Multimodal Identification by Transcriptomics and Multiscale Bioassays of Active Components in Xuanfeibaidu Formula to Suppress Macrophage-Mediated Immune Response.

Xuanfeibaidu Formula (XFBD) is a Chinese medicine used in the clinical treatment of coronavirus disease 2019 (COVID-19) patients. Although XFBD has exhibited significant therapeutic efficacy in clinical practice, its underlying pharmacological mechanism remains unclear. Here, we combine a comprehensive research approach that includes network pharmacology, transcriptomics, and bioassays in multiple model systems to investigate the pharmacological mechanism of XFBD and its bioactive substances. High-resolution mass spectrometry was combined with molecular networking to profile the major active substances in XFBD. A total of 154 compounds were identified or tentatively characterized, including flavonoids, terpenes, carboxylic acids, and other types of constituents. Based on the chemical composition of XFBD, a network pharmacology-based analysis identified inflammation-related pathways as primary targets. Thus, we examined the anti-inflammation activity of XFBD in a lipopolysaccharide-induced acute inflammation mice model. XFBD significantly alleviated pulmonary inflammation and decreased the level of serum proinflammatory cytokines. Transcriptomic profiling suggested that genes related to macrophage function were differently expressed after XFBD treatment. Consequently, the effects of XFBD on macrophage activation and mobilization were investigated in a macrophage cell line and a zebrafish wounding model. XFBD exerts strong inhibitory effects on both macrophage activation and migration. Moreover, through multimodal screening, we further identified the major components and compounds from the different herbs of XFBD that mediate its anti-inflammation function. Active components from XFBD, including Polygoni cuspidati Rhizoma, Phragmitis Rhizoma, and Citri grandis Exocarpium rubrum, were then found to strongly downregulate macrophage activation, and polydatin, isoliquiritin, and acteoside were identified as active compounds. Components of Artemisiae annuae Herba and Ephedrae Herba were found to substantially inhibit endogenous macrophage migration, while the presence of ephedrine, atractylenolide, and kaempferol was attributed to these effects. In summary, our study explores the pharmacological mechanism and effective components of XFBD in inflammation regulation via multimodal approaches, and thereby provides a biological illustration of the clinical efficacy of XFBD.

Taurocholic Acid and Glycocholic Acid Inhibit Inflammation and Activate Farnesoid X Receptor Expression in LPS-Stimulated Zebrafish and Macrophages.

A hyperactive immune response can be observed in patients with bacterial or viral infection, which may lead to the overproduction of proinflammatory cytokines, or "cytokine storm", and a poor clinical outcome. Extensive research efforts have been devoted to the discovery of effective immune modulators, yet the therapeutic options are still very limited. Here, we focused on the clinically indicated anti-inflammatory natural product Calculus bovis and its related patent drug Babaodan to investigate the major active molecules in the medicinal mixture. Combined with high-resolution mass spectrometry, transgenic zebrafish-based phenotypic screening, and mouse macrophage models, taurochiolic acid (TCA) and glycoholic acid (GCA) were identified as two naturally derived anti-inflammatory agents with high efficacy and safety. Both bile acids significantly inhibited the lipopolysaccharide-induced macrophage recruitment and the secretion of proinflammatory cytokines/chemokines in in vivo and in vitro models. Further studies identified strongly increased expression of the farnesoid X receptor at both the mRNA and protein levels upon the administration of TCA or GCA, which may be essential for mediating the anti-inflammatory effects of the two bile acids. In conclusion, we identified TCA and GCA as two major anti-inflammatory compounds in Calculus bovis and Babaodan, which could be important quality markers for the future development of Calculus bovis, as well as promising lead compounds in the treatment of overactive immune responses.

Seed amplification assay of nasal swab extracts for accurate and non-invasive molecular diagnosis of neurodegenerative diseases.

