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1.
Int J Clin Health Psychol ; : 100327, 2022 Jul 25.
Article in English | MEDLINE | ID: covidwho-1956164

ABSTRACT

Background/Objective: This study aimed to examine associations of the impact of COVID-19 pandemic on family life with emotional and behavioral health among preschool children. Methods: A longitudinal study including 1595 preschool children aged 3-6 years and their families was conducted in Anhui Province. The linear regression was applied to examine associations between the impact of COVID-19 pandemic on family life and emotional and behavioral health. Results: Results of the multivariable linear regression indicated that the severe impact of COVID-19 pandemic on family life was significantly associated with more sleep problems, poor dietary behavior habits, more anxiety symptoms, and more problematic behaviors; and these effects exhibited gender and age differences. Conclusions: The severe impact of COVID-19 pandemic on family life significantly increased the risk for exacerbated emotional and behavioral health among preschool children. It is considered vital to identify risk factors for vulnerable families and then to implement precise interventions when necessary for emotional and behavioral health of children in these families.

2.
Front Med (Lausanne) ; 9: 854788, 2022.
Article in English | MEDLINE | ID: covidwho-1952377

ABSTRACT

Objective: The long-term impact of COVID-19 on patient health has been a recent focus. This study aims to determine the persistent symptoms and psychological conditions of patients hospitalized with COVID-19 15 months after onset, that patients first developed symptoms. The potential risk factors were also explored. Methods: A cohort of COVID-19 patients discharged from February 20, 2020 to March 31, 2020 was recruited. Follow-ups were conducted using validated questionnaires and psychological screening scales at 15 months after onset to evaluate the patients' health status. The risk factors for long-term health impacts and their associations with disease severity was analyzed. Findings: 534 COVID-19 patients were enrolled. The median age of the patients was 62.0 years old (IQR 52.0-70.0) and 295 were female (55.2%). The median time from onset to follow-up was 460.0 (451.0-467.0) days. Sleep disturbance (18.5%, 99/534) and fatigue (17.2%, 92/534) were the most common persistent symptoms. 6.4% (34/534) of the patients had depression, 9.2% (49/534) were anxious, 13.0% (70/534) had insomnia and 4.7% (25/534) suffered from post-traumatic stress disorder (PTSD). Multivariate adjusted logistic regression analysis showed that glucocorticoid use during hospitalization (OR 3.58, 95% CI 1.12-11.44) was significantly associated with an increased risk of fatigue. The OR values for anxiety and sleep disorders were 2.36 (95% CI 1.07-5.20) and 2.16 (95% CI 1.13-4.14) in females to males. The OR value of PTSD was 25.6 (95% CI 3.3-198.4) in patients with persistent symptoms to those without persistent symptoms. No significant associations were observed between fatigue syndrome or adverse mental outcomes and disease severity. Conclusions: 15-month follow-up in this study demonstrated the need of extended rehabilitation intervention for complete recovery in COVID-19 patients.

3.
Journal of Translational Critical Care Medicine ; 3(1):1-4, 2021.
Article in English | EuropePMC | ID: covidwho-1824143

ABSTRACT

Background and Objectives: To explore the superiority of flipping-classroom lended learning in which the stay-home e-learning and traditional internship complements each other in resident training of endcorinology during coronavirus disease 2019 restriction period. Materials and Methods: A total of 44 residents were randomized as the study population. In the endocrine-rotation training, we reformed the clinical learning by unified online-teaching led by teachers' combination with individual guidance by residents. Moreover, the final implementation assessment was conducted by standard double-blind examinations. Results: After 4–8 weeks training, the 44 residents were assessed for clinical skills from six dimensions, including medical history collection, physical examination, history report and inpatient record writing, case analysis, and overviewing capability. Compared with the mean scores of 68 residents rotated in internal medicine in 2019, the mean scores on physical examination, inpatient record writing, and overviewing capability in 2020 group were higher with significance ([85.72 ± 8.33] vs.[79.22 ± 10.12], P = 0.0006), ([90.28 ± 10.70] vs. [81.82 ± 8.03], P < 0.0001), ([80.31 ± 8.70] vs. [73.04 ± 12.74], P = 0.0012), whereas scores on skills of medical history collection and history report were slightly lower ([82.11 ± 9.02] vs. [85.06 ± 7.23], P = 0.0586), ([79.30 ± 8.17] vs. [83.21 ± 5.01], P = 0.0022), while scores on case analysis did not show huge gap but with polarized performance in 2020 group ([74.38 ± 10.29] vs. [78.13 ± 8.53], P = 0.0386). Conclusions: Providing the novel pattern of unified online-teaching combined with individual-guidance at the bedside to the front-line residents can reduce the risk of cluster epidemics and effectively ensure the training effect on them but still with shortcomings. The future online teaching reform is better for focus more on how to make up for or reduce the actual problem of disconnection between theory and practice in the process of online clinical skills training for residents and teachers.

