE2) subunit vaccine, KNB-E2. At 42 days post vaccination (DPV), CE2-specific single B cells were isolated via fluorescent-activated cell sorting (FACS) baited by Alexa Fluor™ 647-labeled CE2 (positive), goat anti-porcine IgG (H + L)-FITC antibody (positive), PE mouse anti-pig CD3ε (negative) and PE mouse anti-pig CD8a (negative). The full coding region of IgG heavy (H) chains and light (L) chains was amplified by reverse transcription-polymerase chain reaction (RT-PCR). Overall, we obtained 3 IgG H chains, 9 kappa L chains and 36 lambda L chains, which include three paired chains (two H + κ and one H + λ). CE2-specific mAbs were successfully expressed in 293T cells with the three paired chains. The mAbs exhibit potent neutralizing activity against CSFVs. They can protect ST cells from infections in vitro with potent IC50 values from 14.43 µg/mL to 25.98 µg/mL for the CSFV C-strain, and 27.66 µg/mL to 42.61 µg/mL for the CSFV Alfort strain. This study is the first report to describe the amplification of whole-porcine IgG genes from single B cells of KNB-E2-vaccinated pig. The method is versatile, sensitive, and reliable. The generated natural porcine nAbs can be used to develop long-acting and low-immunogenicity passive antibody vaccine or anti-CSFV agents for CSF control and prevention.

Exploring middle school students' attitudes and satisfaction about home-based online education during the COVID-19 epidemic and the influential variables

Background: Students' attitudes and satisfaction are important predictors of educational quality, especially under such special situation as large scale home-based online education during the COVID-19 epidemic. Objectives: This study investigated middle school students' attitudes and satisfaction about home-based online education during COVID-19 epidemic and potential influential variables. Methods: Survey data were collected from 788 middle school students in two typical Chinese public schools. Multinomial logistic regression analysis and ordinal logistic regression analysis were used to identify influential variables. Findings: We found that more than half of surveyed students felt that home-based online learning was either the same as (35.9%) or better than (18%) traditional face-to-face learning, while 46.1% felt that it was worse than traditional face-to-face learning. More than six tenth of surveyed students felt satisfied or very satisfied with their home-based online education, while less than one third kept neutral attitudes and very few felt unsatisfied or very unsatisfied. Importantly, the study found some influential variables impacting students' attitudes and satisfaction about home-based online education and they included individual variables (gender, time spent in doing homework, level of learning engagement), organizational variables (school type), and relational variables (time spent on communication and relationship with family members). (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently datasets associated in both with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes. Results can be explored at: https://covid.proteomics.wustl.edu/. Graphical abstract

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways.

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Advancing pathogen detection for airborne diseases

Airborne diseases including SARS, bird flu, and the ongoing Coronavirus Disease 2019 (COVID-19) have stimulated the demand for developing novel bioassay methods competent for early-stage diagnosis and large-scale screening. Here, we briefly summarize the state-of-the-art methods for the detection of infectious pathogens and discuss key challenges. We highlight the trend for next-generation technologies benefiting from multidisciplinary advances in microfabrication, nanotechnology and synthetic biology, which allow sensitive, rapid yet inexpensive pathogen assays with portable intelligent device.

Correction: A smartphone-based three-in-one biosensor for co-detection of SARS-CoV-2 viral RNA, antigen and antibody.

Correction for 'A smartphone-based three-in-one biosensor for co-detection of SARS-CoV-2 viral RNA, antigen and antibody' by Yanzhi Dou et al., Chem. Commun., 2022, DOI: https://doi.org/10.1039/d2cc01297a.

A smartphone-based three-in-one biosensor for co-detection of SARS-CoV-2 viral RNA, antigen and antibody.

Rapid and comprehensive diagnostic methods are necessary for early identification and monitoring of SARS-CoV-2. Here, we have developed a universal and portable three-in-one biosensor linked to a smartphone for co-detection of SARS-CoV-2 viral RNA, antigen, and antibody. In combination with a smartphone, the online monitoring of SARS-CoV-2 virus-infected patients from infection to immunization could be intelligently achieved.

