The impact of dynamic adaptive teaching model on surgical education.

Objective To investigate the impact of dynamic adaptive teaching model on surgical education. Methods Due to the COVID-19 pandemic in 2020, we adopted dynamic adaptive teaching model in the Department of Breast Surgery, Peking Union Medical College Hospital, which divided the whole curriculum into several individual modules and recombined different modules to accommodate to student's levels and schedules. Meanwhile, adaptive strategy also increased the proportion of online teaching and fully utilized electronic medical resources. The present study included quantitative teaching score (QTS) recorded from January 2020 to June 2020, and used the corresponding data from 2019 as control. The main endpoint was to explore the impact of dynamic adaptive teaching model on overall QTS and its interaction effect with trainer's experience and student category. Results Totally, 20 trainers and 181 trainees were enrolled in the present study. With implementation of dynamic adaptive strategy, the overall QTS decreased dramatically (1.76+/-0.84 vs. 4.91+/-1.15, t=4.85, P=0.005). The impact was consistent irrespective of trainers' experience (high experience trainers: 0.85+/-0.40 vs. 2.12+/-0.44, t=4.98, P=0.004;medium experience trainers: 0.85+/-0.29 vs. 2.06+/-0.53, t=4.51, P=0.006;and low experience trainers: 0.10+/-0.16 vs. 0.44+/-0.22, t=2.62, P=0.047). For resident (including graduate) and undergraduate student teaching, both QTS was lower with dynamic strategy (residents: 0.18+/-0.34 vs. 0.97+/-0.14, t=4.35, P=0.007;undergraduate students 1.57+/-0.55 vs. 3.77+/-1.24, t=3.62, P=0.015), but dynamic strategy was effective for post-doc student subgroup and reached comparable QTS as traditional model (0.00+/-0.00 vs. 0.17+/-0.41, t=1.00, P=0.363). Conclusions Dynamic adaptive teaching strategy could be a useful alternative to traditional teaching model for post-doc students. It could be a novel effective solution for saving teaching resources and providing individualized surgical teaching modality.Copyright © 2023, Peking Union Medical College Hospital. All rights reserved.

[Rapid detection and genotyping of SARS-CoV-2 Omicron BA.4/5 variants using a RT-PCR and CRISPR-Cas12a-based assay].

OBJECTIVE: To establish a rapid detection and genotyping method for SARS-CoV-2 Omicron BA.4/5 variants using CRISPPR-Cas12a gene editing technology. METHODS: We combined reverse transcription-polymerase chain reaction (RT-PCR) and CRISPR gene editing technology and designed a specific CRISPPR RNA (crRNA) with suboptimal protospacer adjacent motifs (PAM) for rapid detection and genotyping of SARS- CoV-2 Omicron BA.4/5 variants. The performance of this RT- PCR/ CRISPPR-Cas12a assay was evaluated using 43 clinical samples of patients infected by wild-type SARS-CoV-2 and the Alpha, Beta, Delta, Omicron BA. 1 and BA. 4/5 variants and 20 SARS- CoV- 2-negative clinical samples infected with 11 respiratory pathogens. With Sanger sequencing method as the gold standard, the specificity, sensitivity, concordance (Kappa) and area under the ROC curve (AUC) of RT-PCR/CRISPPR-Cas12a assay were calculated. RESULTS: This assay was capable of rapid and specific detection of SARS- CoV-2 Omicron BA.4/5 variant within 30 min with the lowest detection limit of 10 copies/µL, and no cross-reaction was observed in SARS-CoV-2-negative clinical samples infected with 11 common respiratory pathogens. The two Omicron BA.4/5 specific crRNAs (crRNA-1 and crRNA-2) allowed the assay to accurately distinguish Omicron BA.4/5 from BA.1 sublineage and other major SARS-CoV-2 variants of concern. For detection of SARS-CoV-2 Omicron BA.4/5 variants, the sensitivity of the established assay using crRNA-1 and crRNA-2 was 97.83% and 100% with specificity of 100% and AUC of 0.998 and 1.000, respectively, and their concordance rate with Sanger sequencing method was 92.83% and 96.41%, respectively. CONCLUSION: By combining RT-PCR and CRISPPR-Cas12a gene editing technology, we successfully developed a new method for rapid detection and identification of SARS-CoV-2 Omicron BA.4/5 variants with a high sensitivity, specificity and reproducibility, which allows rapid detection and genotyping of SARS- CoV-2 variants and monitoring of the emerging variants and their dissemination.

