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1.
Journal of Craniofacial Surgery ; 33(6):2059-2062, 2022.
Article in English | MEDLINE | ID: covidwho-2063120

ABSTRACT

: Use of facial mask coverings has been a strong Centers for Disease Control and Prevention recommendation as an essential mitigation measure in the spread of the SARS-CoV-2 novel coronavirus (COVID)-19 virus. Face mask utilization has been shown to induce changes in the skin microclimate, especially around the perioral and perinasal regions. This results in increased mask adjustments and development of friction between masks and the underlying skin. The authors report novel findings of 2 individuals with skin cancer who underwent facial reconstruction during the COVID-19 pandemic. They encountered untoward sequelae of facial flap pressure necrosis due to the use of face mask coverings. These individuals were ultimately successfully treated with local wound care. One individual experienced auricular implant extrusion and flap loss. It is critical that reconstructive surgeons be aware of potential complications and the need for potential revision surgeries due to the use of face masks, and educate their patients to properly position the protective face masks based on the type of reconstruction performed. Plastic surgeons might also reconsider reconstructive management options in light of these additional obstacles.

2.
ACS Environmental Au ; 2(5):441-454, 2022.
Article in English | Scopus | ID: covidwho-2062151

ABSTRACT

NO2and O3simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO2assimilations. This study adopted two top-down NOXinversions and estimated their impacts on NO2and O3simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO2retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NOXemissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO2MREs: prior 85%, KNMI -27%, USTC -15%;O3MREs: Prior -39%, KNMI 18%, USTC 11%). The NOXbudgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO2levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O3is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO2: P2 vs P1, -46%, P3 vs P2, +25%;surface O3: P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O3flux differed by 5-6% between the two posteriori simulations, but the difference of NO2flux between P2 and P3 was significant, where the USTC posterior NO2flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO2and O3simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19. © 2022 American Chemical Society. All rights reserved.

3.
Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni ; 61(4):11-21, 2022.
Article in Chinese | Scopus | ID: covidwho-2056463

ABSTRACT

To explore the early stage spatial-temporal characteristics and to assess the factors of atmospheric pollution that may affect the development of coronavirus disease 2019(COVID-19)outbreak in the Chinese Mainland in 2020,we collected the daily new cases of COVID-19 in the Municipalities and Provinces from the websites of National and Provincial Health Commission of China. The spatiotemporal characteristics of COVID-19 epidemic were studied using autocorrelation analysis and trend analysis. The Spearman's correlation coefficient for ranked data and generalized additive model were used for risk assessment of air pollutants affecting the COVID-19 epidemic of Hubei Province. Daily new cases of COVID-19 in the Chinese Mainland totaled 39 877 from January 20th to February 9th of 2020. The global Moran index values of these three weeks were 0.249,0.307 and 0.297(P<0.01),respectively. There was a significant clustering phenomenon. The high incidence regions included Hunan Province,Guangdong Province,Jiangxi Province,Zhejiang Province,Anhui Province and Jiangsu Province. The epidemic hot spots were basically distributed in the area from 108° 47'-123° 10' E to 25° 31'-35° 20' N. Daily new cases of COVID-19 in Hubei Province was positively correlated with daily average concentrations of PM10,NO2 and O3 pollutants(ρ =0.515,0.579 and 0.536,P<0.05). The lag effects of air pollutions were existed. The relative risk(RR)values of PM2.5and PM10 reached to maximum with lag0,the RR value of NO2 reached to maximum with lag4,and the RR value of O3 reached to maximum with lag 0~1. We estimated that a 10 μg/m3 increase in day-before NO2 daily average concentration was associated with a 32.745% (95% Confidence Interval(CI):11.586%-57.916%)excess risk(ER)of daily new cases of COVID-19. And NO2 had a significant impact on daily new cases of COVID-19. When NO2 was introduced to PM2.5and PM10 separately,for every 10 μg/m3 rise in NO2 daily average concentration,the ER of daily new cases of COVID-19 was 23.929%(95% CI:4.705%-46.682%)and 24.672%(95% CI:5.379%-47.496%),respectively. The study showed that the southeast was the main spread direction in the early stage of COVID-19 outbreak in the Chinese Mainland in 2020. Reducing the atmospheric concentration of nitrogen dioxide in epidemic hot spots has a positive effect on epidemic prevention and control. © 2022 Journal of Zhongshan University. All rights reserved.

