The Effect of FOXP3+Regulatory T Cells on Infectious and Inflammatory Diseases

CD4+CD25+FOXP3+regulatory T cells (Tregs) contribute to the maintenance of immune homeostasis and tolerance in the body. The expression levels and functional stability of FOXP3 control the function and plasticity of Tregs. Tregs critically impact infectious diseases, especially by regulating the threshold of immune responses to pathogenic microorganisms. The functional regulatory mechanism and cell-specific surface markers of Tregs in different tissues and inflammatory microenvironments have been investigated in depth, which can provide novel ideas and strategies for immunotherapies targeting infectious diseases.Copyright © 2021. All rights reserved.

Analysing responses of Year-12 students to a hands-on IT workshop: Implications for increasing participation in tertiary IT education in regional Australia

Two hand-on workshops on social media apps were conducted for the Year-12 students from two schools, one from a regional city and the other from a remote community, in a computer laboratory on the Rockhampton campus at Central Queensland University before the COVID-19 pandemic. The school in the regional city offered a specialist Digital Technologies Curriculum (DTC) to students in Years 11 & 12 whereas the remote school did not offer a similar DTC to students in Years 11 & 12. Statistical analyses of the students‟ responses to two casual questions during the workshop indicated that firstly the hands-on activities improved all students‟ general IT knowledge, and secondly the Year-12 students from the regional city were more determined to undertake tertiary IT education than the students from the remote school. Therefore, it is recommended that a mandatory specialist DTC for students in Years 11 &12 in ALL schools should be included in the national curriculum in the future. Implications of these findings on improving the participation rate of post-secondary education in Australian regional communities are also discussed in this article. In particular, regional universities can play a unique role in producing "IT allrounders” to meet the needs of the regional communities through collaborations with governments, secondary schools, regional industries and businesses. © 2023 The Author(s).

Scalable one-stage multi-view subspace clustering with dictionary learning

The clustering of large numbers of heterogeneous features is a hot topic in multi-view communities. Most existing multi-view clustering (MvC) methods employ matrix factorization or anchor strategies to handle large-scale datasets. The former operates on the original data and is, therefore, sensitive to noise and feature redundancy, which is reflected in the final clustering performance. The latter requires post -processing steps to generate the clustering results, which may be suboptimal owing to the isolation steps. To address the above problems, we propose one-stage multi-view subspace clustering with dictionary learning (OSMvSC). Specifically, we integrate dictionary learning, representation coefficient matrix learning, and matrix factorization as a unified learning framework, which directly learns the dictionary and representation coefficient matrix to encode the original multi-view data, and obtains the clustering results with linear time complexity without any postprocessing step. By manipulating the class centroid with the nuclear norm, a more compact and discriminative class centroid representation can be obtained to further improve clustering performance. An effective optimization algorithm with guaranteed convergence is designed to solve the proposed method. Substantial experiments on various real-world multi-view datasets demonstrate the effectiveness and superiority of the proposed method. The source code is available at https://github.com/justcallmewilliam/OSMvSC.(c) 2022 Elsevier B.V. All rights reserved.

Data Driven Modeling Social Media Influence using Differential Equations

Individuals modify their opinions towards a topic based on their social interactions. Opinion evolution models conceptualize the change of opinion as a uni-dimensional continuum, and the effect of influence is built by the group size, the network structures, or the relations among opinions within the group. However, how to model the personal opinion evolution process under the effect of the online social influence as a function remains unclear. Here, we show that the uni-dimensional continuous user opinions can be represented by compressed high-dimensional word embeddings, and its evolution can be accurately modelled by an ordinary differential equation (ODE) that reflects the social network influencer interactions. We perform our analysis on 87 active users with corresponding influencers on the COVID-19 topic from 2020 to 2022. The regression results demonstrate that 99% of the variation in the quantified opinions can be explained by the way we model the connected opinions from their influencers. Our research on the COVID-19 topic and for the account analysed shows that social media users primarily shift their opinion based on influencers they follow (e.g., model explains for 99% variation) and self-evolution of opinion over a long time scale is limited. © 2022 IEEE.