Nasal swabs are non-invasive testing methods for detecting diseases by collecting samples from the nasal cavity or nasopharynx. Dysosmia is regarded as an early sign of coronavirus disease 2019 (COVID-19), and nasal swabs are the gold standard for the detection. By nasal swabs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acids can be cyclically amplified and detected using real-time reverse transcriptase-polymerase chain reaction after sampling. Similarly, olfactory dysfunction precedes the onset of typical clinical manifestations by several years in prion diseases and other neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. In neurodegenerative diseases, nasal swab tests are currently being explored using seed amplification assay (SAA) of pathogenic misfolded proteins, such as prion, α-synuclein, and tau. These misfolded proteins can serve as templates for the conformational change of other copies from the native form into the same misfolded form in a prion-like manner. SAA for misfolded prion-like proteins from nasal swab extracts has been developed, conceptually analogous to PCR, showing high sensitivity and specificity for molecular diagnosis of degenerative diseases even in the prodromal stage. Cyclic amplification assay of nasal swab extracts is an attractive and feasible method for accurate and non-invasive detection of trace amount of pathogenic substances for screening and diagnosis of neurodegenerative disease.

Sleep quality and creativity in Chinese college student during the COVID-19 pandemic: The mediating role of executive function.

Background: COVID-19 has impacted adolescents' interpersonal relationships, life attitudes, and mental health during the past 3 years. However, previous studies predominantly focused on negative problems, while few studies assessed the situation of teenagers from the perspective of positive psychology. Therefore, this study explores the creativity level of Chinese college students during the COVID-19 pandemic, the relationship between sleep quality and creativity, and the mediating role of executive function. Method: A cross-sectional study was conducted across six colleges in Heilongjiang in China, with a sample of 4,258 college students recruited via stratified cluster sampling. Data were collected through an online survey. A mediation model was constructed, and SPSS PROCESS macro was used to analyze the data. Results: The creativity score of Chinese college students during the COVID-19 pandemic was 106.48 ± 13.61. Correlation analysis demonstrated that sleep quality correlated negatively with creativity (r = -0.08, P < 0.01) but positively with executive function (r=0.45, P < 0.01), whilst executive function correlated negatively with creativity (r = -0.10, P < 0.01). Moreover, the mediation model revealed that executive function partially mediated the relationship between sleep quality and creativity in college students (indirect effect = -0.017, SE = 0.004, 95% CI = [-0.025, -0.008]). Executive function accounted for 48.6% of the variance in college students' creativity. Conclusion: School administrators should implement measures such as sleep education to enhance students' sleep quality. Concurrently, curriculum and assessment implementation should enhance executive function. Such measures can contribute to improved student creativity, thus helping students overcome the negative emotional impact of the COVID-19 pandemic.

Emergent cesarean section in a preterm pregnant woman with severe COVID-19 pneumonia in Taiwan: A case report.

OBJECTIVE: The pandemic Coronavirus Disease 2019 (COVID-19) is a global public health crisis. Many maternity units worldwide are currently establishing the management protocols for these patients. CASE REPORT: We report the first critically ill pregnant woman with COVID-19-induced respiratory failure undergoing emergent caesarean delivery at 32 weeks of gestation, in the setting of a positive pressure operating room (OR) with negative pressure anteroom in Taiwan. CONCLUSION: Multidisciplinary planning and collaboration are necessary to achieve satisfactory clinical outcomes in pregnancies with critical COVID-19 pneumonia. The combinations of comprehensive evaluation, timely treatment as well as establishment of rigorous protocol and safe environment for the emergent delivery are important.

Factors Influencing Post-traumatic Stress Symptoms in Chinese Adolescents During the COVID-19 Pandemic.

