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1.
British Journal of Dermatology ; 187(1):E44-E45, 2022.
Article in English | Web of Science | ID: covidwho-1925328
2.
Journal of China Pharmaceutical University ; 52(5):547-554, 2021.
Article in Chinese | EMBASE | ID: covidwho-1897186

ABSTRACT

Remdesivir-loaded liposomes for inhalation were prepared and the in vitro properties were evaluated. Firstly, preparation methods of remdesivir-loaded liposomes were screened, and single-factor experiments were conducted to optimize the prescription and preparation process. Then the physical property, deposition ratio and aerodynamic particle size distribution of remdesivir-loaded liposomes suspension for inhalation were comprehensively evaluated. As a result, the optimal liposomes were prepared by the thin-film dispersion method with pH 6. 5 phosphate-buffered saline as the hydration medium. In the prescription, the ratio of drug to DPPC was 1:20;the cholesterol accounted for 10% of total lipids;and 20% DSPE-mPEG 2000 was added as stabilizer. 4% trehalose was added as lyoprotectant when lyophilizing to obtain ideal appearance, good stability and a small particle size change after reconstitution. Remdesivir-loaded liposomes were spherical with smooth surface and uniform particle size distribution under transmission electron microscope. In vitro release tests showed no significant change for release curves of remdesivir-loaded liposomes suspension before and after nebulization. Deposition experiments indicated that the fine particles fraction of liposomes was 51. 4%, and the mass median aerodynamic diameter was less than 5 μm measured by next generation impactor. To sum up, remdesivir-loaded liposomes for inhalation with high encapsulation efficiency and stability can achieve a suitable particle size distribution to effectively deposit in the lung after nebulization, which provides a new approach for the treatment of COVID-19.

3.
Zhonghua Kou Qiang Yi Xue Za Zhi ; 57(5): 455-461, 2022 May 09.
Article in Chinese | MEDLINE | ID: covidwho-1818247

ABSTRACT

Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.


Subject(s)
COVID-19 , Oral Medicine , Consensus , Humans , Oral Health
4.
4th International Conference on Robotics, Control and Automation Engineering (RCAE) / 4th International Conference on Advanced Mechanical and Electrical Engineering (AMEE) ; : 251-255, 2021.
Article in English | Web of Science | ID: covidwho-1759127

ABSTRACT

Since December 2019, COVID-19 spread around the world and a number of epidemic protection robot products have emerged with outstanding applications. Combining with the rapid development of mobile network communication technology today, a disinfection robot with real-time remote control operation is designed in this paper. The motion chassis of the disinfection robot designed in this project adopts the wheeled chassis based on Ackerman steering. Based on the mobile network communication technology, operating personnel can remotely drive the robot into the contaminated area for operation, without the need to reach the contaminated area. The robot has the characteristics of flexibility, high efficiency and strong mobility. In addition, it has the ability of cross-region remote operation, high real-time, low delay video transmission ability. At the same time, the remote disinfection robot is equipped with a camera, which can observe the site environment remotely, so that the operator can judge the site environment and adopt the best spray disinfection operation method.

5.
IEEE/CVF International Conference on Computer Vision (ICCVW) ; : 2760-2767, 2021.
Article in English | Web of Science | ID: covidwho-1701881

ABSTRACT

Telehealth has the potential to offset the high demand for help during public health emergencies, such as the COVID-19 pandemic. Remote Photoplethysmography (rPPG) - the problem of non-invasively estimating blood volume variations in the microvascular tissue from video - would be well suited for these situations. Over the past few years a number of research groups have made rapid advances in remote PPG methods for estimating heart rate from digital video and obtained impressive results. How these various methods compare in naturalistic conditions, where spontaneous behavior, facial expressions, and illumination changes are present, is relatively unknown. To enable comparisons among alternative methods, the 1st Vision for Vitals Challenge (V4V) presented a novel dataset containing high-resolution videos time-locked with varied physiological signals from a diverse population. In this paper, we outline the evaluation protocol, the data used, and the results. V4V is to be held in conjunction with the 2021 International Conference on Computer Vision(1).

