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1.
Quantitative Imaging in Medicine and Surgery ; 12(7):15, 2022.
Article in English | English Web of Science | ID: covidwho-1884868

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) is a pandemic disease. Fast and accurate diagnosis of COVID-19 from chest radiography may enable more efficient allocation of scarce medical resources and hence improved patient outcomes. Deep learning classification of chest radiographs may be a plausible step towards this. We hypothesize that bone suppression of chest radiographs may improve the performance of deep learning classification of COVID-19 phenomena in chest radiographs. Methods: Two bone suppression methods (Gusarev et al. and Rajaraman et al.) were implemented. The Gusarev and Rajaraman methods were trained on 217 pairs of normal and bone-suppressed chest radiographs from the X-ray Bone Shadow Suppression dataset (https://www.kaggle.com/hmchuong/xray-bone-shadowsupression). Two classifier methods with different network architectures were implemented. Binary classifier models were trained on the public RICORD-1c and RSNA Pneumonia Challenge datasets. An external test dataset was created retrospectively from a set of 320 COVID-19 positive patients from Queen Elizabeth Hospital (Hong Kong, China) and a set of 518 non-COVID-19 patients from Pamela Youde Nethersole Eastern Hospital (Hong Kong, China), and used to evaluate the effect of bone suppression on classifier performance. Classification performance, quantified by sensitivity, specificity, negative predictive value (NPV), accuracy and area under the receiver operating curve (AUC), for non-suppressed radiographs was compared to that for bone suppressed radiographs. Some of the pre-trained models used in this study are published at (https://github.com/danielnflam). Results: Bone suppression of external test data was found to significantly (P<0.05) improve AUC for one classifier architecture [from 0.698 (non-suppressed) to 0.732 (Rajaraman-suppressed)]. For the other classifier architecture, suppression did not significantly (P>0.05) improve or worsen classifier performance. Conclusions: Rajaraman suppression significantly improved classification performance in one classification architecture, and did not significantly worsen classifier performance in the other classifier architecture. This research could be extended to explore the impact of bone suppression on classification of different lung pathologies, and the effect of other image enhancement techniques on classifier performance.

2.
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.

3.
Topics in Antiviral Medicine ; 30(1 SUPPL):174-175, 2022.
Article in English | EMBASE | ID: covidwho-1881004

ABSTRACT

Background: Symptoms reduction is a crucial outcome to be considered when testing novel treatments for COVID-19. The goal was to assess the impact of casirivimab+imdevimab (cas+imd) dose/exposure on the trajectory and resolution time of symptoms in outpatients with COVID-19. Methods: Analysis used data from the COV-2067 trial (NCT04425629). Cas+imd was administered intravenously (total dose 1.2 to 8 g). Symptoms data were collected using SE-C19, a patient-reported survey developed de novo to assess the symptomatic course of COVID-19. Based on patients' responses on SE-C19, a Rasch analysis was used to derive a latent score to infer their overall underlying symptom severity. A direct response model was fitted to the latent score-time data to quantify the effects of dose/exposure, demographic and clinical characteristics on latent symptom trajectory. Symptoms resolution time was defined as time from randomization to the 1st day during which the patient scored "no symptom". Several parametric models were tested as structural model, assuming a known distribution, eg, exponential or Weibull, for time to symptoms resolution data. Risk variables (eg, binary treatment or categorical dose levels, exposure metrics, baseline demographic, clinical, and biological characteristics) were tested as covariates using a proportional hazard model. Results: Results from the direct response model suggest that each dose, as compared to placebo, remarkably reduced IT50 (time taken to achieve half of the maximal response of reducing symptom) by ∼40%. By excluding data from placebo arm, none of the tested doses or predicted exposures, were significant covariates on any of the model parameters. Results from the parametric regression analysis further confirmed that cas+imd (HR=1.25) is a major factor shortening the symptoms resolution time in a dose-and exposure-independent manner. Males (HR=1.13) have a shorter symptoms resolution time. Older age (HR=0.991), higher BMI (HR=0.988), and more severe baseline symptoms (HR=0.783 for moderate and 0.589 for severe) significantly contribute to longer symptoms resolution time. Conclusion: Treatment with cas+imd (1.2 g or above), rapidly resolved symptoms in outpatients in a dose-and exposure-independent manner as indicated by a direct response model using derived latent score and further confirmed by a survival analysis using time to symptoms resolution. In addition, symptom severity, age, BMI, sex were major risk factors affecting the symptoms resolution time.

