Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics.

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

Compatibility of Fuzi and Ginseng Significantly Increase the Exposure of Aconitines.

The herb-pair ginseng-Fuzi (the root of Aconitum carmichaelii) is the material basis of Shenfu prescriptions and is popular in traditional Chinese medicine for the treatment of heart failure, and even shock with severe-stage of COVID-19. A narrow therapeutic window of Fuzi may cause significant regional loss of property and life in clinics. Therefore, systemic elucidation of active components is crucial to improve the safety dose window of Shenfu oral prescriptions. A high performance liquid chromatography-mass spectrometry method was developed for quantification of 10 aconitines in SD rat plasma within 9 min. The limit of detection and the limit of quantification were below 0.032 ng/ml and 0.095 ng/ml, respectively. Furthermore, a systemic comparison with their pharmacokinetic characteristics after oral administration of a safe dosage of 2 g/kg of Fuzi and ginseng-Fuzi decoction for 24 h was conducted. Eight representative diester, monoester, and non-ester aconitines and two new active components (i.e., songorine and indaconitine) were all adopted to elucidating the differences of the pharmacokinetic parameters in vivo. The compatibility of Fuzi and ginseng could significantly increase the in vivo exposure of active components. The terminal elimination half-life and the area under the concentration-time curve of mesaconitine, benzoylaconitine, benzoylmesaconitine, benzoylhypaconitine, and songorine were all increased significantly. The hypaconitine, benzoylmesaconitine, and songorine were regarded as the main active components in vivo, which gave an effective clue for the development of new Shenfu oral prescriptions.

Flavonoids for Treating Viral Acute Respiratory Tract Infections: A Systematic Review and Meta-Analysis of 30 Randomized Controlled Trials.

BACKGROUND: This meta-analysis aimed to investigate the efficacy and safety of flavonoids in treating viral acute respiratory tract infections (ARTIs). METHODS: Randomized controlled trials (RCTs) were entered into meta-analyses performed separately for each indication. Efficacy analyses were based on changes in disease-specific symptom scores. Safety was analyzed based on the pooled data from all eligible trials, by comparing the incidence of adverse events between flavonoids and the control. RESULTS: In this study, thirty RCTs (n = 5,166) were included. In common cold, results showed that the flavonoids group decreased total cold intensity score (CIS), the sum of sum of symptom intensity differences (SSID) of CIS, and duration of inability to work vs. the control group. In influenza, the flavonoids group improved the visual analog scores for symptoms. In COVID-19, the flavonoids group decreased the time taken for alleviation of symptoms, time taken for SARS-CoV-2 RT-PCR clearance, the RT-PCR positive subjects at day 7, time to achievement of the normal status of symptoms, patients needed oxygen, patients hospitalized and requiring mechanical ventilation, patients in ICU, days of hospitalization, and mortality vs. the control group. In acute non-streptococcal tonsillopharyngitis, the flavonoids group decreased the tonsillitis severity score (TSS) on day 7. In acute rhinosinusitis, the flavonoids group decreased the sinusitis severity score (SSS) on day 7, days off work, and duration of illness. In acute bronchitis, the flavonoids group decreased the bronchitis severity score (BSS) on day 7, days off work, and duration of illness. In bronchial pneumonia, the flavonoids group decreased the time to symptoms disappearance, the level of interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-α (TNF-α). In upper respiratory tract infections, the flavonoids group decreased total CIS on day 7 and increased the improvement rate of symptoms. Furthermore, the results of the incidence of adverse reactions did not differ between the flavonoids and the control group. CONCLUSION: Results from this systematic review and meta-analysis suggested that flavonoids were efficacious and safe in treating viral ARTIs including the common cold, influenza, COVID-19, acute non-streptococcal tonsillopharyngitis, acute rhinosinusitis, acute bronchitis, bronchial pneumonia, and upper respiratory tract infections. However, uncertainty remains because there were few RCTs per type of ARTI and many of the RCTs were small and of low quality with a substantial risk of bias. Given the limitations, we suggest that the conclusions need to be confirmed on a larger scale with more detailed instructions in future studies.Systematic Review Registration: inplasy.com/inplasy-2021-8-0107/, identifier: INPLASY20218010.