To investigate the prevalence of post-traumatic stress symptoms (PTSSs) and analyze the influencing factors of PTSS among adolescents in a large sample study during the COVID-19 pandemic, we did a cross-sectional study by collecting demographic data and mental health measurements from a large group of 175,318 adolescents in 32 Chinese provinces and autonomous regions, using the Impact of Event Scale-Revised (IES-R) that was used to measure the PTSS of the participants. The results showed that the prevalence of PTSS was 35.7% in Chinese adolescents during the COVID-19 pandemic. Binary logistic regression analysis showed that, for the personal risk factors, the older age, female gender, the personality domains of extroversion, the irregular sleep schedule, the lack of aerobic exercise, and the lack of peer support were associated with the higher levels of PTSS. The family subjective and objective factors were associated with higher levels of PTSS. Our findings suggested that family factors are the most important factors that affect Chinese adolescents' PTSS due to the longtime home quarantine.

One-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification.

Droplet digital polymerase chain reaction (ddPCR) is a third generation of PCR that was recently developed to overcome the limitation of direct quantification observed in real-time quantification PCR (qPCR). Recent studies have shown that ddPCR is more sensitive than the gold standard reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) in detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) samples. In combination with multiplexing, multiple RT-ddPCR assays can be developed to directly quantify different SARS-CoV-2 nucleic acid targets within a single sample, significantly saving on cost and time. Since ddPCR is tolerant to a number of inhibitors unlike qPCR, it can be used to detect and quantify samples from complex environments like wastewater. Here we present three one-step RT-ddPCR protocols on how to develop simplex (one target), duplex (two targets), and triplex probe mix (three targets) assays for SARS-CoV-2 detection and quantification. The assays can be used for diagnosis or other research-related SARS-CoV-2 applications.

Key factors affecting carbon prices from a time-varying perspective.

For humankind to sustain a livable atmosphere on the planet, many countries have committed to achieving carbon neutralization. Countries mainly reduce carbon emissions by regulations through a carbon tax or by establishing a carbon market using economic stimuli. In this paper, we use the least absolute shrinkage and selection operator (LASSO) method to select the key determinants of a carbon market and then use the Markov switching vector autoregression (MSVAR) model to study the market's driving factors and analyze its time-varying characteristics. The results show that there are perceptible time-varying characteristics and notable differences among markets. During COVID-19, energy factors had a long-term shock on the carbon market, economic factors had a short-term shock on the carbon market, and the economic recession has led to fluctuations in the carbon market. In addition, through MSVAR, the results show that the energy market has a negative effect on the carbon market, and the stock market has a positive effect on the carbon market. In periods of low volatility, compared with the natural gas market and coal market, the oil market has a stronger shock on the carbon market. In periods of high volatility, the coal market has a stronger shock on the carbon market. In terms of emission reduction, countries around the world would be wise to change their energy consumption structure, reduce coal use, and shift to a cleaner energy consumption structure.

Mesenchymal Stem Cells-derived Exosomes Ameliorate Lupus by Inducing M2 Macrophage Polarization and Regulatory T Cell Expansion in MRL/lpr Mice.