4.
American Journal of Respiratory and Critical Care Medicine ; 205:1, 2022.
Article in English | English Web of Science | ID: covidwho-1880765
6.
Molecular Therapy ; 30(4):11-12, 2022.
Article in English | English Web of Science | ID: covidwho-1880181
7.
Topics in Antiviral Medicine ; 30(1 SUPPL):176, 2022.
Article in English | EMBASE | ID: covidwho-1880117

ABSTRACT

Background: Casirivimab+imdevimab (hereinafter referred to as drug) remains vital in reducing hospitalization/death by 70% when administered early in the course of the infection. Our aim was to illustrate the mechanism of drug action in vivo and determine the magnitude of antiviral efficacy of various dose regimens given to outpatients with COVID-19, evaluating the presence of SARS-CoV-2 sero-antibody and ≥1 high-risk factor for developing severe COVID-19 illness as predictors of viral kinetics. Methods: Analysis data came from 2 clinical studies in SARS-CoV-2 infected outpatients with no or ≥1 risk factor for severe COVID-19 (NCT04425629 and NCT04666441), who received single dose of placebo or drug IV (300mg to 8g) or SC (600mg to 1.2g), had assessed viral load in nasopharyngeal swab and drug concentrations in serum (N=4500). The median number of viral load assessments per patient was 5 (range 1-8) within up to 14 days of follow-up time. Drug concentrations were predicted using the individual pharmacokinetic parameters yielded by a population model. The median patient age was 42 years, with similar proportion of males and females. The median viral load at baseline was 6.79 log10 copies/mL, and the median time of symptom onset was 3 days before study baseline. A standard target cell-limited model was used to estimate the time of infection and reconstruct viral kinetic profiles. Various relationships between exposure and resulting antiviral response were evaluated, where the drug could block de novo infection, increase the elimination rate of infected cells, or reduce viral production from infected cells. Results: The results support that the main mechanism of drug action is blocking de novo infection with an estimated decrease in the infectivity rate of 96.6%, for all dose regimens evaluated herein. High-risk factor for severe COVID-19 and baseline sero-antibody-positive/other status were associated with a 4.71% decrease and a 4.96% increase in the elimination rate of infected cells, respectively. The estimated median and 95th percentile of time to viral clearance (ie, viral count reaches below assay quantification limit) were 1.4 and 3.4 days shorter in drug vs placebo (median 10.6 vs 12.0 days, and 95th percentile 15.2 vs 18.6 days). Conclusion: All IV and SC casirivimab+imdevimab dose regimens evaluated herein showed similar near-maximal antiviral activity by blocking de novo infection;hence, shortening the time to virus clearance.

8.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-338321

ABSTRACT

We developed a spatially structured, fully stochastic, individual-based SARS-CoV-2 transmission model to evaluate the feasibility of sustaining SARS-CoV-2 local containment in mainland China considering currently dominant Omicron variants, China's current immunization level, and non-pharmaceutical interventions (NPIs). We also built a statistical model to estimate the overall disease burden under various hypothetical mitigation scenarios. We found that due to high transmissibility, neither Omicron BA.1 or BA.2 could be contained by China's pre-Omicron NPI strategies which were successful prior to the emergence of the Omicron variants. However, increased intervention intensity, such as enhanced population mobility restrictions and multi-round mass testing, could lead to containment success. We estimated that an acute Omicron epidemic wave in mainland China would result in significant number of deaths if China were to reopen under current vaccine coverage with no antiviral uptake, while increasing vaccination coverage and antiviral uptake could substantially reduce the disease burden. As China's current vaccination has yet to reach high coverage in older populations, NPIs remain essential tools to maintain low levels of infection while building up protective population immunity, ensuring a smooth transition out of the pandemic phase while minimizing the overall disease burden.

