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The COVID-19 outbreak may have some impact on the use of biologics in psoriatic patients because immunosuppressive effects of biologics may potentially alter the susceptibility of patients to the virus, deteriorate the condition of infected patients or even change the prognosis of infection. According to currently available recommendations from international psoriasis academic organizations and specialists, as well as specific situation in China, the authors provide some guidance on the use of biologics for psoriatic patients undergoing or planning to undergo treatment with biologics, those with low or high risk of infection, and for those with or without COVID-19 infection, so as to provide references for clinical practice.Copyright © 2020 by the Chinese Medical Association.
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Ethnopharmacological relevance: Scutellaria baicalensis Georgi. contains varieties of function compounds, and it has been used as traditional drug for centuries. Baicalein is the highest amount of flavonoid found in Scutellaria baicalensis Georgi., which exerts various pharmacological activities and might be a promising drug to treat COVID-19. Aim of the study: The present work aims to investigate the metabolism of baicalein in humans after oral administration, and study the pharmacokinetics of BA and its seven metabolites in plasma and urine. Materials and methods: The metabolism profiling and the identification of baicalein metabolites were performed on HPLC-Q-TOF. Then a column-switching method named MPX™-2 system was applied for the high-throughput quantificationof BA and seven metabolites. Results: Seven metabolites were identified using HPLC-Q-TOF, including sulfate, glucuronide, glucoside, and methyl-conjugated metabolites. Pharmacokinetic study found that BA was extensively metabolized in vivo, and only 5.65% of the drug remained intact in the circulatory system after single dosing. Baicalein-7-O-sulfate and baicalein-6-O-glucuronide-7-O-glucuronide were the most abundant metabolites. About 7.2% of the drug was excreted through urine and mostly was metabolites. Conclusion: Seven conjugated metabolites were identified in our assay. A high-throughput HPLC-MS/MS method using column switch was established for quantifying BA and its metabolites. The method has good sensitivity and reproducibility, and successfully applied for the clinical pharmacokinetic study of baicalein and identified metabolites. We expect that our results will provide a metabolic and pharmacokinetic foundation for the potential application of baicalein in medicine. © 2022
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Corona Virus Disease 2019(COVID-19)constitutes a pandemic worldwide, the novel coronavirus(SARS-CoV-2)is still the focus of prevention and control before the full spread of vaccines.Prevention is the key to controlling the epidemic. The Health Management Administration of the various provinces and cities have released the "Traditional Chinese Medicine Diagnosis and Treatment Programs for New Coronavirus Pneumonia" in response to the epidemic situation, among them including a lot of preventive prescriptions of TCM, which emphasizes to adhere to the advanced disease prevention concept of TCM preventing treatment of disease, and based on the principle of "strengthening vital energy and expelling pathogenic factors", through the methods of taking traditional Chinese medicine, medicated diet, medicated tea, acupuncture and guidance, and actively mobilizes the vital qi of human body and strengthen the physique, so as to achieve the epidemic prevention purpose of "the vital qi is stored in the body, the pathogenic factors cannot". The article reviews the prevention programs of TCM issued by various regions, analyzes and summarizes the rules of preventive medicine of TCM, in order to provide reference for the general public and the front-line clinical prevention of COVID-19. Copyright © 2021, Central Station of Chinese Medicinal Materials Information, National Medical Products Administration. All right reserved.