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

OBJECTIVE: Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies. METHODS: We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score. RESULTS: A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio ( OR, 1.27; 95% CI, 1.15-1.39), albumin ( OR, 0.76; 95% CI, 0.70-0.83), and chest computed tomography abnormalities ( OR, 2.01; 95% CI, 1.41-2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667-0.8776). CONCLUSION: This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.

Global analysis of the COVID-19 research landscape and scientific impact.

OBJECTIVES: To consider a 1-year time window of the coronavirus disease 2019 (COVID-19) crisis to integrate qualitative and quantitative data and provide an in-depth analysis of all COVID-19 publications from geographical, epidemiological and chronological perspectives. METHODS: Publications on COVID-19 from December 1, 2019, to December 31, 2020 without document type limitations were extracted from the Web of Science database. Microsoft Excel 2016, GraphPad Prism 9, VOSviewer 1.6.15 and IBM SPSS 21.0 were used to analyze the global epidemiological publication landscape and its correlations, research hotspots around the world and the top 5 countries in terms of publications. RESULTS: A total of 51,317 documents were analyzed in the present study. The publication trend could be divided into an increasing output stage and an explosive output stage. There were positive correlations between monthly publications, confirmed cases and deaths. Research hotspots from the whole year, from individual quarters, and from the top 5 countries with the most publications were further identified. CONCLUSIONS: The correlation analysis of publications indicated that confirmed cases and deaths were forces driving the scientific output, reflecting the growing trend to some extent. Moreover, the hotspot analysis provided valuable information for scientists, funders, policy and decision-makers to determine what areas should be their focus when faced with public health emergencies in the future.

Bibliometric analysis of mental health during the COVID-19 pandemic.

BACKGROUND: As a global pandemic, coronavirus disease 2019 (COVID-19) has had a profound effect on public mental health. METHODS: Publications related to mental health during the COVID-19 pandemic from December 1, 2019, to November 13, 2020, were extracted from the Web of Science database. Bibliometric indicator analysis was performed using VOSviewer 1.6.15. RESULTS: In total, 1233 documents from 2020 were retrieved, of which 680 were original articles. The United States contributed the largest publication output (285, 23.1%). Huazhong University of Science and Technology published the most articles in this field (35), while Wuhan University received the most citations (1149). The United Kingdom had the strongest collaboration network. Four keyword clusters representing hotspots in this field were identified. CONCLUSIONS: In addition to developed countries, countries seriously affected by the COVID-19 pandemic also made significant contributions to mental health research during the COVID-19 pandemic. This study focused on various aspects, such as mental health during isolation, mental health in healthcare workers, and public mental health issues during the COVID-19 pandemic. In the future, countries should strengthen global cooperation and pay more attention to the mental health of vulnerable groups during pandemics.

Comparison with Pharmacokinetic Characteristics of Aconitines after Compatibility with Fuzi and Ginseng (preprint)

The herb-pair Gingseng-Fuzi (the root of Aconitum carmichaelii ) is named as Shenfu prescriptions and is popular in traditional Chinese medicine for treatment of heart failure, and even shock with severe-stage COVID-19. However, a narrow therapeutic window of Fuzi may cause significant regional loss of property and life in clinics. Therefore, systemic elucidation of compatibility mechanism using in vivo comparative exposure is particularly crucial to improve the safety dose window of Shenfu prescriptions. A high performance liquid chromatography-mass spectrometry method was developed for quantification of 11 aconitines in SD rat plasma within 9 min, and a systemic comparison with their pharmacokinetic characteristics after oral administration of a safe dosage of 2 g/Kg of Fuzi and Ginseng-Fuzi decoction for 24 h was conducted. Nine representative diester, monoester, and non-ester aconitines and two new active components ( e . g . songorine and indaconitine) were all adopted to elucidation of the differences of the contents in decoction and the pharmacokinetic parameters in vivo , including the terminal elimination half-life (T1/2), area under the concentration-time curve, mean residence time, time to achieve maximum concentration (Cmax), and maximum plasma concentration. It was found that the compatibility with Fuzi and gingseng could significantly increase their bioavailability of active components. Moreover, the in vivo exposure and the T1/2 of diester aconitines (aconitine and mesaconitine) and the monoester aconitines (benzoylaconitine, benzoylmesaconitine, and benzoylhypaconitine) were all increased significantly, indicating the efficacy was increased simultaneously. Songorine shown the largest Cmax with a potential decardiotoxicity ability. This study provided a solid pharmacokinetic parameters for development of safe and effective new Shenfu oral prescriptions.