9.
Future Cities and Environment ; 8(1):1-14, 2022.
Article in English | Scopus | ID: covidwho-1876043

ABSTRACT

Photocatalytic oxidation (PCO) is a potential approach for air cleaning, especially when utilising titanium dioxide (TiO2). A MopFan is similar to a roller brush but is made of flexible fibres coated with TiO2. Unlike conventional filter/mesh UV systems, a MopFan provides a wide UV-TiO2 interaction surface area and airflow passage. This revolutionary technique can be low cost, efficient, and potentially effective against viruses, making it suitable for cleaning indoor air. It is easy to use but technically advanced. The system may be mounted on walls, floors, or placed on desktops. A photocatalytic air purification based on MopFan prototype was designed, constructed and tested. This study utilised copper wires (0.1 mm, 0.3 mm, 0.4 mm, and 0.5 mm), plastic fibres (0.5 mm and 1.1 mm), brass wire (0.4 mm), steel wire (0.38 mm), and organic “coco” fibres (0.4 mm). Copper wire (0.5 mm) and organic fibre (0.4 mm) were found to be effective against SARS-CoV-2, but brass (0.4 mm) and plastic (0.5 mm) fibres were found only partially effective. The purification performance was compared using MopFan with plastic (0.5 mm), brass (0.4 mm) and organic “coco” (0.4 mm) fibres but the other materials were rejected due to their poor qualities or difficulties in manufacturing. It was found that the system has a better effectiveness with organic fibres, around 21% of reduction consistently throughout the test. It was also found that by using the photocatalytic MopFan air cleaning system, the final concentration of pollutants in a room is determined by the rate and concentration of pollutant generation. Highlights 1. Organic fibres do not require sanding prior to being coated with TiO2 solution. 2. Copper and organic fibres are effective SARS-CoV-2 inhibitors. 3. Organic fibres are the most efficient for air purification. 4. The performance of purification is related to the concentration of pollutants. © 2022 The Author(s).

10.
Diabetic Medicine ; 39(SUPPL 1):116-117, 2022.
Article in English | EMBASE | ID: covidwho-1868635

ABSTRACT

Background and Aims: During the covid-19 pandemic revisions were recommended to the gestational diabetes diagnostic criteria. Given the characteristics of our inner city multi-ethnic cohort, we continued with the NICE 2015 criteria. We aimed to determine the incidence of gestational diabetes during the first wave of the covid-19 pandemic. Methods: Women diagnosed with gestational diabetes in March-July 2020 were retrospectively reviewed and compared to two separate historical time-matched cohorts (03-07/ 2018 and 03-07/ 2017). Maternal demographics, gestational diabetes incidence and fetal outcomes were compared. Results: 953 pregnancies were registered in 2020, 963 in 2018 and 1162 in 2017. The highest gestational diabetes incidence was observed in the covid-19 cohort (12.6% (n = 120), 7.3% (n = 70) and 4.4% (n = 52) respectively, p < 0.001). On average, women were diagnosed with GDM later in 2020 (mean gestational age (GA) 28.6 weeks, 27.0 and 27.0 weeks, p < 0.001). Mean ( ± SD) age, height, and early pregnancy weight/ body mass index were similar. Proportional differences in women with gestational diabetes of non-white ethnicity were exhibited, with the lowest proportion in 2020 (77.0%, 86.4% and 82.9% respectively, p < 0.001). Mean ( ± SD) fetal birth weight varied across the groups (3237.5 ( ± 473)g, 3117 ( ± 647)g and 2981 ( ± 845)g, p < 0.001). There were no differences in adjusted fetal birth weight centiles. Mean (SD) GA at birth was higher in 2020 (38.8 ( ± 1.26), 38.4 ( ± 2.38), 37.60 ( ± 5.1) weeks, p = 0.03). Conclusions: A significant increase in the diagnosis of gestational diabetes during the covid-19 epidemic was observed. The implementation of national lockdowns may have resulted in reduced physical activity and excess gestational weight gain, which could explain this.

11.
Traditional Medicine Research ; 7(4), 2022.
Article in English | EMBASE | ID: covidwho-1870367

ABSTRACT

Respiratory diseases are common conditions that endanger human health. Their etiology, pathogenesis, and prognosis are complex, and clinical research has been extensive. This paper reviews studies from the PubMed database to assess the progress of traditional Chinese medicine in the treatment of respiratory diseases in 2021, focusing on related animal and cell models of coronavirus disease 2019. Traditional Chinese medicine extracts, such as polysaccharides and emodin, and classic prescriptions, such as Mahuang decoction, respond to the treatment of influenza by reducing viral infections and regulating the body’s immune response. Chinese herbal extracts, such as schizandra B and andrographolide, treat asthma by inhibiting inflammatory response pathway formation, NLRP3 inflammasome formation, oxidative stress, and autophagy. Traditional Chinese medicine extracts such as fucoxanthin, and proprietary Chinese medicines such as the Xihuang pill is used in the treatment of lung cancer, as it regulates the cell cycle, inhibit tumor cell proliferation, and enhance the body’s immune function. Classic formulas such as the kidney tonic lung formula and proprietary Chinese medicine, such as compound grass stone silkworm granules, relieve airway inflammation and improve lung function in chronic obstructive pulmonary disease. Chinese herbal extracts, such as jostilbene and sage phenol, inhibit epithelial cell–mesenchymal transformation and regulate the levels of inflammatory factors to treat idiopathic pulmonary fibrosis to provide a reliable basis for the treatment of respiratory diseases.