6.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326798

ABSTRACT

The recently emerged SARS-CoV-2 Omicron variant harbors 37 amino acid substitutions in the spike (S) protein, 15 of which are in the receptor-binding domain (RBD), thereby raising concerns about the effectiveness of available vaccines and antibody therapeutics. Here, we show that the Omicron RBD binds to human ACE2 with enhanced affinity relative to the Wuhan-Hu-1 RBD and acquires binding to mouse ACE2. Severe reductions of plasma neutralizing activity were observed against Omicron compared to the ancestral pseudovirus for vaccinated and convalescent individuals. Most (26 out of 29) receptor-binding motif (RBM)-directed monoclonal antibodies (mAbs) lost in vitro neutralizing activity against Omicron, with only three mAbs, including the ACE2-mimicking S2K146 mAb1, retaining unaltered potency. Furthermore, a fraction of broadly neutralizing sarbecovirus mAbs recognizing antigenic sites outside the RBM, including sotrovimab2, S2X2593and S2H974, neutralized Omicron. The magnitude of Omicron-mediated immune evasion and the acquisition of binding to mouse ACE2 mark a major SARS-CoV-2 mutational shift. Broadly neutralizing sarbecovirus mAbs recognizing epitopes conserved among SARS-CoV-2 variants and other sarbecoviruses may prove key to controlling the ongoing pandemic and future zoonotic spillovers.

7.
Journal of Materials Chemistry C ; : 9, 2022.
Article in English | Web of Science | ID: covidwho-1655684

ABSTRACT

The typical mode of interaction between humans and machines in current intelligent equipment and personalized health care systems is mainly contact-type. However, there are severe problems associated with direct contact, such as uncomfortable wear and cross-infection of bacteria or viruses, especially under global pandemic conditions (e.g., COVID-19, MERS-CoV). In this study, a flexible humidity sensor is developed based on alkalized MXenes and polydopamine (PDA). The unique accordion-like hierarchical structure of the alkalized MXenes with large specific surface area and the chemical structure of the abundant water-absorbing functional groups of PDA wrapped on the MXene surface contribute synergistically to the outstanding performance of the sensor, which has high sensitivity, rapid response, and large detection range. The device was successfully used to control a noncontact switch system based on the distance of the fingertip and monitor different breathing patterns of a volunteer from a long range, proving its potential application in future noncontact human-machine interaction and human physiology monitoring.

8.
Journal of Geo-Information Science ; 23(11):1894-1909, 2021.
Article in Chinese | Scopus | ID: covidwho-1643910

ABSTRACT

The spread of infectious diseases is usually a highly nonlinear space-time diffusion process. Epidemiological models can not only be used to predict the epidemic trend, but also be used to systematically and scientifically study the transmission mechanism of the complex processes under different hypothetical intervention scenarios, which provide crucial analytical and planning tools for public health studies and policy-making. Since host behavior is one of the critical driven factors for the dynamics of infectious diseases, it is important to effectively integrate human spatiotemporal behavior into the epidemiological models for human-hosted infectious diseases. Due to the rapid development of human mobility research and applications aided by big trajectory data, many of the epidemiological models for Coronavirus Disease 2019 (COVID-19) have already coupled human mobility. By incorporating real trajectory data such as mobile phone location data at an individual or aggregated level, researchers are working towards the direction of accurately depicting the real world, so as to improve the effectiveness of the model in guiding actual epidemic prevention and control. The epidemic trend prediction, Non-pharmaceutical Interventions (NPIs) evaluation, vaccination strategy design, and transmission driven factors have been studied by the epidemiological models coupled with human mobility, which provides scientific decision-making aid for controlling epidemic in different countries and regions. In order to systematically understand this important progress of epidemiological models, this study collected and summarized relevant literatures. First, the interactions between the COVID-19 epidemic and human mobility were analyzed, which demonstrated the necessity of integrating the complex spatiotemporal behavior, such as population-based or individual-based mobility, activity, and contact interaction, into the epidemiological models. Then, according to the modeling purpose and mechanism, the models integrated with human mobility were discussed by two types: short-term epidemic prediction models and process simulation models. Among them, based on the coupling methods of human mobility, short-term epidemic prediction models can further be divided into models coupled with first-order and second-order human mobility, while process simulation models can be divided into models coupled with population-based mobility and individual-based mobility. Finally, we concluded that epidemiological models integrating human mobility should be developed towards more complex human spatiotemporal behaviors with a fine spatial granularity. Besides, it is in urgent need to improve the model capability to better understand the disease spread processes over space and time, break through the bottleneck of the huge computational cost of fine-grained models, cooperate cutting-edge artificial intelligence approaches, and develop more universal and accessible modeling data sets and tools for general users. 2021, Science Press. All right reserved.

