Use of platelet-rich plasma for COVID-19-related olfactory loss: a randomized controlled trial.

INTRODUCTION: The current study evaluated the use of platelet-rich plasma (PRP), an autologous blood product with supraphysiologic concentrations of growth factors, in the treatment of prolonged coronavirus disease 2019 (COVID-19)-related smell loss. METHODS: This multi-institutional, randomized controlled trial recruited patients with COVID-19 who had objectively measured smell loss (University of Pennsylvania Smell Identification Test [UPSIT] ≤ 33) between 6 and 12 months. Patients were randomized to three intranasal injections of either PRP or sterile saline into their olfactory clefts. The primary outcome measure was change in Sniffin' Sticks score (threshold, discrimination, and identification [TDI]) from baseline. The secondary end point measures included responder rate (achievement of a clinically significant improvement, ≥5.5 points TDI), change in individual TDI olfaction scores, and change in subjective olfaction via a visual analog scale. RESULTS: A total of 35 patients were recruited and 26 completed the study. PRP treatment resulted in a 3.67-point (95% CI: 0.05-7.29, p = 0.047) greater improvement in olfaction compared with the placebo group at 3 months and a higher response rate (57.1% vs 8.3%, odds ratio 12.5 [95% exact bootstrap confidence interval, 2.2-116.7]). There was a greater improvement in smell discrimination following PRP treatment compared with placebo but no difference in smell identification or threshold. There was no difference in subjective scores between PRP and placebo. No adverse effects were reported. CONCLUSION: Olfactory function following COVID-19 can improve spontaneously after 6 months and can improve to a greater extent with PRP injection. These data build on the promise of PRP to be a safe potential treatment option for patients with COVID-19-related smell loss, and larger-powered studies will help further assess its efficacy.

International Cooperation in Scientific Research during the COVID-19

The research uses the network collaborative construction theory to construct a national scientific cooperation network during the COVID-19 epidemic period, aiming to describe the evolution patterns of scientific research cooperation and the impact on the cooperation during the epidemic period. From the perspective of the cooperation network, the research calculates the network features to investigate the evolution patterns of the scientific research cooperation network. The present work also calculates the national cooperation freshness to investigate the dynamic evolution of the cooperation center. Finally, the regression discontinuity design is used to estimate the impact of the epidemic on national scientific research cooperation. The results show that the outbreak of the epidemic strengthens the scientific research cooperation. Furthermore, China played an important role in the epidemic, especially in the early stage. Although the cooperation center has gradually shifted with the change of the affected areas, China is still an important collaborator. Finally, our work studies the cooperative behavior of countries during the epidemic through regression discontinuity design and finds that the epidemic has been promoting people's ability to cooperate in fighting against disasters. © 2022, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved.

How can we implement targeted policies of rumor governance? An empirical study based on survey experiment of COVID-19

Since early 2020, COVID-19 has been a major public security crisis that has had an enormous impact on the world. With the spread of the epidemic, rumors occur, some of which have even caused public panic. They have greatly affected the government's efforts of epidemic prevention and thus urgently need to be evaluated. This study aimed to examine how to make flexible use of different policy tools to govern rumors based on their different characteristics. From the perspective of behavioral public policy, this study observes the effectiveness of various behavioral policy tools in rumor governance, hoping to explore the optimal solution of rumor governance from the perspective of micro public psychology. The survey experiment shows that individual behavior-related rumors (hereafter referred to as IBRs) are easier to be governed than epidemic progress-related rumors (hereafter referred to as EPRs) are, and that quick response is more effective than non-quick response. Through interaction analysis, it is known that in the governance of IBRs, nudge is more effective in rapid response, while in the context of non-quick response, boost outperforms nudge in rumor governance. A similar phenomenon can be seen in the scenario of EPR governance, despite a tinier difference in effectiveness compared with that of IBRs. The study enlightens us that rumor refutation requires not only people's disbelief in and restraint on rumors, but also the implementation of science-based targeted policies. Based on the conclusion, this study puts forward suggestions on implementing targeted policies of rumor governance.