12.
Chinese Journal of Biologicals ; 34(5):607-611, 2021.
Article in Chinese | EMBASE | ID: covidwho-1857858

ABSTRACT

The pandemic of Coronavirus Disease 2019 (COVID-19) in 2020 has posed a great challenge to global public health resources. Since there are no specific antiviral drugs at present, convalescent plasma (CP) from patients who have recovered from COVID-19 is one of the specific biologic therapies being considered to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Preliminary studies have shown that the CP containing high titer neu¬tralizing antibody against SARS-CoV-2 is safe and promising in blocking viral replication and improving patients'clinical symptoms. In this article, we briefly summarize the application of CP in treatment of COVID-19, and explores possible action mechanism, relevant clinical research and possible influencing factors of clinical effect, which may be helpful to the rational application of CP in treatment of COVID-19.

13.
Modern Pathology ; 35(SUPPL 2):969-970, 2022.
Article in English | EMBASE | ID: covidwho-1857373

ABSTRACT

Background: Since the first case of COVID19 infection in 2019, this RNA virus has led an unprecedented pandemic that infected more than 232 million people. Although the disease is studied extensively, much remains poorly understood. Here, we performed the first correlation study on the peripheral blood morphology and immunophenotype of the white blood cells (WBCs) from COVID19 patients. Design: A total of 52 samples from COVID19 patients and 15 blood samples as control group were analyzed. COVID19 patients were divided into two groups based on clinical severity, severe (respiratory failure) or non-severe (hospitalized but stable). The controls were the patients with negative COVID19 results by PCR and antibody tests. The WBC morphology was examined either by blood smear review or via CellaVision DM analyzer captured images. Navios flow cytometer and Beckman Kaluza C software were used for immunophenotype analysis. Two-tailed T-test was performed on the COVID19 groups and the control group Results: Almost all COVID19 patients showed marked neutrophilia and lymphopenia on the CBC tests. Morphologically, the neutrophils showed irregularities like hypogranulation, toxic granules and pseudo Pelger-Huet anomaly (Fig 1A). In severe COIVD19 group, there was an increase in neutrophils with immatures phenotypes, showing CD33 positivity while CD10, CD13 and CD16 negative (Fig 1B). Conversely, the CD10(+) mature neutrophils aberrantly expressed CD56 (Fig 1B). The percentage of CD56(+) neutrophils was significantly higher in both COVID19 groups, suggesting a stronger cellular adhesion and interaction. The monocytes from the COVID19 patients had increased cytoplasm with cytoplasmic protrusion and vacuolization (Fig 2A). Phenotypically they were positive for CD13, CD33, CD38 and HLA-DR. The lymphocytes were also atypical, including increased cytoplasm with large granules and vacuoles. Phenotypically, they are activated, expressing CD38, HLA-DR, and mainly α/β subtype. Giant platelets with cytoplasmic vacuoles and projections were easily seen. Platelet aggregations were observed (Fig 2B). These platelets were CD45(-) and expressed CD61 at lower-than-normal intensity, while expressing increased CD42b intensity when compared to the control group on a log scale. Conclusions: Despite being a small study, we were able to correlate the morphologic and phenotypic alterations of the WBCs in COVID19 patients. As such, this helped to explain some of the clinical hematologic manifestation of the disease. (Figure Presented).

14.
Emerging Markets Finance and Trade ; : 12, 2022.
Article in English | Web of Science | ID: covidwho-1852672

ABSTRACT

We employ the state-dependent local projection method to identify the dynamic risk aggravation effects on Treasury market volatilities and risk spillovers under both local and global COVID-19 pandemic shocks. We find that emerging markets suffer more instability as risk receivers during the pandemic. Local pandemic shock sharpens the risk spillover mainly in the short run, especially when global risk is high, while global pandemic shock aggravates spillover in the medium run led by economic depression expectations. The results are not only helpful to encourage governments to deepen cooperation in combating the pandemic but also alert authorities to pay more attention to imported financial risk.

16.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-336964

ABSTRACT

As SARS-CoV-2 variants of concerns (VOCs) continue to emerge, cross-neutralizing antibody responses become key towards next-generation design of a more universal COVID-19 vaccine. By analyzing published data from the literature, we report here that the combination of germline genes IGHV2-5/IGLV2-14 represents a public antibody response to the receptor-binding domain (RBD) that potently cross-neutralizes all VOCs to date, including Omicron and its sub-lineages. Detailed molecular analysis shows that the complementarity-determining region H3 sequences of IGHV2-5/IGLV2-14-encoded RBD antibodies have a preferred length of 11 amino acids and a conserved HxIxxI motif. In addition, these antibodies have a strong allelic preference due to an allelic polymorphism at amino-acid residue 54 of IGHV2-5, which locates at the paratope. These findings have important implications for understanding cross-neutralizing antibody responses to SARS-CoV-2 and its heterogenicity at the population level as well as the development of a universal COVID-19 vaccine.