9.
Journal of Geo-Information Science ; 23(11):1936-1945, 2021.
Article in Chinese | Scopus | ID: covidwho-1643909

ABSTRACT

Many cities in China have adopted a series of Non-Pharmaceutical Interventions (NPIs) and rapidly suppressed the 1 st wave of COVID-19 epidemic in 2020. It is critical to evaluate the effectiveness of these NPIs for future epidemic control. However, as a variety of NPIs were applied together in practice, it is difficult to evaluate the effectiveness of a single type of intervention by epidemiological observation. Taking Shenzhen city as an example, this study used a spatially explicit agent-based model by integrating mobile phone location data, travel survey data, building survey data and other multi-source spatiotemporal big data to evaluate the effectiveness of different types of NPIs in the suppression of the 1 st wave of COVID-19 epidemic in Shenzhen. The simulation results show that the peak of the epidemic would have appeared on the 127 th day since Jan 1st of 2020, resulting in an average of 72.26% of the population to be infected without any interventions. In the 1 st wave of Shenzhen epidemic, except for the hospitalization of confirmed cases and intercity traffic restrictions, the stay-at-home order was the most effective one, followed by comprehensive isolation and quarantine measures (for close contacts, imported population and suspected cases), mask wearing, and orderly resumption of work. The stay-at-home order and comprehensive isolation and quarantine measures can effectively control the large-scale outbreak of the COVID-19, which are identified as the core measures;Mask wearing and orderly resumption of work can only reduce the overall infection size and delay the epidemic peak, which are identified as secondary measures. Considering the socioeconomic costs and the receding compliance to interventions in the post-epidemic period, this study suggests that the core measures and secondary measures should be combined to control the sporadic cases. Specifically, the local government can give the highest priority to isolation and quarantine measures for confirmed cases and high-risk individuals, complemented by mask wearing. In addition, our model can reveal the high-risk infection areas at a community level, which can help deploy control measures within an urban environment. In summary, this study demonstrated the advantages of integrating spatiotemporal big data and agent-based models to simulate the spread processes of infectious diseases in an urban environment: it can not only simulate the evolving processes of an epidemic at a fine-grained scale, but also evaluate the effectiveness of the NPIs at an individual level and for activity-travel behaviors, which can be useful for precise intervention. 2021, Science Press. All right reserved.

10.
12th International Conference on E-business, Management and Economics, ICEME 2021 ; : 224-229, 2021.
Article in English | Scopus | ID: covidwho-1574415

ABSTRACT

In the era of COVID-19, it is particularly important to analyze the correlation of economic indicators and propose corresponding policies. In this paper, a number of industry indicators that have an important impact on the economy are selected, and normalization, interpolation, and PCA operations are performed on them. Based on the MF-LSTM neural network, this paper analyzes the many-to-one correlation between industry indicators and macroeconomic indicators. Furthermore, based on the WNN neural network, wavelet analysis is used to predict the impact of macroeconomic indicators on people's livelihood indicators under time series. Based on the above model, the coupling relationship between industry indicators and macroeconomic indicators and the development trend of people's livelihood indicators for a period of time in the future have been obtained, and the accuracy of the model has also been verified. © 2021 ACM.