Uncertainty management in electricity demand forecasting with machine learning and ensemble learning: Case studies of COVID-19 in the US metropolitans

Improving load forecasting is becoming increasingly crucial for power system management and operational research. Disruptive influences can seriously impact both the supply and demand sides of power. This work examines the impact of the coronavirus on power usage in two US states from January 2020 to December 2020. A wide range of machine learning (ML) algorithms and ensemble learning are employed to conduct the analysis. The findings showed a surprising increase in monthly power use changes in Florida and Texas during the COVID-19 pandemic, in contrast to New York, where usage decreased over the same period. In Texas, the quantity of power usage rises from 2% to 6% practically every month, except for September, when it decreased by around 1%. For Florida, except for May, which showed a fall of roughly 2.5%, the growth varied from 2.5% to 7.5%. This indicates the need for more extensive research into such systems and the applicability of adopting groups of algorithms in learning the trends of electric power demand during uncertain events. Such learning will be helpful in forecasting future power demand changes due to especially public health-related scenarios. © 2023 Elsevier Ltd

Guidance on the use of biologic agents in psoriatic patients during COVID-19 outbreak.

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.

The effect of Pickering emulsion adjuvants on the immune efficacy of the COVID-19 polypeptide vaccine

Pickering emulsions were prepared by phacoemulsification in an ice water bath with squalene as the oil phase and an aluminum adjuvant as the particle stabilizer. The effects of formulation and process conditions on the size and distribution of the Pickering emulsions were investigated. Pickering emulsions prepared under the optimal prescription and process conditions were mixed with a peptide antigen to obtain a peptide vaccine. The optimal prescription and process condition of the Pickering emulsion is as follows: squalene as the oil phase, ultra-pure water as the water phase with 5 mg/ml aluminum adjuvant, and an ultrasonication time of 4 min at 200 W power. BALB/c mice were immunized with the peptide vaccine, and the ability of the Pickering emulsion as an immunological adjuvant to improve the efficacy of the peptide vaccine was evaluated. Under optimal conditions, a Pickering emulsion with a small particle size (430.8 nm), uniform distribution (polydispersion index of 16.9%), and zeta potential of 31.5 mV, was obtained. Immunological results showed that the serum specific antibody level in the vaccinated group reached 1×104 after three immunizations. The proportion of CD4+T cells and CD4/CD8 cells was significantly higher (P < 0.05) in the vaccinated groups than the blank control group. Further, cytokine (TNF-α) secretion decreased in the aluminum adjuvant and Pickering emulsion groups but increased in the Freund's adjuvant group. All three vaccinated groups of mice exhibited low but detectable levels of IFN-γ secretion. © 2023

Porous carbon tubes from recycling waste COVID-19 masks for optimization of 8 mol% Y2O3-doped tetragonal zirconia polycrystalline nanopowder.

Disposable polypropylene medical masks are widely used to protect people from injury caused by COVID-19 worldwide. However, disposable medical masks are non-biodegradable materials, and the accumulation of waste masks can pollute the environment and waste resources without a reasonable recycling method. The aims of this study are to transform waste masks into carbon materials and to use them as a dispersant in preparing high-quality 8 mol% Y2O3-doped tetragonal zirconia nanopowders. The waste masks were carbonized to get a carbon source in the first step, then KOH was used to etch the carbon source creating a micropores structure in the carbon material after the carbon-bed heat treatment method. The resulting carbon material is a porous tube structure with a high specific surface area (1220.34 m2/g) and adsorption capacity. The as-obtained porous carbon tubes were applied as a dispersant to produce 8 mol% Y2O3-doped tetragonal zirconia nanopowders, and the resulting nanopowders owned well-dispersed and had the smallest particle size than that prepared by activated carbon as a dispersant. Besides, the sintered 8 mol% Y2O3-doped tetragonal zirconia ceramic possessed high density, which resulted in higher ionic conductivity. These findings suggest that waste face masks can be recycled to prepare high-added-value carbon materials and provide a green and low-cost method to reuse polypropylene waste materials.

The intelligent decision-making process construction of emergency intelligence based on the big data

Global public emergencies represented by COVID-19 have posed new requirements and challenges to the current governance systems and capacities of governments. Mining decision-level intelligence from massive, multi-source and heterogeneous big data is the basic environment of current emergency decision making. This paper is based on the case analysis of COVID-19 epidemic prevention and control and constructs the intelligent decision-making process framework of emergency intelligence from the basic support layer, information and data layer, fusion output layer, emergency decision-making layer and main user layer. A risk governance system of "government-led, enterprise participation, media coordination, social crowdsourcing"has been established with big data co-construction and sharing and joint epidemic prevention and control. Through intelligence collection, processing, analysis and output transmission of epidemic-related data and information in the big data environment, it provides services for the emergency prevention and control of major epidemics in both normal and abnormal situations. In the front-end control phase, the emergency intelligence perception of the source quality is ensured to support the emergency decision, and the wisdom level of emergency decision-making is improved by optimizing the use of terminal intelligence and failure prevention methods. This paper proposes to optimize the intelligent decision-making process of emergencies from the effective prevention strategy of intelligence perception failure and the effective intervention strategy of decision failure prevention. This article explores the big data in the application of global public emergency management and innovation, change and revelation, to expand the emergency decision-making from the perspective of intelligence applications, provides with wisdom for the government emergency decision. © 2022 ACM.