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Low carbon investments are significant in climate change and sustainable economic growth. The research considers the impact of the COVID-19 pandemic on low carbon investments using environmental, social, and governance (ESG) factors in different regions to find the correlation between various markets and the impact of the pandemic. Our research employs the method of covariance/correlation analysis to investigate the relationship between low carbon investments in different regions. We also check the main parameters of descriptive statistics. We use the method of bivariate regression analysis to assess the impact of the COVID-19 pandemic on the performance of ESG stock indices in Emerging, European, and Global markets. The main findings reveal that the global prevalence and mortality risk of COVID-19 infection have a significant adverse effect on the performance of Emerging, European, and Global ESG stock markets. In contrast, the effect of COVID-19 cases reported deaths caused by COVID-19 infection to appear to be mixed. Our research shows that the correlation between the European ESG stock market and other ESG markets is exceptionally low or negative in the 1-year horizon. In contrast, tendencies in other markets are similar. So it means that the European ESG stock market is a good tool for diversification and risk mitigation during critical moments. Our results can be used in practice for portfolio management purposes. Institutional and other investors can use these results for low carbon portfolio management and risk mitigation. Copyright © 2022 Chen, Zhao, Teresienė, Keliuotytė-Staniulėnienė, Budrienė, Kanapickienė, Kartasova and Gu.
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Because predictions of transportation system reliability can provide useful information for intelligent transportation systems (ITS), evaluation of them might be viewed as a beneficial activity for reducing traffic congestion. This evaluation procedure could include some alternatives and criteria in a discrete decision space. To handle this evaluation process in an uncertain environment, a novel uncertain multi-criteria decision-making (MCDM) method is put forward in this paper. Considering the validity of uncertainty theory as a measure of epistemic uncertainty, we first introduce it into analytic hierarchy process (AHP) and provide the whole calculation procedure of the approach. The proposed approach is employed to evaluate regional travel time belief reliability in a case study. Additionally, a comparison is performed between the results of uncertain AHP and other MCDM methods to examine the efficiency of this method. These analyses show that uncertainty theory is particularly suited to be employed combination with the AHP method.
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Objective To realize the current situation and influencing factors of turnover intention among public health workers fighting against COVID-19 in Guangdong Province, explore the moderating effect of social support, and provide evidence for improving the stability of epidemic prevention team. Methods A self-constructed online questionnaire was used to investigate the personnel of Centres for Disease Control and Prevention and primary health care institutes in Guangdong Province. Hierarchical regression analysis was conducted to examine the associated factors of turnover intention and the moderating role of social support. Results A total of 2 168 participants were collected, of which 632(29.15%) had turnover intention. Anti-epidemic public health workers with senior title, working in CDC, having a fixed establishment, sleeping ≥ 6 h, showing more job satisfaction and reporting higher leadership/colleague/relative support had lower turnover intention, while those working overnight and working overtime on rest days were more likely to report turnover intention. The interaction term "job satisfaction × family support" had a negative moderating effect on the relationship between job satisfaction and turnover intention. Conclusions A relatively high turnover intention is reported among public health workers during the fight against COVID-19 in Guangdong Province. Improving the incentive mechanism, increasing job satisfaction and providing more support to primary health workers may reduce their turnover intention. © 2022, Publication Centre of Anhui Medical University. All rights reserved.
