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1.
Traditional Medicine and Modern Medicine ; 3(1):51-57, 2020.
Article in English | EMBASE | ID: covidwho-1582953

ABSTRACT

Objective: To analyze the distribution characteristics of syndrome of TCM of the patients with COVID-19 in Kunming, China. Methods: To classify and summarize the TCM syndrome types of COVID-19 patients via Cluster analysis combining with tongue image, chest CT and clinical expertise of 36 Covid-19 patients in Kunming. Results: In the 36 cases of Kunming region confirmed COVID-19 patients, 17 cases had fever (47.2%), 18 cases had cough (50%), 16 cases felt bitter taste in the mouth (44.4%), 18 cases felt dry throat (50.0%), 17 cases had poor appetite (47.2%), 15 cases had nausea (41.7%);12 cases had diarrhea (33.3%), 15 cases had insomnia (41.7%);12 cases had chest tightness (33.3%);3 cases had dyspnea (8.3%);6 cases had nasal congestion and running nose (16.7%);15 cases had fatigue (41.7%);6 cases had headache and body pain (16.7%);5 cases had red tongue (13.9%);18 cases had pale red tongue (50%);8 cases had tongue with red edge and tip (22.2%);3 cases had dark red tongue (8.3%);2 cases had cyanosis (5.6%);3 cases had swollen tongue (8.3%);18 cases had dentate tongue (50%);4 cases had yellow tongue coating (11.1%);5 cases had yellow sticky tongue coating (13.9%);12 cases had white sticky tongue coating (33.3%);6 cases had thin white tongue coating (16.7%);2 cases had no tongue coating (5.6%). The chest CT results showed that: There were five cases without lesions. The lesions were located in the upper lobe of one lung in 13 cases located in the lower lobe of one lung in seven cases, located in the upper middle lobe in three cases, located in the lower lobe in five cases, and in the upper middle and lower lobes of double lung in 13 cases. There were 14 cases of Shaoyang syndrome, 17 cases of wet Resistance Tir-juao Syndrome. According to the time of onset, the disease was followed by Shaoyang Syndrome (1 day), the Wet blocked tri-jiao Syndrome (3 days), epidemic poison retention lung syndrome and syndrome of flaring heat in qifen and yingfen (5 days), and dampness-toxicity lung-stagnation syndrome (6 days). Conclusion: The TCM syndromes of COVID-19 in Kunming are mainly the Wet Resistance Tri-Jiao Syndrome and Shaoyang syndrome, followed by dampness-toxicity lung-stagnation syndrome, epidemic poison retention lung and syndrome of flaring heat in qifen and yingfen.

2.
Chinese Journal of Liquid Crystals and Displays ; 36(11):1525-1534, 2021.
Article in English | Web of Science | ID: covidwho-1573168

ABSTRACT

During the period of 2019-nCoV controlling, to prevent the spread of the virus, it is necessary to regulate the coverage of mask wearing in densely populated places such as airports and stations. In order to effectively monitor the coverage of mask wearing of crowd, this paper proposes a lightweight mask detection algorithm based on improved YOLOv4-tiny. Following the backbone network of YOLOv4-tiny, a spatial pyramid pooling structure is introduced to pool and fuse the input features at multi-scale, which makes the receptive field of the network enhanced. Then, combined with the path aggregation network, multi-scale features are fused and enhanced repeatedly in two paths to improve the expressive ability of feature maps. Finally, label smoothing is utilized to optimize the loss function for modifying the over-fitting problem in the training process. The experimental results show that the proposed algorithm achieves 94.7% AP and 85.7% AP on mask target and face target respectively (at real-time speed of 76.8 FPS on GeForce GTX 1050ti), which is 4.3% and 7.1% higher than that of YOLOv4-tiny. The proposed algorithm meets the accuracy and real-time requirements of mask detection tasks in various scenes.

3.
Environment and Development Economics ; 2021.
Article in English | Scopus | ID: covidwho-1550186

ABSTRACT

This paper explores the short-run impact of work resumption, extensively launched on February 10, 2020 in China, on air quality after the subsiding of COVID-19. Utilizing the data of 1012 air-quality monitoring sites in 233 cities derived from the Real-Time Release Air Quality Platform and the difference-in-differences method, we find that alternative measures of air quality index in non-Hubei provinces increase significantly, compared with those in Hubei province which was temporarily not allowed work resumption due to the severity of epidemic. Specifically, our results reveal a rise in AQI of 11.28 per cent, in PM2.5 of 12.47 per cent, in PM10 of 10.49 per cent, and in NO2 of 23.64 per cent, relative to the baseline mean. Moreover, the deterioration of air quality is found to be caused by intracity rather than intercity migration. Copyright © The Author(s), 2021. Published by Cambridge University Press.