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.

An Illustrated Guide to the Imaging Evolution of COVID in Non-Epidemic Areas of Southeast China.

Purpose: By analyzing the CT manifestations and evolution of COVID in non-epidemic areas of southeast China, analyzing the developmental abnormalities and accompanying signs in the early and late stages of the disease, providing imaging evidence for clinical diagnosis and identification, and assisting in judging disease progression and monitoring prognosis. Methods: This retrospective and multicenter study included 1,648 chest CT examinations from 693 patients with laboratory-confirmed COVID-19 infection from 16 hospitals of southeast China between January 19 and March 27, 2020. Six trained radiologists analyzed and recorded the distribution and location of the lesions in the CT images of these patients. The accompanying signs include crazy-paving sign, bronchial wall thickening, microvascular thickening, bronchogram sign, fibrous lesions, halo and reverse-halo signs, nodules, atelectasis, and pleural effusion, and at the same time, they analyze the evolution of the abovementioned manifestations over time. Result: There were 1,500 positive findings in 1,648 CT examinations of 693 patients; the average age of the patients was 46 years, including 13 children; the proportion of women was 49%. Early CT manifestations are single or multiple nodular, patchy, or flaky ground-glass-like density shadows. The frequency of occurrence of ground-glass shadows (47.27%), fibrous lesions (42.60%), and microvascular thickening (40.60%) was significantly higher than that of other signs. Ground-glass shadows increase and expand 3-7 days after the onset of symptoms. The distribution and location of lesions were not significantly related to the appearance time. Ground-glass shadow is the most common lesion, with an average absorption time of 6.2 days, followed by consolidation, with an absorption time of about 6.3 days. It takes about 8 days for pure ground-glass lesions to absorb. Consolidation change into ground glass or pure ground glass takes 10-14 days. For ground-glass opacity to evolve into pure ground-glass lesions, it takes an average of 17 days. For ground-glass lesions to evolve into consolidation, it takes 7 days, pure ground-glass lesions need 8 days to evolve into ground-glass lesions. The average time for CT signs to improve is 10-15 days, and the first to improve is the crazy-paving sign and nodules; while the progression of the disease is 6-12 days, the earliest signs of progression are air bronchogram signs, bronchial wall thickening, and bronchiectasis. There is no severe patient in this study. Conclusion: This study depicts the CT manifestation and evolution of COVID in non-epidemic origin areas, and provides valuable first-hand information for clinical diagnosis and judgment of patient's disease evolution and prediction.

Multichannel Immunosensor Platform for the Rapid Detection of SARS-CoV-2 and Influenza A(H1N1) Virus.

The coronavirus disease 2019 (COVID-19) can present a similar syndrome to an influenza infection, which may complicate diagnosis and clinical management of these two important respiratory infectious diseases, especially during the peak season of influenza. A rapid and convenient point-of-care test (POCT) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus is of great importance for prompt and efficient control of these respiratory epidemics. Herein, a multichannel electrochemical immunoassay (MEIA) platform was developed based on a disposable screen-printed carbon electrode (SPCE) array for the on-site detection of SARS-CoV-2 and A(H1N1). The developed MEIA was constructed with eight channels and allowed rapid detection on a single array. On the SPCE surface, monoclonal antibodies against influenza A(H1N1) hemagglutinin (HA) protein or SARS-CoV-2 spike protein were coated to capture the target antigens, which then interacted with a horseradish peroxidase (HRP)-labeled detection antibody to form an immuno-sandwich complex. The results showed that the MEIA exhibited a broader linear range than ELISA and comparable sensitivity for A(H1N1) HA and SARS-CoV-2 spike protein. The detection results on 79 clinical samples for A(H1N1) suggested that the proposed MEIA platform showed comparable results with ELISA in sensitivity (with a positive rate of 100% for positive samples) but higher specificity, with a false-positive rate of 5.4% for negative samples versus that of 40.5% with ELISA. Thus, it offers great potential for the on-the-spot differential diagnosis of infected patients, which would significantly benefit the efficient control and prevent the spread of these infectious diseases in communities or resource-limited regions in the future.