11.
Neuro-Oncology ; 23(SUPPL 4):iv24-iv25, 2021.
Article in English | EMBASE | ID: covidwho-1569717

ABSTRACT

AIMS: Primary central nervous system lymphoma (PCNSL) is a rare form of non-Hodgkin lymphoma with exclusive manifestations in the central nervous system, leptomeninges and eyes. It forms around 5% of all primary brain tumours. It is an aggressive tumour which has a poor prognosis if left untreated. It is imperative that diagnosis is made timely so treatment can be started promptly. Therefore, we performed an audit looking into the speed of diagnostic process of PCNSL in our tertiary Neuro-oncology Unit. METHOD: Single-centre retrospective review of PCNSL cases referred to a tertiary Neuro-Oncology Unit over a six month period from June to November 2020. RESULTS: A total of 1309 cases were discussed in the Neuro-oncology MDT meeting over the study period. Fourteen cases (6 male, 8 female;median age [range] 66 [59-83] years) were identified as highly likely PCNSL. Neuroimaging suggested PCNSL as the likely diagnosis in twelve patients. Twelve patients were started on steroids after CT or MRI brain scans. Nine patients had a surgical target and proceeded to have diagnostic brain biopsy. Two patients had different working diagnoses and three patients were deemed unsuitable for brain surgery. One patient required repeat brain biopsy. A tissue diagnosis was made in twelve patients. One patient deteriorated rapidly and one patient had a brain lesion that was deemed too high risk for surgery. The median time between neuroimaging and biopsy was 25 days. The median time taken from first investigation to the pathological confirmation of PCNSL was 36 days (range 6-86 days). CONCLUSION: The chief reason for delay in diagnosis of PCNSL was that patients were started on steroids before diagnostic investigations were completed. Steroids caused the brain lesions to become smaller or disappear. Accordingly, time was needed to allow withdrawal of steroids before diagnostic investigations could be repeated. Diagnostic delays may have been exacerbated by logistical issues associated with COVID-19. We propose that there needs to be greater awareness of how early introduction of steroids can markedly delay the diagnosis of PCNSL.

12.
Chinese Pharmaceutical Journal ; 56(20):1690-1693, 2021.
Article in Chinese | Scopus | ID: covidwho-1566820

ABSTRACT

OBJECTIVE: To study the dose-based BCS (biopharmaceutical classification system) classification of dexamethasone for different indications. METHODS: Saturation shake-flask method was utilized with the conditions of shaking water bath at 37℃ and 120 r•min-1, somewhat excess solids added into saturate systems at pH 1.2, 4.5 and 6.8 buffers respectively. And high-performance liquid chromatography was used for saturation concentration measurement. In this study, the dosages of dexamethasone for both classic and new indications were collected, such as covid-19, which were divided into low-dose, intermediate-dose and high-dose. Then the dissolution volumes (DSVs) were calculated and the indication-based BCS classifications of dexamethasone was studied. RESULTS: At the low-dose, the BCS classification of dexamethasone was high solubility;at the high-dose, the BCS classification of dexamethasone was low;and at the intermediate-dose, the BCS classification of dexamethasone was on the edge of low solubility and high solubility. CONCLUSION: This study provides basic data for the BCS classification of dexamethasone;dose-related solubility classification has guiding significance for the BCS classification of dexamethasone for new indications, and provides refine reference for the rationality of the BE wavier for solid oral dosage forms in the consistency evaluation of generic drugs. Copyright 2021 by the Chinese Pharmaceutical Association.