4.
Preprint in English | PUBMED | ID: ppcovidwho-292966

ABSTRACT

With the emergence of SARS-CoV-2 variants, there is urgent need to develop broadly neutralizing antibodies. Here, we isolate two V H H nanobodies (7A3 and 8A2) from dromedary camels by phage display, which have high affinity for the receptor-binding domain (RBD) and broad neutralization activities against SARS-CoV-2 and its emerging variants. Cryo-EM complex structures reveal that 8A2 binds the RBD in its up mode and 7A3 inhibits receptor binding by uniquely targeting a highly conserved and deeply buried site in the spike regardless of the RBD conformational state. 7A3 at a dose of a5 mg/kg efficiently protects K18-hACE2 transgenic mice from the lethal challenge of B.1.351 or B.1.617.2, suggesting that the nanobody has promising therapeutic potentials to curb the COVID-19 surge with emerging SARS-CoV-2 variants. One-Sentence Summary: Dromedary camel ( Camelus dromedarius ) V H H phage libraries were built for isolation of the nanobodies that broadly neutralize SARS-CoV-2 variants.

5.
Precision Clinical Medicine ; 4(3):149-154, 2021.
Article in English | EMBASE | ID: covidwho-1467398

ABSTRACT

To assess the impact of the key non-synonymous amino acid substitutions in the RBD of the spike protein of SARS-CoV-2 variant B.1.617.1 (dominant variant identified in the current India outbreak) on the infectivity and neutralization activities of the immune sera, L452R and E484Q (L452R-E484Q variant), pseudotyped virus was constructed (with the D614G background). The impact on binding with the neutralizing antibodies was also assessed with an ELISA assay. Pseudotyped virus carrying a L452R-E484Q variant showed a comparable infectivity compared with D614G. However, there was a significant reduction in the neutralization activity of the immune sera from non-human primates vaccinated with a recombinant receptor binding domain (RBD) protein, convalescent patients, and healthy vaccinees vaccinated with an mRNA vaccine. In addition, there was a reduction in binding of L452R-E484Q-D614G protein to the antibodies of the immune sera from vaccinated non-human primates. These results highlight the interplay between infectivity and other biologic factors involved in the natural evolution of SARS-CoV-2. Reduced neutralization activities against the L452R-E484Q variant will have an impact on health authority planning and implications for the vaccination strategy/new vaccine development.

6.
45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021 ; : 914-923, 2021.
Article in English | Scopus | ID: covidwho-1447798

ABSTRACT

Ever since the beginning of the outbreak of the COVID-19 pandemic, researchers from interdisciplinary domains have worked together to fight against the crisis. The open source community, plays a vital role in coping with the pandemic which is inherently a collaborative process. Plenty of COVID-19 related datasets, tools, software, deep learning models, are created and shared in research communities with great efforts. However, COVID-19 themed open source projects have not been systematically studied, and we are still unaware how the open source community helps combat COVID-19 in practice. To fill this void, in this paper, we take the first step to study COVID-19 themed repositories in GitHub, one of the most popular collaborative platforms. We have collected over 67K COVID-19 themed GitHub repositories till July 2020. We then characterize them from a number of aspects and classify them into six categories. We further investigate the contribution patterns of the contributors, and development and maintenance patterns of the repositories. This study sheds light on the promising direction of adopting open source technologies and resources to rapidly tackle the worldwide public health emergency in practice, and reveals existing challenges for improvement. © 2021 IEEE.

7.
33rd International Conference on Software Engineering and Knowledge Engineering, SEKE 2021 ; 2021-July:249-254, 2021.
Article in English | Scopus | ID: covidwho-1404149

ABSTRACT

The ongoing COVID-19 pandemic has impact almost every aspect of human lives profoundly. This paper investigates the impact of COVID-19 on the activity and contribution of open source software (OSS) developers. Specifically, we make great efforts to harvest the information of all the developers (over 25 million) on GitHub and their contribution activities. With such a large-scale dataset, we perform analysis from four perspectives, including the overall ecosystem level, country level, organization level and developer level, to characterize the impact of COVID-19 on the OSS community. We have revealed a number of interesting observations and trends, which are crucial to understanding the OSS contributors and supporting the collaboration to combat global crisis like COVID-19. © 2021 Knowledge Systems Institute Graduate School. All rights reserved.