4.
Hum Vaccin Immunother ; 18(1): 2029257, 2022 12 31.
Article in English | MEDLINE | ID: covidwho-1692309

ABSTRACT

This study is conducted to explore the association between health behaviors and the COVID-19 vaccination based on the risk compensation concept among health-care workers in Taizhou, China. We conducted a self-administered online survey to estimate the health behaviors among the staff in a tertiary hospital in Taizhou, China, from May 18 to 21 May 2021. A total of 592 out of 660 subjects (89.7%) responded to the questionnaire after receiving an e-poster on WeChat. Subjects who had been inoculated with the COVID-19 vaccine were asked to mention the differences in their health behaviors before and after the vaccination. The results showed that there were no statistical differences in health behaviors between vaccinated and unvaccinated groups, except in terms of the type of gloves they used (62.8% in the vaccinated group and 49.2% in the unvaccinated group, p = .048). Subjects who received earlier COVID-19 vaccinations exhibited better health behaviors (22.40% increased for duration of wearing masks (P = .007), 25.40% increased for times of washing hands (P = .01), and 20.90% increased for times of wearing gloves (P = .01)). Subjects also revealed better health behaviors (washing hands, wearing gloves, and wearing masks) after vaccination compared to that before. In conclusion, concept of risk compensation was not applied in our findings. The health behaviors did not reduce after the COVID-19 vaccination, which even may improve health behaviors among health-care workers in the hospital setting.


Subject(s)
COVID-19 Vaccines , COVID-19 , COVID-19/prevention & control , China/epidemiology , Health Behavior , Health Personnel , Humans , SARS-CoV-2 , Vaccination
5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-322245

ABSTRACT

Background: Much remains unknown about COVID-19 onset and rehabilitation's symptomatic features, especially the long-term health consequences of patients with COVID-19 who have been discharged from the hospital. Methods: In this cohort study, we collected the first pandemic data of hospitalized patients in Wuhan from February 20 to March 31, 2020. All patients completed a 3-month follow-up after discharge. We carefully analyzed the detailed symptomatic characteristics of severe COVID-19 at illness onset and three months after discharge, compared it with non-severe patients, and used multiple logistic regression to determine potential symptomatic risk factors for severe COVID-19. Results: A total of 932 hospitalized patients with COVID-19 were enrolled, including 52 severe cases and 880 non-severe cases. Fever (60%), cough (50.8%), and fatigue (36.4%) were the most common symptoms, followed by anorexia (21.8%) and dyspnea (19.2%). The median duration of fever was seven days, which was characterized by persistent low fever. The median duration of cough was 17 days, characterized by dry cough without sputum. Most dyspnea occurred on the fourth day after symptom onset, with a median duration of 16 days. The incidences of taste loss and olfactory disturbance were only 6.2% and 3.1%, respectively. Multivariate logistic regression analysis showed that age over 65 years old (OR 6.52, 95% CI 3.27-13.02, P <0.0001), male sex (3.71, 1.90-7.26, P = 0.0001), fever lasting for more than five days (1.90, 1.00-3.62, P =0.0498), anorexia at onset (2.61, 1.26-5.40, P =0.0096), and modified Medical Research Council level above grade 2 when dyspnea occurred (14.19,7.01-28.71, P <0.0001) were symptomatic risk factors for severe COVID-19. Three months after discharge from the hospital, 6.2% of patients still cough, 7.2% of patients still dyspnea, and 1.8% still fatigue, and 1.5% of patients had olfactory or taste disorders. Conclusions: COVID-19 caused clusters of symptoms, with multiple systems involved. Specific symptomatic features at the onset of illness have predictive value for severe COVID-19. Persistent legacy symptoms are more frequent in severe COVID-19 patients.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322243