13.
Otolaryngology - Head and Neck Surgery ; 165(1 SUPPL):P173-P174, 2021.
Article in English | EMBASE | ID: covidwho-1467840

ABSTRACT

Introduction: The COVID-19 pandemic accelerated telemedicine efforts throughout otolaryngology. This study examines the impact of telemedicine visits on surgical yield, financial reimbursement, and patient satisfaction within the head and neck division at a tertiary referral center. Method: This is a retrospective review of new head and neck patients seen via telemedicine between January 2020 and December 2020. Chart review was conducted to identify the reason for the visit and surgical yield. Patient satisfaction was assessed using Press-Ganey surveys. Chi-squared tests were used to compare satisfaction scores, and Wilcoxon rank-sum tests and t tests were used to compare reimbursements. Results: In 2020 the head and neck division saw 1157 new patients in-person and 123 new patients via telemedicine. Telemedicine visits led to 52 (42%) surgeries, and 58 (47%) of patients seen were requesting a second opinion. Financial reimbursement data were available for 42 telemedicine and 202 in-person visits. Average reimbursement for telemedicine visits was 86%. No differences were seen between government and commercial payers in the charges (P = .22) and reimbursements (P = .42) for in-person visits. For the telemedicine visits, charges (P < .01) and reimbursements (P = .03) were significantly less for government payers. Of the telemedicine visits, 91% were rated as 'very good' in patients' likeliness to recommend, compared with 94% of in-person visits (P = .30). Some 91% of telemedicine patients felt that the ability of the care team to explain the condition was 'very good,' compared with 92% of in-person patients (P = .83). For 77% and 78% of patients, a 'very good' rating was given on the ease of contacting and scheduling telemedicine visits, which was not significantly different than the 79% and 83% of patients rating in-person visits (P = .90, P =.55). Conclusion: Definitive decisions about surgical planning can be made effectively by patients and providers in a virtual setting. Patient satisfaction rates are generally high for telemedicine visits and similar to those for in-person visits, but reimbursement for telemedicine visits was notably lower in government payers.

14.
Pattern Recognition Letters ; 150:207-213, 2021.
Article in English | Web of Science | ID: covidwho-1414161

ABSTRACT

Laryngeal disease is a common disease worldwide. However, currently there are no public laryngeal image datasets, which hinders the development of automatic classification of laryngeal disease. In this work, we build a new laryngeal image dataset called Laryngoscope8, which comprises 3057 images of 1950 unique individuals, and the images have been labeled with one of eight labels (including seven pathological labels and one normal label) by professional otolaryngologists. We also propose a laryngeal disease classification method, which uses attention mechanism to obtain the critical area under the supervision of image labels for laryngeal disease classification. That is, we first train a CNN model to classify the laryngeal images. If the classification result is correct, the region with strong response is most likely a critical area. The regions with strong responses are used as training data to train an object localization model that can automatically locate the critical area. Given an image for classification, the trained object localization model is employed to locate the critical area. Then, the located critical area is employed for image classification. The entire process only requires image-level labels and does not require manual labeling of the critical area. Experiment results show that the proposed method achieves promising performance in laryngeal disease classification. (C) 2021 Elsevier B.V. All rights reserved.

15.
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(8): 1330-1335, 2021 Aug 10.
Article in Chinese | MEDLINE | ID: covidwho-1362625

ABSTRACT

This paper summarizes the basic principles and models of early warning for infectious disease outbreaks, introduces the early warning systems for infectious disease based on different data sources and their applications, and discusses the application potential of big data and their analysing techniques, which have been studied and used in the prevention and control of COVID-19 pandemic, including internet inquiry, social media, mobile positioning, in the early warning of infectious diseases in order to provide reference for the establishment of an intelligent early warning mechanism and platform for infectious diseases based on multi-source big data.


Subject(s)
COVID-19 , Communicable Diseases , Communicable Diseases/epidemiology , Disease Outbreaks/prevention & control , Humans , Pandemics , SARS-CoV-2
16.
Proc Assoc Inf Sci Technol ; 57(1): e233, 2020.
Article in English | MEDLINE | ID: covidwho-919820

ABSTRACT

In the fight against the COVID-19 pandemic, understanding how the public responds to various initiatives is an important step in assessing current and future policy implementations. In this paper, we analyzed Twitter tweets using topic modeling to uncover the issues surrounding people's discussion of the disease. Our focus was on temporal differences in topics, prior and after the declaration of COVID-19 as a pandemic. Nine topics were identified in our analysis, each of which showed distinct levels of discussion over time. Our results suggest that as the pandemic progresses, the concerns of the public vary as new developments come to light.