Previous studies have implicated that the transplantation of human umbilical cord mesenchymal stem cells (hUC-MSCs) effectively alleviates systemic lupus erythematosus (SLE) primarily due to immunomodulatory effects. However, little is known about the role of hUC-MSC-derived exosomes in SLE. This study is carried out to investigate the modifying effects of hUC-MSC-exosomes on the differentiation and function of immune cells in SLE. hUC-MSC-derived exosomes were extracted from the cultural supernatant of hUC-MSCs by ultrahigh speed centrifugation. Quantitative real-time polymerase chain reaction, western blot, enzyme-linked immunosorbent assay, and flow cytometry were performed to estimate the effect of hUC-MSC-derived exosomes on macrophage and regulatory T cell (Treg) polarization. In vivo, hUC-MSC-exosomes were injected intravenously into 28-week-old MRL/lpr mice. We had found that exosomes derived from hUC-MSC restrained the proliferation and inflammation of macrophages in vitro. Besides, MSC-exosomes inhibited CD68+M1 and HLA-DR+M1 but promoted CD206+M2 and CD163+M2 in vitro. Moreover, MRL/lpr mice administrated by intravenous injection of MSC-exosomes had less infiltration of CD14+CD11c+M1 cells but more CD14+CD163+M2 cells as well as Tregs in spleens compared with those in MRL/lpr mice treated by PBS. Additionally, MSC-exosomes could alleviate nephritis, liver and lung injuries of MRL/lpr mice. The survival of lupus mice could be improved after MSC-exosome treatment. This study has suggested that MSC-derived exosomes exert anti-inflammatory and immunomodulatory effects in SLE. MSC-exosomes ameliorate nephritis and other key organ injuries by inducing M2 macrophages and Tregs polarization. As natural nanocarriers, MSC-exosomes may serve as a promising cell-free therapeutic strategy for SLE.Abbreviations: SLE: Systemic lupus erythematosus; hUC-MSCs: Human umbilical cord mesenchymal stem cells; MSCs: Mesenchymal stem cells; qRT-PCR: Quantitative real-time polymerase chain reaction; ELISA: Enzyme-linked immunosorbent assay; Tregs: Regulatory cells; TNF-α: Tumor necrosis factor alfa; IL: Interleukin; COVID-19: Coronavirus disease 2019; pTHP-1: PMA-induced THP-1 macrophages; TEM: Transmission electron microscopy; LPS: Lipopolysaccharide; EVs: Extracellular vesicles; TRAF1: Tumor necrosis factor receptor-associated factor 1; IRAK1: Interferon-α-interleukin-1 receptor-associated kinase 1; NF-κB: Nuclear factor-κB; BLyS: B lymphocyte stimulator; APRIL: A proliferation-inducing ligand.

Emergency management strategies for clinical laboratories on COVID-19 epidemic and future prevention and control recommendations

The epidemic of coronavirus disease 2019 (COVID-19) has been basically contained in China, but increasingly severe overseas. It indicates that COVID-19 has stepped into the stage of"global pandemic". In the process of the prevention and the control of COVID-19 epidemic, clinical laboratory has been playing an important role. To end the epidemic as soon as possible and improve the capacity of anti-epidemic, the management experience and measures of clinical laboratories during the epidemic are summarized. Meanwhile, some suggestions are made for the future prevention and control measures, in case that the COVID-19 becomes seasonal disease or epidemic-prone infectious disease in winter.

CARes-UNet: Content-aware residual UNet for lesion segmentation of COVID-19 from chest CT images.

PURPOSE: Coronavirus disease 2019 (COVID-19) has caused a serious global health crisis. It has been proven that the deep learning method has great potential to assist doctors in diagnosing COVID-19 by automatically segmenting the lesions in computed tomography (CT) slices. However, there are still several challenges restricting the application of these methods, including high variation in lesion characteristics and low contrast between lesion areas and healthy tissues. Moreover, the lack of high-quality labeled samples and large number of patients lead to the urgency to develop a high accuracy model, which performs well not only under supervision but also with semi-supervised methods. METHODS: We propose a content-aware lung infection segmentation deep residual network (content-aware residual UNet (CARes-UNet)) to segment the lesion areas of COVID-19 from the chest CT slices. In our CARes-UNet, the residual connection was used in the convolutional block, which alleviated the degradation problem during the training. Then, the content-aware upsampling modules were introduced to improve the performance of the model while reducing the computation cost. Moreover, to achieve faster convergence, an advanced optimizer named Ranger was utilized to update the model's parameters during training. Finally, we employed a semi-supervised segmentation framework to deal with the problem of lacking pixel-level labeled data. RESULTS: We evaluated our approach using three public datasets with multiple metrics and compared its performance to several models. Our method outperforms other models in multiple indicators, for instance in terms of Dice coefficient on COVID-SemiSeg Dataset, CARes-UNet got the score 0.731, and semi-CARes-UNet further boosted it to 0.776. More ablation studies were done and validated the effectiveness of each key component of our proposed model. CONCLUSIONS: Compared with the existing neural network methods applied to the COVID-19 lesion segmentation tasks, our CARes-UNet can gain more accurate segmentation results, and semi-CARes-UNet can further improve it using semi-supervised learning methods while presenting a possible way to solve the problem of lack of high-quality annotated samples. Our CARes-UNet and semi-CARes-UNet can be used in artificial intelligence-empowered computer-aided diagnosis system to improve diagnostic accuracy in this ongoing COVID-19 pandemic.