8.
35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence ; 35:4804-4811, 2021.
Article in English | Web of Science | ID: covidwho-1381651

ABSTRACT

Coronavirus Disease 2019 (COVID-19) causes a sudden turnover to bad at some checkpoints and thus needs the intervention of intensive care unit (ICU). This resulted in urgent and large needs of ICUs posed great risks to the medical system. Estimating the mortality of critical in-patients who were not admitted into the ICU will be valuable to optimize the management and assignment of ICU. Retrospective, 733 in-patients diagnosed with COVID-19 at a local hospital (Wuhan, China), as of March 18, 2020. Demographic, clinical and laboratory results were collected and analyzed using machine learning to build a predictive model. Considering the shortage of ICU beds at the beginning of disease emergence, we defined the mortality for those patients who were predicted to be in needing ICU care yet they did not as Missing-ICU (MI)-mortality. To estimate MI-mortality, a prognostic classification model was built to identify the in-patients who may need ICU care. Its predictive accuracy was 0.8288, with an AUC of 0.9119. On our cohort of 733 patients, 25 in-patients who have been predicted by our model that they should need ICU, yet they did not enter ICU due to lack of shorting ICU wards. Our analysis had shown that the MI-mortality is 41%, yet the mortality of ICU is 32%, implying that enough bed of ICU in treating patients in critical conditions.

10.
Iranian Journal of Radiology ; 18(3), 2021.
Article in English | EMBASE | ID: covidwho-1377096

ABSTRACT

Background: The novel coronavirus disease 2019 (COVID-19) has become a global public health emergency. Computed tomography (CT) offers valuable clues to the diagnosis of COVID-19. However, little is known about the correlation between dynamic changes of CT scores and therapeutic response in the course of COVID-19. Objectives: To describe the temporal changes of CT findings and characterize the time window of disease progression on the follow-up CT scans of patients with COVID-19. Patients and Methods: In this historical cohort study performed in Shanghai, China, the follow-up chest CT images of 91 patients with COVID-19 with different therapeutic responses were reviewed in multiple centers, with an emphasis on characterizing the changing trend of CT scores for lung lesions at 13-15 days after the symptom onset and thereafter. The CT score curve patterns were categorized into type 1 (characterized by an increase to the peak level, followed by a decrease), type 2 (characterized by a steady change without an obvious peak), and type 3 (characterized by a progressive increase). Results: The CT scores of the progression group (n = 9) with a longer time to the peak were significantly higher than those of the non-progression group (n = 82) on the first day and days 13-15 (P < 0.05), except for the median CT scores before days 13-15. The CT curve type 1 and type 2 were commonly observed in the non-progression group (63.4% and 36.6%, respectively), while type 3 was more common in the progression group (88.9%). Conclusion: Most patients with COVID-19 show favorable responses to clinical treatments in Shanghai. Thirteen to fifteen days after the symptom onset can be considered as a turning point for the therapeutic response. The CT curve type 3 usually represents a poor response. The CT scores of patients with different therapeutic responses may overlap before days 13-15. The changing trend of longitudinal CT scores may contribute to the prediction of disease progression.

11.
2020 Ieee International Conference on Bioinformatics and Biomedicine ; : 555-561, 2020.
Article in English | Web of Science | ID: covidwho-1354409

ABSTRACT

COVID-19 causes burdens to the ICU. Evidence-based planning and optimal allocation of the scarce ICU resources is urgently needed but remains unaddressed. This study aims to identify variables and test the accuracy to predict the need for ICU admission, death despite ICU care, and among survivors, length of ICU stay, before patients were admitted to ICU. Retrospective data from 733 in-patients confirmed with COVD-19 in Wuhan, China, as of March 18, 2020. Demographic, clinical and laboratory were collected and analyzed using machine learning to build the predictive models. The built machine learning model can accurately assess ICU admission, length of ICU stay, and mortality in COVID-19 patients toward optimal allocation of ICU resources. The prediction can be done by using the clinical data collected within 1-15 days before the actual ICU admission. Lymphocyte absolute value involved in all prediction tasks with a higher AUC.