Early Treatment Effect of Chinese Herbal Medicine Formula Huashibaidu Granule on Mild COVID-19 Patients in Fangcang Hospital: An Unblinded, Cluster-Randomized Clinical Trial (preprint)

BACKGROUND: Previous study suggested that Chinese Herbal Medicine (CHM) Formula Huashibaidu granule might shorten disease course of Corona Virus Disease 2019 (COVID-19) patients. Our research aims to investigate the early treatment effect of Huashibaidu granule in mild COVID-19 patients under well clinical management.METHODS: An unblended cluster-randomized clinical trial was conducted at the Dongxihu FangCang hospital. 2 cabins were randomly allocated to CHM or control group, with 204 randomly sampled mild COVID-19 patients in each cabin. All participants received a 7-day conventional treatment, and CHM group cabin used additional Huashibaidu granule 10g twice daily. Participants were followed up until they met clinical endpoint. The primary outcome was patient become worsening before clinical endpoint occurred. The secondary outcomes was discharge with cure before clinical endpoint occurred and relief of composite symptoms after 7 days treatment.FINDINGS: All 408 participants were followed up to meet clinical endpoint and included in statistical analysis. The baseline characteristics were comparable between 2 groups. The number of worsening patients in the CHM group was 5 (2.5%), and that in the control group was 16 (7.8%). There was a significant difference between groups (P=0.014). 8 foreseeable mild adverse events occurred without statistical difference between groups.INTERPRETATION: 7-day early treatment with Huashibaidu granule reduced worsening conversion of mild COVID-19 patients. Our study supports Huashibaidu Granule as an active option for early treatment of mild COVID-19 in similar medical locations with well management.TRIAL REGISTRATION: The Chinese Clinical Trial Registry: ChiCTR2000029763.FUNDING: This study was supported by “National Key R&D Program of China” (No.2020YFC0841500).DECLARATION OF INTERESTS: The authors guaranteed that there existed no competing interest in this paper.ETHICS APPROVAL STATEMENT: Ethics Review Committee of Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences Approval of Ethical Review Acceptance Number: S2020-001; Approval Number: P20001/PJ01.

COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a major pandemic outbreak recently. Various diagnostic technologies have been under active development. The novel coronavirus disease (COVID-19) may induce pulmonary failures, and chest X-ray imaging becomes one of the major confirmed diagnostic technologies. The very limited number of publicly available samples has rendered the training of the deep neural networks unstable and inaccurate. This study proposed a two-step transfer learning pipeline and a deep residual network framework COVID19XrayNet for the COVID-19 detection problem based on chest X-ray images. COVID19XrayNet firstly tunes the transferred model on a large dataset of chest X-ray images, which is further tuned using a small dataset of annotated chest X-ray images. The final model achieved 0.9108 accuracy. The experimental data also suggested that the model may be improved with more training samples being released. COVID19XrayNet, a two-step transfer learning framework designed for biomedical images.

Coronavirus disease (COVID-19) and neonate: What neonatologist need to know.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause china epidemics with high morbidity and mortality, the infection has been transmitted to other countries. About three neonates and more than 230 children cases are reported. The disease condition of the main children was mild. There is currently no evidence that SARS-CoV-2 can be transmitted transplacentally from mother to the newborn. The treatment strategy for children with Coronavirus disease (COVID-19) is based on adult experience. Thus far, no deaths have been reported in the pediatric age group. This review describes the current understanding of COVID-19 infection in newborns and children.

A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version).

In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named "2019 novel coronavirus (2019-nCoV)" by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world's attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.