Environmental surveillance of SARS-CoV-2 RNA in wastewater systems and related environments in Wuhan: April to May of 2020.

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool in monitoring fecal-oral pathogen infections within a community. Congruently, SARS-CoV-2, the etiologic agent of COVID-19, has been demonstrated to infect the gastrointestinal tissues, and be shed in feces. In the present study, SARS-CoV-2 RNA was concentrated from wastewater, sludge, surface water, ground water, sediment, and soil samples of municipal and hospital wastewater systems and related environments in Wuhan during the COVID-19 middle and low risk periods, and the viral RNA copies quantified using reverse transcription quantitative polymerase chain reaction (RT-qPCR). From the findings of this study, during the middle risk period, one influent sample and three secondary effluents collected from waste water treatment plant 2, as well as two samples from Jinyintan Hospital wastewater system influent were SARS-CoV-2 RNA positive. One sludge sample collected from Guanggu Branch of Tongji Hospital, which was obtained during the low risk period, was also positive for SARS-CoV-2 RNA. These study findings demonstrate the significance of WBE in continuous surveillance of SARS-CoV-2 at the community level, even when the COVID-19 prevalence is low. Overall, this study can be used as an important reference for contingency management of wastewater treatment plants and COVID-19 prevention and control departments of Wuhan.

Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method.

Chest computed tomography (CT) image data is necessary for early diagnosis, treatment, and prognosis of Coronavirus Disease 2019 (COVID-19). Artificial intelligence has been tried to help clinicians in improving the diagnostic accuracy and working efficiency of CT. Whereas, existing supervised approaches on CT image of COVID-19 pneumonia require voxel-based annotations for training, which take a lot of time and effort. This paper proposed a weakly-supervised method for COVID-19 lesion localization based on generative adversarial network (GAN) with image-level labels only. We first introduced a GAN-based framework to generate normal-looking CT slices from CT slices with COVID-19 lesions. We then developed a novel feature match strategy to improve the reality of generated images by guiding the generator to capture the complex texture of chest CT images. Finally, the localization map of lesions can be easily obtained by subtracting the output image from its corresponding input image. By adding a classifier branch to the GAN-based framework to classify localization maps, we can further develop a diagnosis system with improved classification accuracy. Three CT datasets from hospitals of Sao Paulo, Italian Society of Medical and Interventional Radiology, and China Medical University about COVID-19 were collected in this article for evaluation. Our weakly supervised learning method obtained AUC of 0.883, dice coefficient of 0.575, accuracy of 0.884, sensitivity of 0.647, specificity of 0.929, and F1-score of 0.640, which exceeded other widely used weakly supervised object localization methods by a significant margin. We also compared the proposed method with fully supervised learning methods in COVID-19 lesion segmentation task, the proposed weakly supervised method still leads to a competitive result with dice coefficient of 0.575. Furthermore, we also analyzed the association between illness severity and visual score, we found that the common severity cohort had the largest sample size as well as the highest visual score which suggests our method can help rapid diagnosis of COVID-19 patients, especially in massive common severity cohort. In conclusion, we proposed this novel method can serve as an accurate and efficient tool to alleviate the bottleneck of expert annotation cost and advance the progress of computer-aided COVID-19 diagnosis.

Successive Passage In Vitro Led to Lower Virulence and Higher Titer of A Variant Porcine Epidemic Diarrhea Virus.