Internet Governance: Social Mentality and Public Emotion Analysis on Online Media during the COVID-19 Epidemic in Mainland China

Based on a systematical discussion of the logical relationship between social mentality as a psychological basis of social actions and institutions and social governance, and the online emotion as the core element of the dynamic tendency of internet-based social mentality to form emotional energy to promote the operation of the internet society, this paper conducts an empirical study on the online social mentality and public sentiment guidance during the COVID-19 epidemic in mainland China. We use more than 1 million Weibo dynamic data of 104 accounts of three different types including official media, self-media, and big V media and conduct emotional calculation and judgment to address our objectives. The results show that the public sentiment presented by Weibo as the carrier is mainly positive, among which the official media play a positive role in guiding emotions, while the role played by big Vs' is limited during the COVID-19 epidemic. There exists different public sentiment stemmed from the regional differences brought by the heterogeneity of social governance, economic and social development beyond the media guidance. The study provides valuable internet governance experience on how the government can guide the public to respond to and deal with the crisis with a positive attitude when major public health emergencies occur in the future. © 2022 IEEE.

Perioperative management strategies for surgical patients during the COVID-19 outbreak.

At present, the prevention and control situation of epidemics of Corona Virus Disease 2019 (COVID-19) is still serious, medical institutions should provide quality and safe routine medical services while doing their best in the prevention and control of this disease. The purpose of this article is to suggest a way to give quality and safe medical services to patients who need surgical treatment, especially to those who need emergency surgical treatment, with strict classified managements and standard precaution during perioperative period. With those suggestions, we may reduce the incidence of nosocomial infection and contribute to the prevention and control of COVID-19.Copyright © 2020 by the Chinese Medical Association.

Application of glucocorticoids in treatment of COVID-19.

The infection of 2019-nCoV can lead to overexpression of inflammatory factors, triggering cytokine storm and causing serious damage to the body. Glucocorticoids have anti-inflammatory properties and may be an effective treatment option. The use and dosage of glucocorticoids in coronavirus disease 2019 (COVID-19) remains controversial. This article reviews the theoretical basis, clinical evidence, debates and specific measures of glucocorticoids in the treatment of COVID-19, to provide reference for rational application of glucocorticoids in the future.Copyright © 2021 Chinese Medical Association

Application of glucocorticoids in treatment of COVID-19.

The infection of 2019-nCoV can lead to overexpression of inflammatory factors, triggering cytokine storm and causing serious damage to the body. Glucocorticoids have anti-inflammatory properties and may be an effective treatment option. The use and dosage of glucocorticoids in coronavirus disease 2019 (COVID-19) remains controversial. This article reviews the theoretical basis, clinical evidence, debates and specific measures of glucocorticoids in the treatment of COVID-19, to provide reference for rational application of glucocorticoids in the future.Copyright © 2021 Chinese Medical Association

COVID-19 and systemic anti-cancer therapy.

The corona virus disease 2019 (COVID-19) pandemic continues to severely impact healthcare systems around the world, and patients with cancer are even worse affected owing to compromised immune status and greater exposure risk. In the present review, we retrieved the relevant literature including guidelines and consensuses directly related to the purpose of this study from the PubMed database, and then summarized the research data on cancer and COVID-19, aiming to discuss the personal protection, systemic anti-cancer therapy, outcome of co-infection, and the clinical management strategy in this population. We found that patients with malignant tumors had a higher chance of suffering COVID-19, co-infection of whom had an even worse clinical prognosis, especially for those with lung cancer or hematologic cancers. Systemic chemotherapy may delay the clearance of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) virus of human body, and thus have a negative impact on the clinical outcomes of COVID-19, while certain endocrine therapy and targeted drugs having limited or no impact. There has been no sufficient evidence for the impact of immune checkpoint therapy on the outcomes of COVID-19 till now. It is of great value to strengthen the personal protection of patients, adjust the anti-tumor treatments rationally and optimize the clinical management processes.Copyright © 2022, Editorial Office of China Oncology. All rights reserved.