The Russia-Ukraine conflict and foreign stocks on the US market

PurposeThe authors investigate how market quality diverges between foreign firms and domestic firms on the US stock market in response to the Russia-Ukraine conflict.Design/methodology/approachWith an event study approach, the authors compare foreign firms with domestic firms in their market responses over the three-day window around the outbreak of the war. Further, with Difference-in-Difference (DID) analyses, the authors study the change in foreign firms' market quality upon this outbreak in comparison with their domestic counterparts. Finally, the authors compare the foreign firms across firm specific characteristics and home country characteristics.FindingsThe authors find that foreign stocks listed in the US experience more severe market quality deterioration compared to the stocks' domestic counterparts. This effect is especially strong for companies from countries considered friendlier towards Russia and companies that are not cross-listed. The authors' findings are consistent with the information asymmetry hypothesis concerning market quality. Moreover, US market investors have more concerns over political risks with non-US-aligned political standings during war times.Research limitations/implicationsThe authors' findings are consistent with the information asymmetry hypothesis concerning market quality. Moreover, US market investors have more concerns over political risks over non-US-aligned political standings during war time.Practical implicationsSince both countries in the conflict are in Europe, the US stock market, to a certain degree, becomes a safe haven for capital from Europe and other countries. In the meantime, American Depository Receipts (ADRs) have been important for US investors to create a globally diversified portfolio, and the knowledge regarding ADRs' vulnerability to international geopolitical events is valuable. The author' results are informative for stock market investors to understand the market dynamics for international and domestic companies during this extremely uncertain time.Originality/valueThis is the first study that examines the market quality divergence between foreign firms and domestic firms on the US stock market in response to the Russia-Ukraine conflict. The authors provide novel evidence on the change in ADRs' market quality associated with significant political uncertainty. The authors show that ADRs' market quality is more vulnerable to international geopolitical risks relative to otherwise comparable domestic firms.

BinImg2Vec: Augmenting Malware Binary Image Classification with Data2Vec

Rapid digitalisation spurred by the Covid-19 pandemic has resulted in more cyber crime. Malware-as-a-service is now a booming business for cyber criminals. With the surge in malware activities, it is vital for cyber defenders to understand more about the malware samples they have at hand as such information can greatly influence their next course of actions during a breach. Recently, researchers have shown how malware family classification can be done by first converting malware binaries into grayscale images and then passing them through neural networks for classification. However, most work focus on studying the impact of different neural network architectures on classification performance. In the last year, researchers have shown that augmenting supervised learning with self-supervised learning can improve performance. Even more recently, Data2Vec was proposed as a modality agnostic self-supervised framework to train neural networks. In this paper, we present BinImg2Vec, a framework of training malware binary image classifiers that incorporates both self-supervised learning and supervised learning to produce a model that consistently outperforms one trained only via supervised learning. We also show how our framework produces outputs that facilitate explanability. © 2022 IEEE.

Use of comprehensive solicited event reporting for safety monitoring in clinical trials with standard of care drugs

Safety reporting in traditional clinical trials is often accomplished through investigator's independent identification of events meeting Adverse Event reporting criteria. In some study settings, such as observational or standard of care-based research, the subjectivity in this reporting approach can result in gaps or inconsistencies in safety data, limiting the ability to confidently confirm both presence and absence of key events. The Emmes contract research organization has adopted a new approach for clinical research studies to improve upon the traditional, passive, non-specific collection of adverse events with a more targeted solicitation of study-specific Events of Special Interest. Events of Special Interests may be derived from the drug labels, package inserts, or known disease indications, and ensure consistency and uniformity in safety data collection across sites and similar studies. Events of Special Interest reporting aims to target specific events and avoids over or under reporting by sites. Events of Special Interests also reduce the burden of site reporting of irrelevant events, the need to determine if an event is or is not reportable, such as in a sick patient population, and finally supports efficient data and safety monitoring in alignment with the Food and Drug Administration Investigational New Drug Application Safety reporting guidance. The Emmes contract research organization has adopted this approach to ensure comprehensive data collection in support of improved labeling for marketed products in pediatric and adolescent populations. It has proven most effective in observational or standard of care studies, particularly those with sick and/or inpatient populations. Safety event data are bolstered with site required confirmation of occurrence in an unequivocal No or Yes manner, along with the addition of severity, causality, and association assessments by the clinician/ subject matter expert. Events of Special Interests are study-defined events, aiding study staff or programmatic searches of health records in the identification and ion of event data. Events of Special Interests also allow researchers to more accurately tabulate event frequency and rates, as well as assist sponsors in identifying site reporting imbalances. Clinical research is constantly evolving, driven by the need to optimize data collection and reduce time, effort, and cost, which is particularly important for trials being implemented during the COVID-19 pandemic. The traditional methods used to collect safety data require a high level of effort to collect, review by numerous subject matter experts, and can often result in the collection of large amounts of data that are irrelevant to research objectives. This utilization of safety reporting and analysis to include Events of Special Interests has been shown to significantly reduce the level of effort to collect, subject matter expert review, MedDRA code, and tabulate safety data. By improving data collection consistency and uniformity, utilization of Events of Special Interest reporting has improved the overall process of safety event reporting in our clinical research, increasing the efficacy of study data utilized to inform regulatory authorities.