A highly virulent porcine epidemic diarrhea virus (PEDV) appeared in China and spread rapidly to neighbor countries, which have led to great economic losses to the pig industry. In the present study, we isolated a PEDV using Vero cells and serially propagated 100 passages. PEDV SDSX16 was characterized in vitro and in vivo. The viral titers increased to 107.6 TCID50/mL (100th) by serial passages. The spike (S) gene and the whole gene of the SDSX16 virus was fully sequenced to assess the genetic stability and relatedness to previously identified PEDV. Along with successive passage in vitro, there were 18 nucleotides (nt) deletion occurred in the spike (S) gene resulting in a deletion of six amino acids when the SDSX16 strain was passaged to the 64th generation, and this deletion was stable until the P100. However, the ORF1a/b, M, N, E, and ORF3 genes had only a few point mutations in amino acids and no deletions. According to growth kinetics experiments, the SDSX16 deletion strain significantly enhanced its replication in Vero cells since it was passaged to the 64th generation. The animal studies showed that PEDV SDSX16-P10 caused more severe diarrhea and vomiting, fecal shedding, and acute atrophic enteritis than SDSX16-P75, indicating that SDSX16-P10 is enteropathogenic in the natural host, and the pathogenicity of SDSX16 decreased with successive passage in vitro. However, SDSX16-P10 was found to cause lower levels of cytokine expression than SDSX16-P75 using real-time PCR and flow cytometry, such as IL1ß, IL6, IFN-ß, TNF-α, indicating that SDSX16-P10 might inhibit the expression of cytokines. Our data indicated that successive passage in vitro resulted in virulent attenuation in vivo of the PEDV variant strain SDSX16.

Worries, strategies, and confidence of older Chinese adults during the 2019 novel coronavirus outbreak.

OBJECTIVES: Since the novel coronavirus disease (COVID-19) outbreak started in late 2019, the older population has accounted for a large proportion of severe and fatal cases. This study investigated the mental state and attitudes of older Chinese adults during this epidemic. DESIGN: Cross-sectional online surveys on a convenience sample of China's general population at two different time points. Online surveys were disseminated through popular Chinese social media applications. Adults 18 or older living in China during the initial (N = 1148) and second stages (N = 470) were included in the survey. The Worries, Strategies, and Confidence Questionnaire was created to assess worries and awareness of the disease. RESULTS: Combined responses (N = 1618), 76.1% were female and about 7.0% were 60 years or above. In the first wave, older adults were found less likely to worry about being infected by COVID-19 (p < 0.05) and reported less attention paid to protective measures (p = 0.004) than young adults. However, as the disease evolved, older participants in the second wave were more worried than young adults (p = 0.027) and older adults in the first wave (p = 0.001). CONCLUSIONS: During the epidemic of COVID-19, watchfulness of the epidemic among older Chinese adults fluctuated over time. Initially, they were slow to respond proactively, but their worries gradually increased. Health care and social service professionals need to address the vulnerabilities of older adults to this public health crisis.

Early forecasting of the potential risk zones of COVID-19 in China's megacities.

Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital for the megacities implementing targeted infection prevention and control measures. In this study, the communities with confirmed cases during January 21-February 27 were collected and considered as the specific epidemic data for Beijing, Guangzhou, and Shenzhen. We evaluated the spatiotemporal variations of the epidemics before utilizing the ecological niche models (ENM) to assemble the epidemic data and nine socioeconomic variables for identifying the potential risk zones of this infection in these megacities. Three megacities were differentiated by the spatial patterns and quantities of infected communities, average cases per community, the percentages of imported cases, as well as the potential risks, although their COVID-19 infection situations have been preliminarily contained to date. With higher risks that were predominated by various influencing factors in each megacity, the potential risk zones coverd about 75% to 100% of currently infected communities. Our results demonstrate that the ENM method was capable of being employed as an early forecasting tool for identifying the potential COVID-19 infection risk zones on a fine scale. We suggest that local hygienic authorities should keep their eyes on the epidemic in each megacity for sufficiently implementing and adjusting their interventions in the zones with more residents or probably crowded places. This study would provide useful clues for relevant hygienic departments making quick responses to increasingly severe epidemics in similar megacities in the world.