ABSTRACT

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE) and AUC achieved by our method are 91.79%, 93.05%, 89.95% and 96.35%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312698

ABSTRACT

Background: No specific therapeutic agents or vaccines are available for the treatment of Coronavirus disease 2019 (Covid-19) yet. In this study, we aimed to assess the efficacy of high dose ulinastatin for patients with Covid-19. Methods: Twelve patients hospitalized with confirmed SARS-CoV-2 infection were treated with high dose of ulinastatin beyond standard care. The changes of clinical manifestations, laboratory examinations and chest images were retrospectively analyzed. Results: A total of 10 patients with severe Covid-19 and 2 patients with moderate Covid-19 received ulinastatin treatment. The average age of the patients was 68.0 ± 11.9 years, ranging from 48 to 87 years. Nine of 12 patients (75.0%) had one or more comorbidities. The most common symptoms on admission were fever (8/12, 66.7%), cough (5/12, 41.7%) and dyspnea (5/12, 41.7%). The percentage of lymphocytes was decreased in 41.7% of patients (5/12), and 58.3% of patients (7/12) had elevated hypersensitive C-reactive protein (CRP) levels (mean, 49.70 ± 77.70 mg/L). The white blood cell levels and the percentage of lymphocytes returned to normal in all of the patients, and CRP decreased significantly and returned to normal in 83.3% of patients (10/12;mean, 6.87 ± 6.63 mg/L) on the seventh day after ulinastatin treatment. Clinical symptoms were relieved synchronously. The peripheral oxygen saturation improved and 66.7% of the patients (8/12) did not need further oxygen therapy seven days after ulinastatin treatment. No patients required intensive care unit admission or mechanical ventilation. All patients revealed different degrees of absorption of pulmonary lesions after treatment. No obvious adverse events were observed. Conclusions: Our preliminary data revealed that high dose of ulinastatin treatment was safe and showed a potential beneficial effect for patients with Covid-19.

8.
Experimental & Therapeutic Medicine ; 23(2):N.PAG-N.PAG, 2022.
Article in English | Academic Search Complete | ID: covidwho-1678877

ABSTRACT

Currently, there are no specific therapeutic agents available for the treatment of coronavirus disease 2019 (Covid-19). The present study aimed to assess the efficacy of high-dose ulinastatin for the treatment of patients with Covid-19. A total of 12 patients hospitalized with confirmed severe acute respiratory syndrome coronavirus 2 infection were treated with a high dose of ulinastatin alongside standard care. Changes in clinical manifestations, laboratory examinations and chest images were retrospectively analyzed. A total of 10 patients with severe Covid-19 and two patients with moderate Covid-19 received ulinastatin treatment. The average age of the patients was 68.0±11.9 years (age range, 48-87 years). In total, nine of the 12 patients (75.0%) had one or more comorbidities. The most common symptoms on admission were fever (8/12, 66.7%), cough (5/12, 41.7%) and dyspnea (5/12, 41.7%). The percentage of lymphocytes was decreased in 41.7% of patients (5/12) and 58.3% of patients (7/12) had elevated hypersensitive C-reactive protein (CRP) levels (mean, 49.70±77.70 mg/l). The white blood cell levels and the percentage of lymphocytes returned to normal in all of the patients, and CRP was significantly decreased and returned to normal in 83.3% of patients (10/12;mean, 6.87±6.63 mg/l) on day 7 after ulinastatin treatment. Clinical symptoms were relieved synchronously. The peripheral oxygen saturation improved and 66.7% of the patients (8/12) did not require further oxygen therapy 7 days after ulinastatin treatment. No patients required intensive care unit admission or mechanical ventilation. All patients revealed different degrees of absorption of pulmonary lesions after treatment. Compared with the standard care group, ulinastatin treatment significantly prevented illness deterioration. In conclusion, these preliminary data revealed that high-dose ulinastatin treatment was safe and exhibited a potential beneficial effect for patients with Covid-19. [ FROM AUTHOR] Copyright of Experimental & Therapeutic Medicine is the property of Spandidos Publications UK Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