Study on pathological mechanism of pneumonia infected by coronavirus based on time-series gene co-expression network analysis

Recently, the epidemic of COVID-19 infection broke out in Wuhan, China. To explore the pathological mechanism of pneumonia infected by coronavirus, we built a bioinformatics pipeline based on time-series gene co-expression network analysis to analyze the gene expression profile of lung cells in mice infected by SARS-Cov (GSE19137). In this study, Pearson correlation analysis was performed to construct a gene co-expression network. Time-ordered gene network modules were digged out by BFS algorithm. PageRank algorithm was used to explore HUB genes related to pneumonia infected by coronavirus. Based on the information we got, we think that cell lines infected by coronavirus might go through 5 stages, and 10 HUB genes(AKT1, CD68, CTSS, FCGR3A, HSPA8, PTPRC, UBC, VCP, PRPF31, ITPKB) might play a key role in coronavirus infection. This might provide some hints for coronavirus related research. © 2021 IEEE.

Using an Android Robot to Improve Social Connectedness by Sharing Recent Experiences of Group Members in Human-Robot Conversations

Social connectedness is vital for developing group cohesion and strengthening belongingness. However, with the accelerating pace of modern life, people have fewer opportunities to participate in group-building activities. Furthermore, owing to the teleworking and quarantine requirements necessitated by the Covid-19 pandemic, the social connectedness of group members may become weak. To address this issue, in this study, we used an android robot to conduct daily conversations, and as an intermediary to increase intra-group connectedness. Specifically, we constructed an android robot system for collecting and sharing recent member-related experiences. The system has a chatbot function based on BERT and a memory function with a neural-network-based dialog action analysismodel. We conducted a 3-day human-robot conversation experiment to verify the effectiveness of the proposed system. The results of a questionnaire-based evaluation and empirical analysis demonstrate that the proposed system can increase the familiarity and closeness of group members. This suggests that the proposed method is useful for enhancing social connectedness. Moreover, it can improve the closeness of the user-robot relation, as well as the performance of robots in conducting conversations with people.

Online Flipped Classroom Based on Task-Driven Teaching Practice: Take Introduction to Systems Engineering as an example

Flipped classroom is an effective teaching method to improve teaching efficiency and quality. However, flipped classroom can easily lead to the defects of fragmentation of teaching process and polarization of learning effect, which hinders its effective application in online teaching. Task-driven teaching has the advantages of clear tasks and systematic knowledge, which can make up for the shortcomings of online teaching in flipped classroom. Aiming at the characteristics of online teaching under COVID-19 epidemic, this research carried out the design of task-driven online flipped classroom teaching model and explored practice. Based on the comprehensive use of multi-dimensional information platform, the situational design aroused and motivated the interest of students. The continuously upgrading tasks lead students to realize the conversion of knowledge mastery to ability formation. The effectiveness of online learning is comprehensively evaluated to realize the healthy operation of the teaching process and finally achieve the teaching goals. © 2020 IEEE.