4.
Innovation in Aging ; 5:379-379, 2021.
Article in English | Web of Science | ID: covidwho-2012280
6.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009514

ABSTRACT

Background: Despite the use of multiple lines of targeted therapy has revolutionized treatment for HER2-positive breast cancer, these methods still have limited efficacy for triple-positive breast cancer (TPBC), which calls for persistent exploration for optimized treatment strategy. This MUKDEN-01 prospective trial aimed to evaluate the efficacy of oral, chemo-sparing neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib, which also meet the need for treatment convenience under COVID-19 pandemic, for patients with TPBC. Methods: The MUKDEN 01 was an investigator-initiated, multicentre, single arm, prospective phase II trial, which was performed at twelve hospitals in China( NCT04486911). Treatment-naïve patients with stage II-III tumors that according to the AJCC 8th edition criteria were eligible. Patients were treated with each cycle of 4 weeks with oral administration of pyrotinib 320 mg, and letrozole 2.5mg once daily for 4 weeks, and dalpiciclib 125 mg once daily for three weeks, followed by one week off, for five cycles. The primary endpoint was pathological complete response (pCR) in the breast and axilla (ypT0/is ypN0). Secondary endpoints included pCR in the breast (ypT0/is). residual cancer burden (RCB) score, Ki67 index change at surgery compared with baseline, and safety. Safety was analyzed in all patients, who received treatment. The study is still ongoing, and the enrollment has been completed. Results: Between June 20, 2020 and Sep. 6, 2021, 68 patients were screened for eligibility and 61 patients were recruited into this first stage of study. After surgery, 18 (29.5%, 95% CI 18.5-42.6) out of 61 patients achieving tpCR(ypT0/is ypN0), 21 (34.4%, 95% CI 22.7-47.7) patients achieved bpCR(ypT0/is). The patients with excellent pathologic response (RCB 0-1) to the combined therapy accounted for 54.1% (33/61, 95% CI 40.9-66.9). Mean Ki67 expression was reduced from 38.7% (95%CI: 31.3-46.0) at baseline to 19.3% (95% CI:13.6- 25.0;p=0.0001) in the surgical samples. The most frequent grade 3 AE were neutropenia (35 [57%]), leukopenia (13 [21%]), diarrhea (9 [15%]) and oral mucositis (4 [7%]). There were five grade 4 neutropenia (8%) and one grade 4 increased AST (2%), but without other SAE and death throughout the study. Conclusions: Neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib yielded a pCR rate comparable to standard chemotherapy plus dual HER2 blockade in TPBC patients. The combined therapy was also well-tolerated and provided a chemo-sparing neoadjuvant approach for TPBC patients. To our knowledge, this is the first study to evaluate the therapeutic efficacy of a chemo-free neoadjuvant treatment with HER2 TKI pyrotinib and letrozole plus CDK4/6 inhibitor dalpiciclib for TPBC patients. Further validation in a large-scale randomized controlled trial is warranted.

8.
Advanced Therapeutics ; 5(8), 2022.
Article in English | EMBASE | ID: covidwho-2007088

ABSTRACT

Cancer gene therapy based on various gene delivery vectors has some potential but also has obvious disadvantages. In this study, a new M13 phage-based oncolytic virus is constructed that carried the RGD peptides to target tumor cells and the 3C gene of Seneca Valley virus (SVV) preceded by a eukaryotic initial transcriptional region (ITR) to transcribe an oncolytic protein to kill tumor cells. Recombinant virus particles of 1200 nm in length are obtained in large quantities by transfecting the recombinant M13 phage plasmid into the host BL2738 and are investigated in vitro in tumor cells and in vivo in tumor-bearing mice to evaluate their antitumor effect. The experiments using Hela cells confirm that the engineered M13 phage can target and enter Hela cells, and express the SVV 3C protein, resulting in apoptosis of target cells by upregulating the expression of caspase 3. Furthermore, the results of experiments in vivo also show that the recombinant phage significantly inhibits the enhanced tumor volume in nude mice compared to the control groups. The M13 phage may be engineered to fuse with a variety of oncolytic proteins to inhibit the growth of tumor cells in the future, providing a promising phage-based targeted oncolytic reagent.