12.
International Journal of Clinical and Experimental Medicine ; 14(7):2123-2131, 2021.
Article in English | EMBASE | ID: covidwho-1346973

ABSTRACT

Coronavirus disease (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) still has no specific laboratory markers to assess severity. As a novel acute infectious disease, early recognition of severe cases (nearly 20%) is essential for early triage and corresponding treatment. This study aimed to summarize the potential practical predictors for clinicians to identify severe cases during hospitalization. We collected the clinical laboratory data as well as the demographic, epidemiological and clinical information from 58 COVID-19 patients (26 severe cases, 32 mild cases) in Xiangyang Central Hospital (Xiangyang, China) during their hospitalization. The correlation between laboratory parameters and disease severity, laboratory parameters dynamics and the outcome of severe COVID-19 patients were fully analyzed. Finally, we compared the characteristics between severe and mild cases and summarized several laboratory parameters. The median age, concomitant diseases, PT, FIB, DD, ISTH/CDSS score, UN, CK, ESR and CRP were significantly higher in the severe cases, while the LYM count, viral nucleic acid Ct value, and Alb were significantly lower. Logistic regression analysis and AUC of ROC showed that Ct, Alb, CK, ESR and CRP may be good predictors for the severity of COVID-19 cases and patient prognosis. Laboratory parameter dynamics indicated the repletion of LYM, Alb, D-D, UN, CK, ESR and CRP may be important for the recovery of severe cases. Low Ct value and other parameters may have the potential to discriminate mild and severe COVID-19 cases and could be used as prognostic markers to guide treatment.

13.
2020 Ieee 22nd International Workshop on Multimedia Signal Processing ; 2020.
Article in English | Web of Science | ID: covidwho-1261630

ABSTRACT

Confinement during COVID-19 has caused serious effects on agriculture all over the world. As one of the efficient solutions, mechanical harvest/auto-harvest that is based on object detection and robotic harvester becomes an urgent need. Within the auto-harvest system, robust few-shot object detection model is one of the bottlenecks, since the system is required to deal with new vegetable/fruit categories and the collection of large-scale annotated datasets for all the novel categories is expensive. There are many few-shot object detection models that were developed by the community. Yet whether they could be employed directly for real life agricultural applications is still questionable, as there is a context-gap between the commonly used training datasets and the images collected in real life agricultural scenarios. To this end, in this study, we present a novel cucumber dataset and propose two data augmentation strategies that help to bridge the context-gap. Experimental results show that 1) the state-of-the-art few-shot object detection model performs poorly on the novel 'cucumber' category;and 2) the proposed augmentation strategies outperform the commonly used ones.

15.
Canadian Liver Journal ; 4(2):110-112, 2021.
Article in English | EMBASE | ID: covidwho-1256335
16.
Preprint in English | PubMed | ID: ppcovidwho-8946

ABSTRACT

COVID-19 patients commonly present with neurological signs of central nervous system (CNS) and/or peripheral nervous system dysfunction. However, which neural cells are permissive to infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been controversial. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively permissive to SARS-CoV-2 infection both in vitro and upon transplantation in vivo, and that SARS-CoV-2 infection triggers a DA neuron inflammatory and cellular senescence response. A high-throughput screen in hPSC-derived DA neurons identified several FDA approved drugs, including riluzole, metformin, and imatinib, that can rescue the cellular senescence phenotype and prevent SARS-CoV-2 infection. RNA-seq analysis of human ventral midbrain tissue from COVID-19 patients, using formalin-fixed paraffin-embedded autopsy samples, confirmed the induction of an inflammatory and cellular senescence signature and identified low levels of SARS-CoV-2 transcripts. Our findings demonstrate that hPSC-derived DA neurons can serve as a disease model to study neuronal susceptibility to SARS-CoV-2 and to identify candidate neuroprotective drugs for COVID-19 patients. The susceptibility of hPSC-derived DA neurons to SARS-CoV-2 and the observed inflammatory and senescence transcriptional responses suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.

