共检索78条数据Total:78
School of Physics and Physical Engineering, Qufu Normal University, Qufu 273165, China.; Key Laboratory of Green Natural Products and Pharmaceutical Intermediates in Colleges and Universities of Shandong Province, School of Chemistry and Chemical Engineering, Qufu Normal University, Qufu 273165, China.; Key Laboratory of Life-Organic Analysis of Shandong Province, School of Chemistry and Chemical Engineering, Qufu Normal University, Qufu 273165, China.; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China.
As a public health emergency of international concern, the highly contagious coronavirus disease 2019 (COVID-19) pandemic has been identified as a severe threat to the lives of billions of individuals. Lung cancer, a malignant tumor with the highest mortality rate, has brought significant challenges to both human health and economic development. Natural products may play a pivotal role in treating lung diseases. We reviewed published studies relating to natural products, used alone or in combination with US Food and Drug Administration-approved drugs, active against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and lung cancer from 1 January 2020 to 31 May 2021. A wide range of natural products can be considered promising anti-COVID-19 or anti-lung cancer agents have gained widespread attention, including natural products as monotherapy for the treatment of SARS-CoV-2 (ginkgolic acid, shiraiachrome A, resveratrol, and baicalein) or lung cancer (daurisoline, graveospene
2021-09-27
Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China.; Trauma Center, National Center for Trauma Medicine, Key Laboratory of Trauma and Neural Regeneration, Peking University People's Hospital, Beijing, China.; Trauma Center, National Center for Trauma Medicine, Key Laboratory of Trauma and Neural Regeneration, Peking University People's Hospital, Beijing, China.
The role of triglycerides (TG) in coronavirus disease (COVID-19) is controversial. The objective of this study was to explore the relationship between TG levels and prognosis in COVID-19 patients and investigate the factors that affect TG. COVID-19 patients were divided into normal or high TG level groups. Their demographic data, medical history, signs and symptoms, laboratory results, and final clinical results were analyzed retrospectively. A total of 174 patients were included. TG level was 1.6 (interquartile range [IQR]: 1.1-2.1) mmol/L for all patients; 2.2 (IQR: 1.8-2.7) mmol/L and 1.1 (IQR: 1.0-1.3) mmol/L in the high TG and control groups, respectively. Overall, 29 patients (16.7%) died during hospitalization, including 19 (23.1%) in the high TG group and 10 (11.5%) in the control group (absolute survival difference, 2.5% (95% confidence interval [CI], 1.2%-5.1%), log-rank χ (2) = 5.7, and p = .017). Serum ferritin, C-reactive protein (CRP), lactate dehydrogenase (LDH), and
2020-03-04
•The published data, which showed the COVID-19 patients with low digestive.•manifestation, might be misleading. Case with negative URT test showed positive in.•rectal scarab which challenge the isolation protocol.•As fomite transmission caused clusters of infection of SARS, adequate disinfection.•operations should be adopted in SARS-CoV-2 outbreak.
2020-03-04
•The published data, which showed the COVID-19 patients with low digestive.•manifestation, might be misleading. Case with negative URT test showed positive in.•rectal scarab which challenge the isolation protocol.•As fomite transmission caused clusters of infection of SARS, adequate disinfection.•operations should be adopted in SARS-CoV-2 outbreak.
2021-09-29
Department of Infectious Disease, St Mary's Campus, Imperial College London, London, UK. john.tregoning@imperial.ac.uk.; Department of Infectious Disease, St Mary's Campus, Imperial College London, London, UK.; Department of Infectious Disease, St Mary's Campus, Imperial College London, London, UK.; Department of Infectious Disease, St Mary's Campus, Imperial College London, London, UK.; Department of Infectious Disease, St Mary's Campus, Imperial College London, London, UK.
Where 2020 saw the development and testing of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at an unprecedented pace, the first half of 2021 has seen vaccine rollout in many countries. In this Progress article, we provide a snapshot of ongoing vaccine efficacy studies, as well as real-world data on vaccine effectiveness and the impact of virus variants of concern. Where they have been deployed in a high proportion of the adult population, the currently approved vaccines have been extremely effective in preventing COVID-19, particularly severe disease. Nonetheless, there are still significant challenges in ensuring equitable vaccine access around the globe and lessons that can be learned for controlling this pandemic and for the next pandemic.CI - © 2021. Springer Nature Limited.
2021-08-02
Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada.; Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada.; Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada.; Vanke School of Public Health, Tsinghua University, Beijing, China.; Vanke School of Public Health, Tsinghua University, Beijing, China.; Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada.; Institute for Global Health & Development, the Aga Khan University, Karachi, Pakistan.
BACKGROUND: There is uncertainty with respect to SARS-CoV-2 transmission in children (0-19 years) with controversy on effectiveness of school-closures in controlling the pandemic. It is of equal importance to evaluate the risk of transmission in children who are often asymptomatic or mildly symptomatic carriers that may incidentally transmit SARS-CoV-2 in different settings. We conducted this review to assess transmission and risks for SARS-CoV-2 in children (by age-groups or grades) in community and educational-settings compared to adults. METHODS: Data for the review were retrieved from PubMed, EMBASE, Cochrane Library, WHO COVID-19 Database, China National Knowledge Infrastructure (CNKI) Database, WanFang Database, Latin American and Caribbean Health Sciences Literature (LILACS), Google Scholar, and preprints from medRixv and bioRixv) covering a timeline from December 1, 2019 to April 1, 2021. Population-screening, contact-tracing and cohort studies reporting prevalence and
2021-02-10
School of Electronics Engineering and Computer Science, Peking University, Beijing, People's Republic of China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, People's Republic of China.; National Institute of Health Data Science, Peking University, Beijing, People's Republic of China.; Institute of Medical Technology, Health Science Center of Peking University, Beijing, People's Republic of China.; School of Electronics Engineering and Computer Science, Peking University, Beijing, People's Republic of China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, People's Republic of China.; School of Electronics Engineering and Computer Science, Peking University, Beijing, People's Republic of China. leehy@pku.edu.cn.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, People's Republic of China. leehy@pku.edu.cn.; Institute of Population Research, Peking University, No.5 Yiheyuan Road, Beijing, 100871, People's Republic of China. zhenjie.wang@pku.edu.cn.