Behavioral Implementation and Compliance of Anti-Epidemic Policy in the COVID-19 Crisis

Different countries have introduced different urgent policies to control the spread of the novel coronavirus. The compliance behavior of these anti-epidemic policies has always been an important concern to governments, and its effects need to be tested. In recent years, many scholars have paid attention to the mechanism and intervention of policy compliance behavior, which helps to explain the mechanism of anti-epidemic compliance behavior, and to improve the effectiveness of anti-epidemic policy. Therefore, considering the characters of youth groups in the context of the novel coronavirus, this study takes campus anti-epidemic compliance behavior as the research topic, based on 680 effective samples of college students in China, in order to examine the effectiveness of these policies using an investigation experiment. This study revealed that the 'Nudge' policy instrument was the most effective way to guide individuals' behavior during the coronavirus outbreak, the 'Sermon' instrument was the least recognized, and the 'Whip' instrument (a traditional and classical policy instrument) had its normal effect on individuals' behavior. Additionally, it found that high accessibility in policy implementation results in more significant policy behavior. By taking the effects of different policy behaviors into consideration, governments may produce better and more effective policy implementation and compliance during the anti-epidemic period.

Relation between Cardiac Injury and Elevated Levels of Inflammatory Biomarkers in Patients with Severe COVID-19

Background: Since early December 2019, coronavirus disease 2019 (COVID-19) has emerged as a global pandemic and public health crisis. This study aims to explore the relationship between cardiac injury and inflammatory biomarkers in patients with severe COVID-19. Methods: We collected data on 91 patients with a confirmed diagnosis of severe COVID-19 from February 8 to March 31, 2020. Demographic characteristics, clinical data, and in-hospital outcomes were compared. The relationship between cardiac injury and inflammatory biomarkers was analyzed. Logistic regression was used to explore the independent risk factors for cardiac injury. Results: The mean age of all patients was 61 years +/- 14 years. About half of the patients were male. Hypertension and coronary heart disease were more common in the cardiac injury group. The levels of inflammatory biomarkers in patients who experienced cardiac injury were generally higher than the levels of those without cardiac injury, including interleukin-6, interleukin-2 receptor (IL-2R), procalcitonin, and high-sensitivity C-reactive protein. There were positive correlations between the levels of high-sensitivity troponin I and N-terminal prohormone of brain natriuretic peptide and the levels of inflammatory biomarkers. Logistic regression shows that IL-2R (odds ratio 1.001, 95% confidence interval 1.000-1.002, P = 0.045) and comorbidities (odds ratio 4.909, 95% confidence interval 1.231-19.579, P = 0.024) are independent risk factors for cardiac injury in patients with severe COVID-19. Conclusion: High levels of inflammatory biomarkers are associated with higher risk of cardiac injury in patients with severe COVID-19. IL-2R and comorbidities are predictors of cardiac injury.

Wheel-Legged Robotic Limb to Assist Human with Load Carriage: An application for environmental disinfection during COVID-19

During COVID-19, with a heavy sprayer filled with disinfectant, the risk of infection for epidemic prevention personnel has been increased by long-term environmental disinfection. In order to reduce the burden and save energy of human, this paper proposed a Wheel-Legged Robotic Limb (WRL) for the carriers. The mass of WRL is only 1.77 kg. The WRL has one rigid robotic limb located below the sprayer, which can provide active supporting force for the sprayer. The WRL adopts force closed-loop control method to ensure the system provide an expected supporting force. The system performance was evaluated including standing and walking at 5 km/h, under three experimental conditions included: 1) with a sprayer, 19.41 kg (SPRAYER), 2) with the powered WRL, 22.18 kg (WRL_ON) and 3) with the unpowered WRL, 22.18 kg (WRL_OFF). When the supporting force is set as 80 N, the experimental results show that the WRL_ON condition has reduced the vertical load force on the human, the vertical ground reaction force of human feet, and the metabolic power by 41.28%, 8.03%, and 17.46%, respectively, during standing, and also reduced by 32.29%, 8.08% and 18.92%, respectively, during walking, compared to SPRAYER condition. IEEE