9.
European heart journal ; 43(Suppl 1), 2022.
Article in English | EuropePMC | ID: covidwho-1998551

ABSTRACT

Funding Acknowledgements Type of funding sources: None. OnBehalf Cardioovascular Analytics Group Background Medical research is critical to professional advancement, and mentoring is an important means of early research engagement in medical training. In contrast to international research collaborations, research mentoring programs are often locally limited. With the COVID-19 pandemic causing drifts to virtual classes and conferences, virtual international medical research mentoring may be viable. We hereby describe our experience with a virtual, international mentorship group for cardiovascular research. Methods Our virtual international research mentorship group has been running since 2015. The group focuses on risk stratification and outcomes research in cardiovascular medicine and epidemiology. Mentees from any country or region in all stages of medical careers are welcomed. Considering the increasing emphasis of contemporary research on multidisciplinary healthcare and translational research, our team also includes allied healthcare professionals or students, and graduates from natural sciences (Figure 1). With our members’ diverse backgrounds, we firmly adhere to the principle that all members must be given equal opportunities and treatment, regardless of their age, gender, race, nationality, sexual orientation, family background, and institution of study or practice. We make use of virtual platforms and multi-level mentoring (both senior and peer mentoring), and emphasize active participation, early leadership, open culture, accessible research support, and a distributed research workflow (i.e. an accessible-distributed model). Results Since establishment, our group has expanded to include 63 active members from 14 countries (Figure 2), leading a total of 109 peer-reviewed original studies and reviews published. We observed no significant difficulty in communication between team members, nor conflicts due to differences in nationality or ethnicity. Most studies involve cross-country and ethnicity collaborations, and inter-disciplinary and inter-regional knowledge exchanges are frequent. Multi-level mentoring ensured mentoring quality without compromising bonding and communication. Conclusion An accessible-distributed model of virtual international medical research collaboration and multi-level mentoring is viable, efficient, and caters to the needs of contemporary healthcare. We hope that others will build similar models and improve medical research mentoring globally. Figure 1   Figure 2

10.
15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022 ; 13369 LNAI:457-468, 2022.
Article in English | Scopus | ID: covidwho-1971569

ABSTRACT

In recent decades, new epidemics have seriously endangered people’s lives and are now the leading cause of death in the world. The prevention of pandemic diseases has therefore become a top priority today. However, effective prevention remains a difficult challenge due to factors such as transmission mechanisms, lack of documentation of clinical outcomes, and population control. To this end, this paper proposes a susceptible-exposed-infected-quarantined (hospital or home)-recovered (SEIQHR) model based on human intervention strategies to simulate and predict recent outbreak transmission trends and peaks in Changchun, China. In this study, we introduce Levy operator and random mutation mechanism to reduce the possibility of the algorithm falling into a local optimum. The algorithm is then used to identify the parameters of the model optimally. The validity and adaptability of the proposed model are verified by fitting experiments to the number of infections in cities in China that had COVID-19 outbreaks in previous periods (Nanjing, Wuhan, and Xi’an), where the peaks and trends obtained from the experiments largely match the actual situation. Finally, the model is used to predict the direction of the disease in Changchun, China, for the coming period. The results indicated that the number of COVID-19 infections in Changchun would peak around April 3 and continue to decrease until the end of the outbreak. These predictions can help the government plan countermeasures to reduce the expansion of the epidemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

11.
15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022 ; 13369 LNAI:417-428, 2022.
Article in English | Scopus | ID: covidwho-1971568

ABSTRACT

The rapid spread of the Coronavirus (COVID-19) poses an unprecedented threat to the public health system and social economy, with approximately 500 million confirmed cases worldwide. Policymakers confront with high-stakes to make a decision on interventions to prevent the pandemic from further spreading, which is a dilemma between public health and a steady economy. However, the epidemic control problem has vast solution space and its internal dynamic is driven by population mobility, which makes it difficult for policymakers to find the optimal intervention strategy based on rules-of-thumb. In this paper, we propose a Deep Reinforcement Learning enabled Epidemic Control framework (DRL-EC) to make a decision on intervention to effectively alleviate the impacts of the epidemic outbreaks. Specifically, it is driven by reinforcement learning to learn the intervention policy autonomously for the policymaker, which can be adaptive to the various epidemic situation. Furthermore, District-Coupled Susceptible-Exposed-Infected-Recovered (DC-SEIR) model is hired to simulate the pandemic transmission between inter-district, which characterize the spatial and temporal nature of infectious disease transmission simultaneously. Extensive experimental results on a real-world dataset, the Omicron local outbreaks in China, demonstrate the superiority of the DRL-EC compared with the strategy based on rules-of-thumb. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

12.
2nd International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2021 ; : 570-574, 2021.
Article in English | Scopus | ID: covidwho-1948774

ABSTRACT

The sudden COVID-19 pandemic made us feel the limitations of offline sales. In order to let consumers fully realize the convenience of the Internet era and highlight the advantages of online sales, a personalized online florist system (OFS) is developed. The website takes JSP (JavaServer Pages) + SSM (Spring + SpringMVC + MyBatis) framework as the development technology and based on B/S (Browser/Server) structure, an online florist system based on JavaWeb is designed and implemented. © 2021 IEEE.