A rapid screening classifier for diagnosing COVID-19.

Rationale: Coronavirus disease 2019 (COVID-19) has caused a global pandemic. A classifier combining chest X-ray (CXR) with clinical features may serve as a rapid screening approach. Methods: The study included 512 patients with COVID-19 and 106 with influenza A/B pneumonia. A deep neural network (DNN) was applied, and deep features derived from CXR and clinical findings formed fused features for diagnosis prediction. Results: The clinical features of COVID-19 and influenza showed different patterns. Patients with COVID-19 experienced less fever, more diarrhea, and more salient hypercoagulability. Classifiers constructed using the clinical features or CXR had an area under the receiver operating curve (AUC) of 0.909 and 0.919, respectively. The diagnostic efficacy of the classifier combining the clinical features and CXR was dramatically improved and the AUC was 0.952 with 91.5% sensitivity and 81.2% specificity. Moreover, combined classifier was functional in both severe and non-serve COVID-19, with an AUC of 0.971 with 96.9% sensitivity in non-severe cases, which was on par with the computed tomography (CT)-based classifier, but had relatively inferior efficacy in severe cases compared to CT. In extension, we performed a reader study involving three experienced pulmonary physicians, artificial intelligence (AI) system demonstrated superiority in turn-around time and diagnostic accuracy compared with experienced pulmonary physicians. Conclusions: The classifier constructed using clinical and CXR features is efficient, economical, and radiation safe for distinguishing COVID-19 from influenza A/B pneumonia, serving as an ideal rapid screening tool during the COVID-19 pandemic.

COVID­19 and ischemic stroke: Mechanisms of hypercoagulability (Review).

During the coronavirus disease 2019 (COVID­19) pandemic, some patients with severe COVID­19 exhibited complications such as acute ischemic stroke (AIS), which was closely associated with a poor prognosis. These patients often had an abnormal coagulation, namely, elevated levels of D­dimer and fibrinogen, and a low platelet count. Certain studies have suggested that COVID­19 induces AIS by promoting hypercoagulability. Nevertheless, the exact mechanisms through which COVID­19 leads to a hypercoagulable state in infected patients remain unclear. Understanding the underlying mechanisms of hypercoagulability is of utmost importance for the effective treatment of these patients. The present review aims to summarize the current status of research on COVID­19, hypercoagulability and ischemic stroke. The present review also aimed to shed light into the underlying mechanisms through which COVID­19 induces hypercoagulability, and to provide therapies for different mechanisms for the more effective treatment of patients with COVID­19 with ischemic stroke and prevent AIS during the COVID­19 pandemic.

Temporal changes of COVID-19 pneumonia by mass evaluation using CT: a retrospective multi-center study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has widely spread worldwide and caused a pandemic. Chest CT has been found to play an important role in the diagnosis and management of COVID-19. However, quantitatively assessing temporal changes of COVID-19 pneumonia over time using CT has still not been fully elucidated. The purpose of this study was to perform a longitudinal study to quantitatively assess temporal changes of COVID-19 pneumonia. METHODS: This retrospective and multi-center study included patients with laboratory-confirmed COVID-19 infection from 16 hospitals between January 19 and March 27, 2020. Mass was used as an approach to quantitatively measure dynamic changes of pulmonary involvement in patients with COVID-19. Artificial intelligence (AI) was employed as image segmentation and analysis tool for calculating the mass of pulmonary involvement. RESULTS: A total of 581 confirmed patients with 1,309 chest CT examinations were included in this study. The median age was 46 years (IQR, 35-55; range, 4-87 years), and 311 (53.5%) patients were male. The mass of pulmonary involvement peaked on day 10 after the onset of initial symptoms. Furthermore, the mass of pulmonary involvement of older patients (>45 years) was significantly severer (P<0.001) and peaked later (day 11 vs. day 8) than that of younger patients (≤45 years). In addition, there were no significant differences in the peak time (day 10 vs. day 10) and median mass (P=0.679) of pulmonary involvement between male and female. CONCLUSIONS: Pulmonary involvement peaked on day 10 after the onset of initial symptoms in patients with COVID-19. Further, pulmonary involvement of older patients was severer and peaked later than that of younger patients. These findings suggest that AI-based quantitative mass evaluation of COVID-19 pneumonia hold great potential for monitoring the disease progression.