9.
Exp Ther Med ; 23(2): 121, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1594196

ABSTRACT

Currently, there are no specific therapeutic agents available for the treatment of coronavirus disease 2019 (Covid-19). The present study aimed to assess the efficacy of high-dose ulinastatin for the treatment of patients with Covid-19. A total of 12 patients hospitalized with confirmed severe acute respiratory syndrome coronavirus 2 infection were treated with a high dose of ulinastatin alongside standard care. Changes in clinical manifestations, laboratory examinations and chest images were retrospectively analyzed. A total of 10 patients with severe Covid-19 and two patients with moderate Covid-19 received ulinastatin treatment. The average age of the patients was 68.0±11.9 years (age range, 48-87 years). In total, nine of the 12 patients (75.0%) had one or more comorbidities. The most common symptoms on admission were fever (8/12, 66.7%), cough (5/12, 41.7%) and dyspnea (5/12, 41.7%). The percentage of lymphocytes was decreased in 41.7% of patients (5/12) and 58.3% of patients (7/12) had elevated hypersensitive C-reactive protein (CRP) levels (mean, 49.70±77.70 mg/l). The white blood cell levels and the percentage of lymphocytes returned to normal in all of the patients, and CRP was significantly decreased and returned to normal in 83.3% of patients (10/12; mean, 6.87±6.63 mg/l) on day 7 after ulinastatin treatment. Clinical symptoms were relieved synchronously. The peripheral oxygen saturation improved and 66.7% of the patients (8/12) did not require further oxygen therapy 7 days after ulinastatin treatment. No patients required intensive care unit admission or mechanical ventilation. All patients revealed different degrees of absorption of pulmonary lesions after treatment. Compared with the standard care group, ulinastatin treatment significantly prevented illness deterioration. In conclusion, these preliminary data revealed that high-dose ulinastatin treatment was safe and exhibited a potential beneficial effect for patients with Covid-19.

10.
Nat Cell Biol ; 23(12): 1314-1328, 2021 12.
Article in English | MEDLINE | ID: covidwho-1559292

ABSTRACT

The lung is the primary organ targeted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), making respiratory failure a leading coronavirus disease 2019 (COVID-19)-related mortality. However, our cellular and molecular understanding of how SARS-CoV-2 infection drives lung pathology is limited. Here we constructed multi-omics and single-nucleus transcriptomic atlases of the lungs of patients with COVID-19, which integrate histological, transcriptomic and proteomic analyses. Our work reveals the molecular basis of pathological hallmarks associated with SARS-CoV-2 infection in different lung and infiltrating immune cell populations. We report molecular fingerprints of hyperinflammation, alveolar epithelial cell exhaustion, vascular changes and fibrosis, and identify parenchymal lung senescence as a molecular state of COVID-19 pathology. Moreover, our data suggest that FOXO3A suppression is a potential mechanism underlying the fibroblast-to-myofibroblast transition associated with COVID-19 pulmonary fibrosis. Our work depicts a comprehensive cellular and molecular atlas of the lungs of patients with COVID-19 and provides insights into SARS-CoV-2-related pulmonary injury, facilitating the identification of biomarkers and development of symptomatic treatments.