13.
8th International Conference on Human Aspects of IT for the Aged Population, ITAP 2022 Held as Part of the 24th HCI International Conference, HCII 2022 ; 13330 LNCS:521-540, 2022.
Article in English | Scopus | ID: covidwho-1930324

ABSTRACT

Mobile payment has become increasingly popular worldwide, especially during the COVID-19 pandemic. However, older adults have more difficulties in adapting to mobile payments than others. To understand the reasons behind this phenomenon, we explore cognitive lock-in and its antecedents in adopting WeChat Pay based on the status quo bias theory. We use the PLS-SEM technique with survey data from Chinese older adults over the age of 50. The results show that the cognitive lock-in of older adults is significantly affected by technology anxiety, habit, regret avoidance, and uncertainty costs. Moreover, older adults’ intention to adopt WeChat Pay is positively associated with social influence and self-actualization, while cognitive lock-in is a significant negative determinant. This study can help us better understand the underlying mechanism behind older adults’ adoption of mobile payment from a cognitive lock-in perspective. Furthermore, this study steers the discussion about improving older adults’ digital literacy and optimizing age-appropriate services for mobile payments. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

14.
INTERNATIONAL JOURNAL OF MENTAL HEALTH PROMOTION ; 24(4):603-618, 2022.
Article in English | Web of Science | ID: covidwho-1912681

ABSTRACT

The study aimed to investigate the influence of academic stressors on mental health and the mediating effect of social support and self-identity among college students and further studied the difference between the graduating students and non-graduating students during the COVID-19 Pandemic. Recruiting 900 college students as subjects, used the college students??? academic stressors questionnaire, social support questionnaire, self-identity scale and depression anxiety stress scales (DASS-21). The results showed that: (1) The college students??? academic stressor positively predicted mental health;(2) Social support and self-identity mediated the relationship;(3) The model also held when academic stressors was replaced by work stressor, but there were differences between the graduating and nongraduating students;(4) The direct effect work stressor on mental health in the graduating group was not significant;(5) The non-graduating students??? work stressor could not predict mental health through social support.

15.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research ; 25(7):S543-S543, 2022.
Article in English | EuropePMC | ID: covidwho-1904675
16.
12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022 ; 643 IFIP:80-86, 2022.
Article in English | Scopus | ID: covidwho-1898990

ABSTRACT

The devastating, ongoing Covid-19 epidemic has led to many students resorting to online education. In order to better guarantee the quality, online education faces severe challenges. There is an important part of online education referred to as Knowledge Tracing (KT). The objective of KT is to estimate students’ learning performance using a series of questions. It has garnered widespread attention ever since it was proposed. Recently, an increasing number of research efforts have concentrated on deep learning (DL)-based KT attributing to the huge success over traditional Bayesian-based KT methods. Most existing DL-based KT methods utilize Recurrent Neural Network and its variants, i.e. Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) etc. Recurrent neural networks are good at modeling local features, but underperforms at long sequence modeling, so the attention mechanism is introduced to make up for this shortcoming. In this paper, we introduce a DL-based KT model referred to as Convolutional Attention Knowledge Tracing (CAKT) utilizing attention mechanism to augment Convolutional Neural Network (CNN) in order to enhance the ability of modeling longer range dependencies. © 2022, IFIP International Federation for Information Processing.

17.
Applied Economics Letters ; : 7, 2022.
Article in English | English Web of Science | ID: covidwho-1882910

ABSTRACT

Bitcoin market had a significant momentum phenomenon before the launch of Futures, and then it turned into an insignificant reversal effect. After Covid-19 appeared, the momentum effect and reversal effect disappeared. The advent of bitcoin futures has increased how investors respond to information. With the outbreak of COVID-19, investor interest in Bitcoin as a safe-haven asset has increased the effectiveness of the price. We estimate the speed of signal diffusion in the bitcoin market, and the results support that effective response to information is the essential mechanism for the disappearance of momentum effect.

18.
60th IEEE Conference on Decision and Control (CDC) ; : 2824-2829, 2021.
Article in English | Web of Science | ID: covidwho-1868529

ABSTRACT

This paper studies the distributed link removal problem for controlling epidemic spreading in a networked meta-population system. A deterministic networked susceptible-infected-recovered (SIR) model is considered to describe the epidemic evolving process. To curb the spread of epidemics, we reformulate the original topology design problem into a minimization program of the Perron-Frobenius eigenvalue of the matrix involving the network topology and transition rates. A modified distributed link removal strategy is developed such that it can be applied to the SIR model with heterogeneous transition rates on weighted digraphs. The proposed approach is implemented to control the COVID-19 pandemic by using the infected and recovered data reported by the German federal states. The numerical experiment shows that the infected percentage can be significantly reduced by employing the distributed link removal strategy.

19.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(4): 474-478, 2022 Apr 06.
Article in Chinese | MEDLINE | ID: covidwho-1834947

ABSTRACT

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.


Subject(s)
COVID-19 , Contact Tracing , Cohort Studies , Humans , Incidence , Prospective Studies
20.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-334681

ABSTRACT

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimate viral reproduction and clearance rates, and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to superspreading. Viral genome load often peaked days earlier in saliva than in nasal swabs, indicating strong compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of B.1.1.7 and non-B.1.1.7 viruses in nasal swabs were indistinguishable, however B.1.1.7 exhibited a significantly slower pre-peak growth rate in saliva. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.

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