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. METHODS: We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Our method can grasp the dynamic relations in irregularly sampled time series, which is ignored by existing works. Specifically, our method predicted the outcome of COVID-19 patients by considering both the biomarkers and the
2021-01-20
Department of Endocrinology, General Hospital of Central Theater Command, Wuluo Road 627, Wuhan 430070, Hubei Province, China; The First School of Clinical Medicine, Southern Medical University, NO.1023, Shatai Nan Road, Guangzhou, Guangdong Province, China.; Department of Endocrinology, General Hospital of Central Theater Command, Wuluo Road 627, Wuhan 430070, Hubei Province, China.; Department of Endocrinology, General Hospital of Central Theater Command, Wuluo Road 627, Wuhan 430070, Hubei Province, China.; Department of Endocrinology, General Hospital of Central Theater Command, Wuluo Road 627, Wuhan 430070, Hubei Province, China. Electronic address: zhangjx023@163.com.; Department of Endocrinology, General Hospital of Central Theater Command, Wuluo Road 627, Wuhan 430070, Hubei Province, China; The First School of Clinical Medicine, Southern Medical University, NO.1023, Shatai Nan Road, Guangzhou, Guangdong Province, China. Electronic address: Guangda64@hotmail.com.
BACKGROUND: Coronavirus disease 2019 (COVID-19) has been declared a global pandemic. COVID-19 is more severe in people with diabetes. The identification of risk factors for predicting disease severity in COVID-19 patients with type 2 diabetes mellitus (T2DM) is urgently needed. METHODS: Two hundred and thirty-six patients with COVID-19 were enrolled in our study. The patients were divided into 2 groups: COVID-19 patients with or without T2DM. The patients were further divided into four subgroups according to the severity of COVID-19 as follows: Subgroup A included moderate COVID-19 patients without diabetes, subgroup B included severe COVID-19 patients without diabetes, subgroup C included moderate COVID-19 patients with diabetes, and subgroup D included severe COVID-19 patients with diabetes. The clinical features and radiological assessments were collected and analyzed. We tracked the dynamic changes in laboratory parameters and clinical outcomes during the hospitalization period.
2021-11-29
Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China; Key Laboratory of Tree Breeding and Cultivation and Urban Forest Research Centre, National Forestry and Grassland Administration, Beijing, 10091, China. Electronic address: zhangchang_caf@caf.ac.cn.; Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China; Key Laboratory of Tree Breeding and Cultivation and Urban Forest Research Centre, National Forestry and Grassland Administration, Beijing, 10091, China. Electronic address: wch8361@163.com.; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital/Institute of Mental Health) and the Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China. Electronic address: chenchaojames@163.com.; Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China. Electronic address: tendytly@163.com.; Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China; Key Laboratory of Tree Breeding and Cultivation and Urban Forest Research Centre, National Forestry and Grassland Administration, Beijing, 10091, China. Electronic address: jiali_jin@126.com.; Department of Landscape Architecture, School of Architecture, Tsinghua University, Beijing, 100084, China. Electronic address: ziyanw93@163.com.; Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China; Key Laboratory of Tree Breeding and Cultivation and Urban Forest Research Centre, National Forestry and Grassland Administration, Beijing, 10091, China. Electronic address: jiabaoquan2006@163.com.
BACKGROUND: During the COVID-19 epidemic period, people showed a stronger connection to the environment within their communities. Although tree canopy in residential areas has been shown to positively affect psychological distress, it is not clear whether the COVID-19 epidemic played a role in this process. Elucidation of the relationship between tree canopy and the impact on psychological distress during the COVID-19 epidemic could provide valuable information as to the best methods to help individuals cope with urban mental stress events. METHODS: A total of 15 randomly selected residential areas of Beijing were enrolled in this repeated cross-sectional study. A total of 900 residents were included in the two-waves of the investigation (450 residents per wave) before and during the COVID-19 epidemic (i.e., May 2019 and May 2020). Psychological distress was estimated using the 12-question General Health Questionnaire (GHQ-12). Tree canopy coverage (TCC) was measured through visual
2021-11-23
Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.; Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China. Electronic address: gaoyh@nim.ac.cn.
The ongoing coronavirus disease 2019 (COVID-19) pandemic has become a public health emergency. Although many reverse-transcription PCR (RT-PCR) assays have been developed, their performance, especially sensitivity assessment, has been insufficiently tested. In this study, a preliminary comparison of the analytical sensitivity of nine RT-qPCR kits from different manufacturers was first conducted using a certified reference material derived from the genomic RNA of SARS-CoV-2 as the template. Subsequently, three of the nine kits, comprising two highly sensitive kits (DAAN, Huirui) and one less sensitive kit (Geneodx), were selected for further sensitivity and specificity validation. The results revealed variations in the performance between kits of the two groups. For the two highly sensitive kits, the limits of detection at 95 % probability (LOD95%) were 5.6 copies of the N gene and 3.5 copies of the ORF 1ab per reaction (DAAN), and 6.4 (N) and 4.6 (ORF 1ab) copies per reaction (Huirui