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Background: BAT1806/BIIB800 is a proposed biosimilar to reference tocili-zumab (TCZ). A Phase III randomised, double-blind, active-controlled clinical trial was conducted as part of a biosimilar development programme. Objectives: To evaluate the efficacy, pharmacokinetics (PK), safety and immu-nogenicity of BAT1806/BIIB800 in comparison with EU-sourced TCZ in subjects with moderate to severe rheumatoid arthritis with inadequate response to meth-otrexate (MTX). Methods: The study was conducted at 55 centres in China and Europe, between June 2018 and January 2021. Eligible subjects were randomised in a 2:1:1 ratio to one of three treatment groups: (1) BAT1806/BIIB800 up to Week 48, (2) TCZ up to Week 48, or (3) TCZ up to Week 24, followed by BAT1806/BIIB800 from Week 24 to Week 48, administered intravenously every 4 weeks at a dose of 8mg/kg. The primary endpoint was the proportion of subjects achieving an ACR20 response at timepoints pre-specifed to meet the requirements of different Regulatory Agencies: Week 12, for EMA;Week 24, for FDA and NMPA. Equivalence margins applied to differences in ACR20 response rates in the BAT1806/BIIB800 and TCZ treatment groups were pre-specifed as follows: +/-14.5% for EMA (95% confdence interval (CI));-12.0%,15% for FDA (90% CI);+/-13.6% for NMPA (95% CI). Secondary endpoints included pharmacokinetics, safety and immunogenicity. The ICH E9(R1) estimands framework including intercurrent events (related or unrelated to the COVID19 pandemic) was implemented for the ACR20 evaluation. A logistic regression model including 'region' (China and Eastern Europe) and 'previous biologic or targeted synthetic DMARD use' (Yes/No) as captured in Interactive Web Response System as stratifcation factors was utilised to assess equivalence for the primary endpoint. The difference in response rates was estimated and corresponding confdence intervals were derived to assess equivalence for the primary endpoint. This presents results up to Week 24. Results: In total, 621 subjects were randomised to receive BAT1806/BIIB800 (N=312), TCZ (N=155), or TCZ followed by BAT1806/BIIB800 (N=154). The groups were comparable in terms of baseline demographics and disease characteristics, including age, gender, disease activity and disease duration. The estimated proportions of subjects achieving an ACR20 response in the BAT1806/BIIB800 vs. the TCZ groups, respectively, were 68.97% vs. 64.82% at Week 12 and 69.89% vs. 67.94% at Week 24. The estimated difference between ACR response rates was 4.15% (95% CI-3.63, 11.93) at week 12, and 1.94% (90% CI-4.04, 7.92;95% CI-5.18, 9.07) at Week 24. The CIs for the estimated differences between the treatment groups were within the pre-defned equivalence margins (Figure 1). The treatment groups were comparable in terms of serum trough levels, incidence of TEAEs and ADA/NAb positivity (Table 1). Conclusion: BAT1806/BIIB800 has demonstrated equivalent efficacy at Week 12 and Week 24 and a similar PK, safety and immunogenicity profile as reference tocilizumab up to Week 24.
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COVID-19 pandemic has put a huge burden on public health and global economy. Vaccines play an important role in controlling virus transmission and reducing mortality. While monoclonal virus neutralizing antibodies can reduce the viral load, improve symptoms, and prevent the aggravation of the disease from hospitalization. Now hundreds of clinical trials of COVID-19 vaccine and monoclonal neutralizing antibody are in progress. The vaccine focuses on disease prevention, while the neutralizing antibody focuses on disease treatment. There are quite many differences between the two kinds of clinical trials by following different technical guidelines, research purpose, trial design, implementation and outcome assessment. Therefore, it is necessary to summarize the similarities and differences between the clinical trials for the reference of new drug research and development as well as clinical researchers.
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Students need to maintain certain living conditions in order to pursue online learning at home. However, there is a lack of a scientific explanation for the extent to which students’ performance in online at-home education is influenced by living conditions. Students from 2002 low-income households in China were surveyed, and a multivariate logistic regression analysis was conducted in order to explore the impact of living conditions on online education. The results showed that, rather than computers and smartphones, broadband Internet at home can affect students’ performance in online learning. The larger the residence area, the better the children’s performance in at-home e-learning. Moreover, children living in dilapidated houses are unable to satisfactorily perform in an e-learning environment. Contrarily, children who live in families with separate rooms and tap water show better performances. Additionally, the performance will be worse in the case of unattended students. Furthermore, children from low-income and-status families in the community are often at a disadvantage in an at-home e-learning environment. Cognition regarding the connection between living conditions and online education can be crucial for the improvement of the living conditions of low-income families in order to achieve online education equity. © 2022 by the author. Licensee MDPI, Basel, Switzerland.