Turn calamities into blessings: the impact of resource reconfiguration and firm resilience on the company's recovery and growth in the COVID-19 times

Purpose: The purpose of this paper is to construct an integrated theoretical framework of firm resilience, and examine the relationship between resource reconfiguration, firm resilience, disruption impact, profit growth, innovation and environmental uncertainty in the context of COVID-19. Design/methodology/approach: A survey was distributed to 220 companies and a total of 207 respondents returned the survey. chief executive officer (CEO) and chief financial officer (CFO) of each company participants in the survey. The hypotheses are tested using structural equation modeling (SEM) technique. Findings: The results showed that firm resilience can be stimulated through the reconstruction of existing resources, and environmental uncertainty played a moderating role in this process;in turn, the improvement of firm resilience enabled companies to reduce the impact of disruptions, achieve profit growth and promote innovation. Practical implications: This study provides practical implications for how business management shapes firm resilience and promotes organization recovery and development. Originality/value: This study expands the literature of firm resilience by providing an integrated theoretical framework of firm resilience. Firstly, based on the perspective of dynamic capabilities, this study reveals that resource reconfiguration plays a key role in shaping firm resilience. Secondly, this study enriches the boundary research on firm resilience by incorporating environmental uncertainty into the research framework. Thirdly, this study validates the impact of firm resilience on disruption impact, profit growth and innovation of companies, providing sufficient empirical evidence for the outcomes of firm resilience. © 2022, Emerald Publishing Limited.

Influence of Reporting Rate on Epidemic Control Based on SIXAR Model

How to balance the control efficiency of the epidemic and the economy is extremely important. This paper proposes a Susceptible-Infected-Isolated-Asymptomatic-Recovered (SIXAR, X represents isolated people) model, considering the asymptomatic and the isolated. We conduct an in-depth research on the reporting rate in the epidemic, and find the critical reporting rate to prevent the spread of the epidemic. The result proves that maintaining the reporting rate near a critical value can both ensure epidemic prevention and control and reduce economic consumption. It will provide a new idea for the government to formulate rational measures. © 2022 Technical Committee on Control Theory, Chinese Association of Automation.

Analysis of COVID-19 in Japan with extended SEIR model and ensemble Kalman filter.

We introduce an extended SEIR infectious disease model with data assimilation for the study of the spread of COVID-19. In this framework, undetected asymptomatic and pre-symptomatic cases are taken into account, and the impact of their uncertain proportion is fully investigated. The standard SEIR model does not consider these populations, while their role in the propagation of the disease is acknowledged. An ensemble Kalman filter is implemented to assimilate reliable observations of three compartments in the model. The system tracks the evolution of the effective reproduction number and estimates the unobservable subpopulations. The analysis is carried out for three main prefectures of Japan and for the entire country of Japan. For these four communities, our estimated effective reproduction numbers are more stable than the corresponding ones estimated by a different method (Toyokeizai). We also perform sensitivity tests for different values of some uncertain medical parameters, like the relative infectivity of symptomatic/asymptomatic cases. The regional analysis results suggest the decreasing efficiency of the states of emergency.

The Basic Reproduction Number and Delayed Action of T Cells for Patients Infected with SARS-CoV-2

COVID-19 has been prevalent for the last two years. The transmission capacity of SARS-CoV-2 differs under the influence of different epidemic prevention policies, making it difficult to measure the infectivity of the virus itself. In order to evaluate the infectivity of SARS-CoV-2 in patients with different diseases, we constructed a viral kinetic model by adding the effects of T cells and antibodies. To analyze and compare the delay time of T cell action in patients with different symptoms, we constructed a delay differential equation model. Through the first model, we found that the basic reproduction number of severe patients is greater than that of mild patients, and accordingly, we constructed classification criteria for severe and mild patients. Through the second model, we found that the delay time of T cell action in severe patients is much longer than that in mild patients, and accordingly, we present suggestions for the prevention, diagnosis, and treatment of different patients.