17.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-336850

ABSTRACT

We developed a spatially structured, fully stochastic, individual-based SARS-CoV-2 transmission model to evaluate the feasibility of sustaining a "Zero-COVID" policy in mainland China in light of currently dominant Omicron variants, China's current immunization level, and non-pharmaceutical intervention (NPI) strategies. We found that due to high transmissibility, neither Omicron BA.1 or BA.2 sublineages could be contained by China's Pre-Omicron non-pharmaceutical intervention strategies which were successful at sustaining the "Zero-COVID" policy until March 2022. However, increased intervention intensity, such as enhanced population mobility restrictions and multi-round mass testing, could lead to containment success without the necessity of population-wide lockdown. As China's current vaccination has yet to reach high coverage in older populations, non-pharmaceutical interventions remain essential tools to maintain low levels of infection while building protective population immunity, ensuring a smooth transition out of the pandemic phase, and minimizing the overall disease burden and societal costs.

18.
Drugs and Clinic ; 37(3):622-626, 2022.
Article in Chinese | Scopus | ID: covidwho-1847650

ABSTRACT

Objective To analyze and summarize the use and rationality of blood-activating TCM injections in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from 2019 to 2020, so as to provide reference for rational drug use in clinic. Methods The hospital information system and Excel software were used to analyze the use of TCM injections for promoting blood circulation from January 2019 to December 2020. Results In 2020 the application of blood-activating Chinese medicine injections in our hospital decreased by 20.68% compared with 2019, but the proportion of total Chinese patent medicine was basically the same. Xueshuantong (freeze-dried) for injection is the blood activating traditional Chinese medicine injection with the highest sales amount and use frequency in 2019 and 2020. The average daily cost of blood-activating TCM injections in 2020 decreased as a whole, and the synchronization was more reasonable. Although the use of blood-activating TCM injections has been affected by COVID-19, medical policies have a greater impact on the application of traditional Chinese medicine injections. Conclusion Blood-activating traditional Chinese medicine injection is an important part of hospital medication, and its application is relatively reasonable, and continue to improve the level of rational drug use, so that it can play a greater role in clinical practice. © 2022 Tianjin Press of Chinese Herbal Medicines. All rights reserved.

19.
7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021 ; : 296-299, 2021.
Article in English | Scopus | ID: covidwho-1840234

ABSTRACT

As social media becomes more and more popular, fake news spreads rapidly which is more likely to cause serious consequences, especially during the COVID-19 pandemic. On the premise of meeting data privacy and security requirements, federated learning uses multi-party heterogeneous data to further promote machine learning. This paper proposes a federal learning based COVID-19 fake news detection model with deep self-attention network (FL-FNDM). We construct a deep self-attention network for fake news detection, which combines self-attention-based pretrained model BERT and deep convolutional neural network to detect fake news. Moreover, the fake news detection model is learned under the framework of horizontal federated learning, aiming at protecting users' data security and privacy. The experimental results demonstrate that the proposed model can improve the performance of fake news detection on the COVID-19 dataset, which can achieve almost the same effect of sharing data without leaking user data. © 2021 IEEE.

20.
2021 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2021 ; : 641-646, 2021.
Article in English | Scopus | ID: covidwho-1832578

ABSTRACT

Since the spread of COVID-19 around the world, a series of policies and measures are adopted by the Japanese government to control the epidemic. As a result of these policies, people's daily life and the functional division of society have changed. In order to understand the changes in urban function and people's daily behavior over the past year, we collected and analyzed over 1.13 million social media data (Twitter in our example) containing geographic information. We propose regional competitiveness, which represents the access frequency of social data in each raster unit to several attributes. In order to analyze the regional competitiveness in different categories and map tiles, we applied an improved spatio-temporal graph attention network model (ST-GAT) based on unstructured POI (point of interest) data and Twitter data in different levels of the map to the city-regional competitiveness. We have developed and evaluated the competitiveness map tiles based on 5 attributes utilized Twitter data at 2020 of Kyoto in Japan. As the spread of COVID-19 disease and government anti-epidemic measures change the frequency of visits to the core of the city and the trend of regional competitiveness, and our results showed that the regional competitiveness in the map tiles obtained by social media data and POI data visualizes the dynamic change analysis of crowd behavior activities and urban social functions. This research enlightens the promising future of spatio-temporal GAT in users' dynamic responses with geographic information. © 2021 ACM.

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