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Background: Patients (pts) with cancer have increased morbidity and mortality associated with the development of SARS-Co-V2 infection. The mRNA vaccines BNT162b2 and mRNA-1273 have robust safety and efficacy with 95-97% prevention of severe COVID-19 disease and development of protective antibody titers in 92 - 100% of healthy individuals. By contrast, some pts with hematological malignancy fail to produce anti-spike antibodies (Ab) despite full courses of vaccination. This is particularly true for pts with non-Hodgkin lymphomas (NHL) and chronic lymphocytic leukemia (CLL) who are actively treated with or have received B cell-directed therapies (BCT). We recently demonstrated that NHL pts who received the COVID-19 vaccine within 9 months from BCT demonstrated markedly lower rates of seroconversion (11%) compared to healthy individuals (100%) or a cohort of older (age >65y) residents of a nursing home (91.5%). NHL pts who had received BCT more than 9 months before the vaccine responded more robustly (88%) (Ghione et al, Blood 2021). Here, we update the results of our earlier study and perform an analysis to identify factors that may help predict for adequate response to COVID-19 vaccines. We hypothesized that neutrophil (N) or lymphocyte (L) counts and/or N/L ratio (NLR) at baseline might predict for adequate Ab production in response to COVID-19 vaccines after receipt of BCT. Methods: This was an observational study performed at Roswell Park Comprehensive Cancer Center. Pts with NHL/CLL who had received COVID-19 mRNA vaccine were included, vaccine response was assessed as previously described (Ghione et al, Blood 2021). For NLR calculation, pts with CLL or NHL with blood involvement were excluded. Clinical variables were analyzed with the t test and Fisher's exact test;validity and cut-off for the L count was obtained with the ROC analysis using GraphPad9 and SPSS. Results: A total of 142 pts with various types of NHL and CLL receiving standard of care treatments were enrolled. Five pts with prior exposure to COVID-19 infection were excluded from the analysis, reaching a total n=137. Of 83 pts with NHL (n=57) and CLL(n=26) in our cohort who were vaccinated within 9 months of BCT, 14 (17%) seroconverted. Baseline N count (p= 0.5), sex (p= 0.2), age (p= 0.8), number of prior lines of treatment (p= 0.4), type of disease (p= 0.7), time from end of BCT to vaccine (p= 0.7) and type of vaccine (p= 0.08), did not affect the rate of seroconversion. For analysis of N and L counts, 37/137 pts with CLL/NHL involving peripheral blood were excluded. Among the remaining 100 pts, 76 had received/were receiving BCT and 24 were either on observation or were on a treatment not including BCT. Only 26/76 (34%) pts on treatment/previously treated with BCT mounted IgG Ab response, while 22/24 (91.6%) patients who were not on BCT mounted the IgG Ab response (p= 0.007). In these NHL pts (N=100), higher L counts and higher NLR were associated with an increased IgG response to the vaccine (p= 0.019). For pts on BCT (N=76) a higher L count (cut-off of 1455 lymphocytes per cubic millimeter of blood [µL] as noted in the ROC) was associated with a higher rate of COVID-19 vaccine response (p= 0.020, with a sensitivity of 84% and specificity 71.5%). Conclusion: In this study, we confirm that pts with NHL/CLL receiving COVID-19 vaccination while on active treatment or within 9 months of treatment with BCT respond poorly to COVID-19 mRNA vaccination (17% seroconversion). Although a higher lymphocyte count and NLR ratio were associated with improved seroconversion rates, these were not powerful predictors. Further study of specific lymphocyte sub-populations that contribute to effective vaccine induced immunity in the context of BCT is ongoing. These studies will help to define optimal strategies for immunization in patients receiving BCT. [Formula presented] Disclosures: Torka: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Griffiths: Takeda Oncology: Consultancy, Honoraria;Alexion Pharmaceuticals: Consultanc , Research Funding;Abbvie: Consultancy, Honoraria;Novartis: Honoraria;Taiho Oncology: Consultancy, Honoraria;Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding;Boston Biomedical: Consultancy;Astex Pharmaceuticals: Honoraria, Research Funding;Genentech: Research Funding;Apellis Pharmaceuticals: Research Funding.