SARS-CoV-2 RNA reference materials

Coronavirus disease (COVID-19) is an acute infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Reverse transcription real-time fluorescent quantitative polymerase chain reaction (RT-qPCR) was the firstly authorized method for the detection of SARS-CoV-2 RNA. As this method is sensitive, specific, it has been widely recognized as the golden standard for the diagnosis of COVID-19. Unfortunately, several false-negative cases have been reported after the outbreak of COVID-19, probably due to the quality of the kits or the improper operation of RT-qPCR. Nucleic acid reference materials (RM) are the key element for the metrology traceability and quality control of SARS-CoV-2 RNA detection, but the development of RNA RM remains a challenge in the biology metrology field. Two main problems are the low stability of the RNA sample and the lack of proven absolute quantification methods. To establish the measurement traceability for SARS-CoV-2 RNA detection, a novel RNA reference material (RM) was developed. The RM is a mixed solution of 3 in vitro transcribed RNA molecules which cover different key target sequences of SARS-CoV-2 gene: The full-length of nucleoprotein (N) gene (28274-29533, GenBank: MT027064.1), the full-length of envelope protein (E) gene (26245-26472, GenBank: MT027064.1), and partial sequence of open reading frame 1ab (ORF1ab) (13321-15540, GenBank: MT027064.1). The purity of the transcribed RNA molecules was verified by a biological analyzer. The results showed that the molecular length of all the RNA molecules were consistent with our design. The clear peaks of our RNA RMs strongly demonstrated good purity. For absolute quantification of RNA RMs, we studied digital PCR (dPCR) for RNA samples. Digital PCR evenly partitioned the sample and PCR reaction solution to a very large number of units, on a microporous chip or in the liquid droplets, etc. After a PCR amplification reaction, the fluorescence signal was detected for each unit individually, with a binary readout of "0" or "1" for negative and positive results respectively. Through the statistics of positive results based on the Poisson distribution, the copy number of RNA sample was accurately determined without standard curves needed. Digital PCR has significantly higher reliability and accuracy. Mainly based on the PCR primers and probes for SARS-CoV-2 detection suggested by the Chinese CDC and WHO, we optimized the key factors of dPCR towards improved amplification efficiency. Through digital PCR measurements by 4 laboratories, the certified values of concentration (copies/mu L) were assigned for the N gene, E gene, and ORF1ab gene in the mixed RM. Single-stranded RNA is unstable and easy to be degraded by RNase in the environment, thus the optimization of RNA protectants is very important for the stability of RNA RMs. During the study of the stability, we found that a proper protector (1 mmol/L DTT and 0.5 U/L Rnase Inhibitor) can effectively increase the valid storage life of our RNA RM. Based on the latest data, the concentration of our RNA RMs was stable for at least 30 d under -80 degrees C storage and 13 d under -4 degrees C storage. In order to verify the applicability of our RNA RM in the actual virus detection process, we analyzed our RMs using 9 SARS-CoV-2 nucleic acid detection kits. These virus RNA detection kits were from different manufacturers with various detection principles, that are being applied in laboratories for virus detection. Finally, our RNA RMs showed high generalizability among 9 kits. The development of RNA RM provides the metrological basis for the quality control of SARS-CoV-2 detection kits.