GeoHealth Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

GeoHealth research both characterizes and predicts problems at the nexus of earth and human systems like climate change, pollution, and natural hazards. While GeoHealth excels in the area of integrated science, there is a need to improve coordinated and networked efforts to produce open science to enable environmental justice. There is a need to resource and empower frontline populations that are disproportionately marginalized by environmental injustice (i.e., the unequal protection from environmental harms and lack of access and meaningful engagement in decision making for a healthy environment;EPA, 2022, https://www.epa.gov/environmentaljustice). GeoHealth practice has the opportunity to advance environmental justice or the “fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income” with respect to how research and collaboration of GeoHealth professionals supports the “development, implementation, and enforcement of environmental laws, regulations, and policies” that produce equal protection from environmental and health hazards and access to the decision making for a health environment (EPA, 2022, https://www.epa.gov/environmentaljustice). Here we highlight barriers and opportunities to apply an equity‐centered ICON framework to the field of GeoHealth to advance environmental justice and health equity.

Financial Risk Prediction Based on Stochastic Block and Cox Proportional Hazards Models

Since 2019, the sudden outbreak of COVID-19 has made huge impacts on various aspects of society, especially the financial industries that are closely related to the national economy and people’s livelihood. Finance is a data-intensive field and its traditional research models include supervised and unsupervised models, state-based models, econometric models, and stochastic models. However, the above models are prone to lose their effectiveness in the situation of an extremely complex financial ecosystem with a large number of nonlinear unpredictable effects, such as those caused by COVID-19. To address this issue, we comprehensively explore and fuse Stochastic Block Model (SBM) and Cox Proportional Hazards Model (COX) for a reliable and accurate financial risk prediction. Specifically, SBM, which is popular in social network analysis, is employed to capture the impact factors on the financial industry in public emergencies, and COX is then leveraged to determine the duration of the impact factors. An extensive experimental evaluation validates the effectiveness of our framework in predicting financial risk. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Saliva as a testing specimen with or without pooling for SARS-CoV-2 detection by multiplex RT-PCR test

Objectives Sensitive and high throughput molecular testing availability is essential during the COVID-19 pandemic. The vast majority of the SARS-CoV-2 molecular assays use nasopharyngeal or oropharyngeal swab specimens collected from suspected individuals. However, collecting these specimens has apparent drawbacks, including discomfort to patients and exposure risk to healthcare workers. Methods We developed and validated of QuantiVirus™ SARS-CoV-2 multiplex test using saliva as the testing specimens with pooling. Results The analytical sensitivity (LOD) was confirmed to be 100-200 copies/mL. For clinical evaluation, 85 known positive and 90 knowns negative NPS specimens were showed a positive predictive agreement of 100% and a negative predictive agreement of 98.9%. Twenty paired NPS and saliva samples were tested and showed overall 80% concordance rate without significant difference between NPS and saliva specimens by Wilcoxon signed-rank test (p=0.13). On a large scale of saliva-based population screening, the positive test rate was 1.79% among 389 saliva specimens. Furthermore, saliva sample pooling up to 6 samples for SARS-CoV-2 detection is feasible with sensitivity of 94.8% and specificity of 100%. Conclusions These results demonstrated that the clinical performance of saliva-based testing is comparable to that of NPS-based testing, and that pooling of saliva specimens for SARS-CoV-2 detection is feasible.

Impact of Epidemic on Consumer Economy via Transaction Data

The sudden COVID-19 pandemic has led to unprecedented impact on China's economic and social development, especially on consumer economy. Payment is the most closely related economic activity regarding consumers, the data of which can accurately capture the characteristic of the consumer economy. Given the point of view, this paper makes an in-depth exploration in the research direction of payment data. Based on the transaction data from China UnionPay, this paper quantifies the impact of the epidemic on consumer economy and makes a comparative analysis of different provinces and industries. The paper quantitatively reveals that the epidemic progress significantly affects the consumer confidence and the development of consumer economy. According to our analysis, it is unwise to restart work resumption when the epidemic is still not under effective control. From the perspective of payment, this paper profoundly tells about the story of how China fights against the epidemic and puts forward relevant suggestions for the follow-up epidemic prevention and control as well as the comprehensive economic recovery policies. © 2022, Editorial Office of Journal of Applied Sciences. All right reserved.

Flat warts self-cured in a patient after given COVID-19 vaccination: A case report

A 26-year-old male presented with flat warts for 2 years, and was given the treatment of retinoids and CO2 lattice laser, with poor therapeutic effect. The Patient was given COVID-19 vaccination (vero cell), Inactivated (Beijing Institute of Biological Products Co., Ltd, Batch Number: 2021020088) on May 13, 2021. The lesions colour turned red, and itching obviously after 1 day of vaccination. No treatment was given when the patient visited the doctor on May 17, 2021. The lesions subsided when the patient visited the doctor on May 23, 2021. © 2022 China Journal of Leprosy and Skin Diseases. All rights reserved.