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This article aims to investigate the recent evolution of China's development policy and practice. More precisely, how do China's policymakers and practitioners understand and debate China's role in international development, specifically in the context of the global Covid-19 pandemic? China's growing development activities overseas, particularly in the African continent, have spurred intense debate over its role as a rising power in international development. China is viewed in the West both as a threat and as a valuable potential partner in development cooperation. However, differences between Western and Chinese conceptions of development have complicated cooperation and understanding of China's development policy. Further understanding of these differences is needed, in order to evaluate their implications for low-income countries, and for potential trilateral cooperation.
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With the development of the novel coronavirus epidemic, virus detection and research has gradually become a hot research direction. The structure of the virus is mainly divided into protein shell and ribonucleic acid (RNA). RNA is an important information-carrying biopolymer within biological cells that plays a key role in regulatory processes and transcription control. Studies of RNA-induced conditions, including human immunodeficiency viruses, neocymavirus, and even Alzheimer's and Parkinson's disease, require an understanding of the structure and function of RNA. As a result, the study of RNA is becoming increasingly important in a range of applications, including biology and medicine. The function of RNA is determined primarily by the thermodynamic three-stage folding of a sequence of nucleotides. The hydrogen bond between nucleotides determines the main driving force for the formation of a three-stage structure. Smaller folds around the hydrogen bond are called secondary structures of RNA. The three-stage structure determines the function and nature of RNA, and traditional manual exploration of RNA tertiary structures, such as X-ray crystal diffraction, and MRI to determine RNA tertiary structures, while accurate and reliable, is labor-intensive and time-consuming. Accurate judgment of secondary structures has greatly influenced the study of RNA tertiary structures and deeper studies, and the exploration of RNA secondary structures with artificial intelligence can lead to more accurate, rapid and efficient results. In the current field, artificial intelligence algorithms to predict RNA secondary structures usually use deep learning, genetic algorithms and other means, through neural network fitting to obtain prediction results. This approach is supervised learning, requiring a large amount of RNA secondary structure data to be collated prior to the study, while the models trained are not explanatory. As we all know, RNA folding is driven primarily by thermodynamics, can we train a model that learns the principles of RNA folding on its own, based on limited structural data? The main research direction of this paper is to explore the secondary structure model of ribonucleic acid independently by using algorithms in the way of computer deep-strengthening learning. Deep-enhanced learning primarily transforms the prediction process of the RNA secondary structure into the process of intelligent decision-making to explore optimal decision-making. Due to the limited training set and computing power, this paper explores the feasibility and development potential of deep-enhanced learning algorithms in RNA secondary structure prediction. In the current field, artificial intelligence algorithms to predict RNA secondary structures usually use deep learning, genetic algorithms and other means, through neural network fitting to obtain prediction results. This approach is supervised learning, requiring a large amount of RNA secondary structure data to be collated prior to the study, while the models trained are not explanatory. As we all know, RNA folding is driven primarily by thermodynamics, can we train a model that learns the principles of RNA folding on its own, based on limited structural data? The main research direction of this paper is to explore the secondary structure model of ribonucleic acid independently by using algorithms in the way of computer deep-strengthening learning. Deep-enhanced learning primarily transforms the prediction process of the RNA secondary structure into the process of intelligent decision-making to explore optimal decision-making. Due to the limited training set and computing power, this paper explores the feasibility and development potential of deep-enhanced learning algorithms in RNA secondary structure prediction. The main research direction of this paper is to explore the secondary structure model of ribonucleic acid independently by using algorithms in the way of computer deep-strengthening learning. Deep-enhanced learning primarily transforms the prediction process of the RNA second ry structure into the process of intelligent decision-making to explore optimal decision-making. Due to the limited training set and computing power, this paper explores the feasibility and development potential of deep-enhanced learning algorithms in RNA secondary structure prediction. © 2021 IEEE.