Identification and high-throughput quantification of baicalein and its metabolites in plasma and urine

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

Vaccination with Span, an antigen guided by SARS-CoV-2 S protein evolution, protects against challenge with viral variants in mice

SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan, China: A Retrospective, Observational Study

Background:Coronavirus disease 2019 (COVID-19) is a serious and even lethal respiratory illness. The mortality of critically ill patients with COVID-19, especially short term mortality, is considerable. It is crucial and urgent to develop risk models that can predict the mortality risks of patients with COVID-19 at an early stage, which is helpful to guide clinicians in making appropriate decisions and optimizing the allocation of hospital resoureces.Methods:In this retrospective observational study, we enrolled 949 adult patients with laboratory-confirmed COVID-19 admitted to Tongji Hospital in Wuhan between January 28 and February 12, 2020. Demographic, clinical and laboratory data were collected and analyzed. A multivariable Cox proportional hazard regression analysis was performed to calculate hazard ratios and 95% confidence interval for assessing the risk factors for 30-day mortality.Results:The 30-day mortality was 11.8% (112 of 949 patients). Forty-nine point nine percent (474) patients had one or more comorbidities, with hypertension being the most common (359 [37.8%] patients), followed by diabetes (169 [17.8%] patients) and coronary heart disease (89 [9.4%] patients). Age above 50 years, respiratory rate above 30 beats per minute, white blood cell count of more than10 × 109/L, neutrophil count of more than 7 × 109/L, lymphocyte count of less than 0.8 × 109/L, platelet count of less than 100 × 109/L, lactate dehydrogenase of more than 400 U/L and high-sensitivity C-reactive protein of more than 50 mg/L were independent risk factors associated with 30-day mortality in patients with COVID-19. A predictive CAPRL score was proposed integrating independent risk factors. The 30-day mortality were 0% (0 of 156), 1.8% (8 of 434), 12.9% (26 of 201), 43.0% (55 of 128), and 76.7% (23 of 30) for patients with 0, 1, 2, 3, ≥4 points, respectively.Conclusions:We designed an easy-to-use clinically predictive tool for assessing 30-day mortality risk of COVID-19. It can accurately stratify hospitalized patients with COVID-19 into relevant risk categories and could provide guidance to make further clinical decisions. © 2021 The Chinese Medical Association, Published by Wolters Kluwer Health, Inc.

A Bibliometric Analysis of the Literature on Postgraduate Teaching

The sustainable development of human society and economy needs the support of senior talents. Postgraduate teaching is one of the crucial components of higher education, and the priority method to cultivate senior talents. The 7th United Nations STI Forum in 2022 will focus on open science and postgraduate teaching;the theme of the forum is "While comprehensively implementing the 2030 Agenda for Sustainable Development, strengthen science, technology, and innovation, and promote the world's recovery from the COVID-19 pandemic". Therefore, the analysis of the field of postgraduate teaching is of great theoretical and practical significance to the cultivation of postgraduate students, the research of researchers, and the management of postgraduate teaching by the education sector. This research has carried out a bibliometric analysis to better obtain the knowledge structure in the field of postgraduate teaching and research, and help other researchers obtain the characteristics of the field of postgraduate teaching and research. VOSviewer and CiteSpace are used to analyze 4816 scientific core collection articles related to postgraduate teaching. These publications are from the Web of Science database. The dates of the articles range from 1995-2022. This research intuitively introduces a systematic overview of postgraduate teaching literature research, covering a number of publications, major categories, the most significant nations, groups, publications, writers, significant literature, and academic trends. The goal of this article is to create a map of the postgraduate teaching knowledge structure, while also examining the research collaboration across organizations, authors, nations, and areas. For scholars and practitioners in the field of graduate education, objective advice and helpful ideas are given through the analysis and discussion of the data acquired.

Application progress of telemedicine in bipolar disorder patients under the COVID-19 pandemic

Bipolar disorder (BD) is a highly pathological disorder that is often misdiagnosed or undiagnosed. The main treatment is a combination of psychotherapy and medication. Traditional psychotherapy is affected by factors such as time, space, shortage of professional psychotherapists and patients' stigma, and has low availability. In terms of drug therapy, patients' medication compliance is poor, leading to repeated illness. The epidemic of coronavirus in 2019, closed management and telemedicine provide new ideas for the treatment of BD. Telemedicine can provide convenient medical services, promote disease rehabilitation, effectively guide patients' self-management, improve patients' treatment compliance, and prevent disease recurrence. This paper analyzes and summarizes the research related to telemedicine in BD, including the origin and significance, technical methods and application effects. To provide a reference for the application of telemedicine in patients with BD. © 2022 ACM.