17.
Chinese Journal of Laboratory Medicine ; 44(3):239-245, 2021.
Article in Chinese | Scopus | ID: covidwho-1167786
18.
Canadian Liver Journal ; 4(1):16-22, 2021.
Article in English | EMBASE | ID: covidwho-1161121

ABSTRACT

BACKGROUND: Since December 2019, there are 30 million confirmed cases of a novel coronavirus disease (COVID-19) secondary to severe acute respiratory syndrome coronavirus 2. As of 2020, hepatitis B virus (HBV) affects more than 200 million people worldwide. Both are caused by viral agents. The short-term mortality rate from COVID-19 is much higher than that of HBV. OBJECTIVE: We sought to understand the impact of HBV coinfection on hospitalized patients with COVID-19. SEARCH METHODS: Searches of the literature were conducted in the PubMed, Cochrane Library, and Embase electronic databases. SELECTION CRITERIA: We included cohort studies and randomized studies with information on rates of mortality and intensive care unit (ICU) admission from individuals coinfected by HBV and COVID-19. DATA COLLECTION AND ANALYSIS: Data from six cohort studies with 2,015 patients were collected between January and April 2020, and the results were analyzed by meta-analysis. MAIN RESULTS: HBV coinfection did not lead to increased mortality or ICU admission rates among individuals hospitalized for COVID-19 (risk ratio 0.79, 95% CI 0.333–1.83, N = 2,015;adjusted OR = 0.79, 95% CI 0.31–1.98). During their hospital stay, coinfected patients did not appear to have an increased hospital length of stay or risk of hepatitis B reactivation. CONCLUSIONS: This systematic review and meta-analysis provides support that HBV is not a significant risk factor for serious adverse outcomes among patients hospitalized for COVID-19 infection.

19.
Chinese Journal of Clinical Infectious Diseases ; 13(1):9-15, 2020.
Article in Chinese | Scopus | ID: covidwho-1143641

ABSTRACT

Objective: To compare the efficacy of the combination of abidol, lopinavir/ritonavir plus recombinant interferon α-2b (rIFNα-2b) and the combination of lopinavir/ritonavir plus rIFNα-2b for patients with COVID-19 in Zhejiang province. Methods: A multicenter prospective study was carried out to compare the efficacy of triple combination antiviral therapy and dual combination antiviral therapy in 15 medical institutions of Zhejiang province during January 22 to February 16, 2020. All patients were treated with rIFNα-2b (5 million U, 2 times/d) aerosol inhalation, in addition 196 patients were treated with abidol (200 mg, 3 times/d) + lopinavir/ritonavir (2 tablets, 1 time/12 h) (triple combination group) and 41 patients were treated with lopinavir/ritonavir (2 tablets, 1 time/12 h) (dual combination group). The patients who received triple combination antiviral therapy were further divided into three subgroups: <48 h, 3-5 d and >5 d according the time from the symptom onset to medication starting. The therapeutic efficacy was compared between triple combination group and dual combination group, and compared among 3 subgroups of patients receiving triple combination antiviral therapy. SPSS 17.0 software was used to analyze the data. Results: The virus nucleic acid-negative conversion time in respiratory tract specimens was (12.2±4.7) d in the triple combination group, which was shorter than that in the dual combination group [(15.0±5.0) d] (t=6.159, P<0.01). The length of hospital stay in the triple combination group [12.0 (9.0, 17.0) d] was also shorter than that in the dual combination group [15.0 (10.0, 18.0) d] (H=2.073, P<0.05). Compared with the antiviral treatment which was started within after the symptom onset of in the triple combination group, the time from the symptom onset to the viral negative conversion was 13.0 (10.0, 17.0), 17.0 (13.0, 22.0) and 21.0 (18.0, 24.0) d in subgroups of 48 h, 3-5 d and >5 d, respectively (Z=32.983, P<0.01), while the time from antiviral therapy to viral negative conversion was (11.8±3.9), (13.5±5.1) and (11.2±4.3) d, respectively(Z=6.722, P<0.05). Conclusions: The triple combination antiviral therapy of abidol, lopinavir/litonavir and rIFNα-2b shows shorter viral shedding time and shorter hospitalization time, compared with the dual combination antiviral therapy;and the earlier starting triple combination antiviral therapy will result in better antiviral efficacy. Copyright © 2020 by the Chinese Medical Association.

20.
ACM Int. Conf. Proc. Ser. ; : 214-219, 2020.
Article in English | Scopus | ID: covidwho-1133350

ABSTRACT

This article first sorts out the specific measures taken by various subdivision fields of the Chinese education industry to actively respond to the call for "suspended class, ongoing learning"after the outbreak of COVID-19. Among them, online education is facing a huge challenge and an unprecedented development opportunity as a new teaching method. Before the submission, most of the research in the academia favored macro-policy recommendations. On this basis, this paper focuses on the impact of the epidemic on structural changes in education, online teaching models, comparison of online and offline training between China and foreign countries, and the future development trend of online education. With a view to providing suggestions for relevant departments and education practitioners. © 2020 ACM.

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