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Purpose: Although the use of online technology has generated excitement over its potential to increase access to education, most existing research has focused on comparing online and in-person student performance. This study provides empirical evidence that semiprivate space at the family level affects students' access to online education. Design/methodology/approach: Students from 1,565 low-income households in China were surveyed, and a multivariate logistic regression analysis was conducted on the hypothesized factors that affect access to online education at home. Findings: The results show that the absence of computers, smartphones and broadband networks at home severely hinders children's access to online education, and even leads to their exclusion from it. Children with their fathers or paternal grandfathers as guardians have a lower probability of receiving online education at home. It was also found that the higher the education level of the head of the household, the more likely it is that children will receive online education at home. Originality/value: This study is one of the first to examine online accessibility at the family level. It also demonstrates that the semiprivate space at the family level may limit opportunities for students who would otherwise pursue online education at home. © 2021, Emerald Publishing Limited.
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Recently, there has been a pressing need to manage high-dimensional vector data in data science and AI applications. This trend is fueled by the proliferation of unstructured data and machine learning (ML), where ML models usually transform unstructured data into feature vectors for data analytics, e.g., product recommendation. Existing systems and algorithms for managing vector data have two limitations: (1) They incur serious performance issue when handling large-scale and dynamic vector data;and (2) They provide limited functionalities that cannot meet the requirements of versatile applications. This paper presents Milvus, a purpose-built data management system to efficiently manage large-scale vector data. Milvus supports easy-to-use application interfaces (including SDKs and RESTful APIs);optimizes for the heterogeneous computing platform with modern CPUs and GPUs;enables advanced query processing beyond simple vector similarity search;handles dynamic data for fast updates while ensuring efficient query processing;and distributes data across multiple nodes to achieve scalability and availability. We first describe the design and implementation of Milvus. Then we demonstrate the real-world use cases supported by Milvus. In particular, we build a series of 10 applications (e.g., image/video search, chemical structure analysis, COVID-19 dataset search, personalized recommendation, biological multi-factor authentication, intelligent question answering) on top of Milvus. Finally, we experimentally evaluate Milvus with a wide range of systems including two open source systems (Vearch and Microsoft SPTAG) and three commercial systems. Experiments show that Milvus is up to two orders of magnitude faster than the competitors while providing more functionalities. Now Milvus is deployed by hundreds of organizations worldwide and it is also recognized as an incubation-stage project of the LF AI & Data Foundation. Milvus is open-sourced at https://github.com/milvus-io/milvus. © 2021 Owner/Author.
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The coronavirus disease 2019 (COVID-19) outbreak affects the use of biologics for psoriatic patients, in the way that the consequential immunosuppression potentially alters a patient's susceptibility to the virus or deteriorate the condition if the patient is infected or even change the prognosis of infection. Therefore, authors reviewed currently available recommendations from international psoriasis academic organizations and specialists, and summarized them with the specific situation in China. We are trying to provide guidance to the use of biologics for psoriatic patients in the following contexts: patients on biologic therapy, patients being considered for biologic therapy initiation, patients with low-risk or high-risk of SARS-CoV-2 coronavirus infection, patients tested negative or positive for the nucleic acid testing of virus. © 2021 Lippincott Williams and Wilkins. All rights reserved.
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Among the staff of Beijing Chao-Yang Hospital, Capital Medical University, who received the inactivated SARS-CoV-2 vaccine on January 30 in 2021, 28 recipients were selected for this research. Samples for nucleic acid tests were collected from the surface of the recipients' both hands before and after vaccination. The hemostatic stickers used after the inoculation were also collected for nucleic acid tests. The nucleic acid tests of the samples collected from the surface of both hands of the 28 recipients before vaccination were all negative. After vaccination, the nucleic acid tests of the samples collected from the surface of both hands of recipients were positive in 3 cases, and suspicious in 8 cases, with a positive rate of 10.7%. A total of 25 hemostatic stickers used were collected, 24 of them had positive nucleic acid tests, and the rest one had suspicious nucleic acid test result, with a positive rate of 96%. The hemostatic stickers used after the inoculation have the risk of nucleic acid contamination.