18.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(5): 657-661, 2020 May 10.
Article in Chinese | MEDLINE | ID: covidwho-546795

ABSTRACT

Objective: To assess the imported risk of COVID-19 in Guangdong province and its cities, and conduct early warning. Methods: Data of reported COVID-19 cases and Baidu Migration Index of 21 cities in Guangdong province and other provinces of China as of February 25, 2020 were collected. The imported risk index of each city in Guangdong province were calculated, and then correlation analysis was performed between reported cases and the imported risk index to identify lag time. Finally, we classified the early warming levels of epidemic by imported risk index. Results: A total of 1 347 confirmed cases were reported in Guangdong province, and 90.0% of the cases were clustered in the Pearl River Delta region. The average daily imported risk index of Guangdong was 44.03. Among the imported risk sources of each city, the highest risk of almost all cities came from Hubei province, except for Zhanjiang from Hainan province. In addition, the neighboring provinces of Guangdong province also had a greater impact. The correlation between the imported risk index with a lag of 4 days and the daily reported cases was the strongest (correlation coefficient: 0.73). The early warning base on cumulative 4-day risk of each city showed that Dongguan, Shenzhen, Zhongshan, Guangzhou, Foshan and Huizhou have high imported risks in the next 4 days, with imported risk indexes of 38.85, 21.59, 11.67, 11.25, 6.19 and 5.92, and the highest risk still comes from Hubei province. Conclusions: Cities with a large number of migrants in Guangdong province have a higher risk of import. Hubei province and neighboring provinces in Guangdong province are the main source of the imported risk. Each city must strengthen the health management of migrants in high-risk provinces and reduce the imported risk of Guangdong province.


Subject(s)
Communicable Diseases, Imported , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , COVID-19 , China/epidemiology , Cities , Epidemiological Monitoring , Humans , Pandemics , Risk Assessment
19.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(4): 362-366, 2020 Apr 06.
Article in Chinese | MEDLINE | ID: covidwho-324688

ABSTRACT

Objective: To evaluate the exported risk of COVID-19 from Hubei Province and the imported risk in various provinces across China. Methods: Data of reported COVID-19 cases and Baidu Migration Indexin all provinces of the country as of February 14, 2020 were collected. The correlation analysis between cumulative number of reported cases and the migration index from Hubei was performed, and the imported risks from Hubei to different provinces across China were further evaluated. Results: A total of 49 970 confirmed cases were reported nationwide, of which 37 884 were in Hubei Province. The average daily migration index from Hubei to other provinces was 312.09, Wuhan and other cities in Hubei were 117.95 and 194.16, respectively. The cumulative COVID-19 cases of provinces was positively correlated with the migration index derived from Hubei Province, also in Wuhan and other cities in Hubei, with correlation coefficients of 0.84, 0.84, and 0.81. In linear model, population migration from Hubei Province, Wuhan and other cities in Hubei account for 71.2%, 70.1%, and 66.3% of the variation, respectively. The period of high exported risk from Hubei occurred before January 27, of which the risks before January 23 mainly came from Wuhan, and then mainly from other cities in Hubei. Hunan Province, Henan Province and Guangdong Province ranked the top three in terms of cumulative imported risk (the cumulative risk indices were 58.61, 54.75 and 49.62 respectively). Conclusion: The epidemic in each province was mainly caused by the importation of Hubei Province. Taking measures such as restricting the migration of population in Hubei Province and strengthening quarantine measures for immigrants from Hubei Province may greatly reduce the risk of continued spread of the epidemic.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Risk Assessment , Betacoronavirus , COVID-19 , China/epidemiology , Cities , Humans , Linear Models , Pandemics , SARS-CoV-2
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