Subject(s)
COVID-19/genetics , Lung/metabolism , Transcriptome/genetics , Alveolar Epithelial Cells/metabolism , Alveolar Epithelial Cells/pathology , Alveolar Epithelial Cells/virology , COVID-19/metabolism , Fibrosis/metabolism , Fibrosis/pathology , Fibrosis/virology , Humans , Lung/pathology , Lung/virology , Proteomics/methods , SARS-CoV-2/pathogenicity
11.
BMC Med Imaging ; 21(1): 154, 2021 10 21.
Article in English | MEDLINE | ID: covidwho-1546762

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) causes tens of million infection world-wide. Many machine learning methods have been proposed for the computer-aided diagnosis between COVID-19 and community-acquired pneumonia (CAP) from chest computed tomography (CT) images. Most of these methods utilized the location-specific handcrafted features based on the segmentation results to improve the diagnose performance. However, the prerequisite segmentation step is time-consuming and needs the intervention by lots of expert radiologists, which cannot be achieved in the areas with limited medical resources. METHODS: We propose a generative adversarial feature completion and diagnosis network (GACDN) that simultaneously generates handcrafted features by radiomic counterparts and makes accurate diagnoses based on both original and generated features. Specifically, we first calculate the radiomic features from the CT images. Then, in order to fast obtain the location-specific handcrafted features, we use the proposed GACDN to generate them by its corresponding radiomic features. Finally, we use both radiomic features and location-specific handcrafted features for COVID-19 diagnosis. RESULTS: For the performance of our generated location-specific handcrafted features, the results of four basic classifiers show that it has an average of 3.21% increase in diagnoses accuracy. Besides, the experimental results on COVID-19 dataset show that our proposed method achieved superior performance in COVID-19 vs. community acquired pneumonia (CAP) classification compared with the state-of-the-art methods. CONCLUSIONS: The proposed method significantly improves the diagnoses accuracy of COVID-19 vs. CAP in the condition of incomplete location-specific handcrafted features. Besides, it is also applicable in some regions lacking of expert radiologists and high-performance computing resources.


Subject(s)
COVID-19/diagnosis , Deep Learning , Diagnosis, Computer-Assisted/methods , Machine Learning , SARS-CoV-2 , Tomography, X-Ray Computed/methods , COVID-19/epidemiology , Humans
12.
Elife ; 102021 08 20.
Article in English | MEDLINE | ID: covidwho-1368023

ABSTRACT

SARS-CoV-2 has been spreading around the world for the past year. Recently, several variants such as B.1.1.7 (alpha), B.1.351 (beta), and P.1 (gamma), which share a key mutation N501Y on the receptor-binding domain (RBD), appear to be more infectious to humans. To understand the underlying mechanism, we used a cell surface-binding assay, a kinetics study, a single-molecule technique, and a computational method to investigate the interaction between these RBD (mutations) and ACE2. Remarkably, RBD with the N501Y mutation exhibited a considerably stronger interaction, with a faster association rate and a slower dissociation rate. Atomic force microscopy (AFM)-based single-molecule force microscopy (SMFS) consistently quantified the interaction strength of RBD with the mutation as having increased binding probability and requiring increased unbinding force. Molecular dynamics simulations of RBD-ACE2 complexes indicated that the N501Y mutation introduced additional π-π and π-cation interactions that could explain the changes observed by force microscopy. Taken together, these results suggest that the reinforced RBD-ACE2 interaction that results from the N501Y mutation in the RBD should play an essential role in the higher rate of transmission of SARS-CoV-2 variants, and that future mutations in the RBD of the virus should be under surveillance.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Mutation , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Binding Sites , Cell Line , Humans , Protein Binding , Spike Glycoprotein, Coronavirus/genetics
13.
Journal of Physics: Conference Series ; 1931(1), 2021.
Article in English | ProQuest Central | ID: covidwho-1280023

ABSTRACT

The employment situation in civil aviation has become more severe this year due to the adverse effects of the COVID-19 epidemic. The online teaching of employment guidance courses can promote high-quality employment for graduates, but also poses new challenges for teachers and students. For college students enrolled in 2018 majoring in civil aviation, the teachers in the Civil Aviation Management Institute of China accomplished the employment guidance course, adopting a teaching method combining online teaching with offline guidance, and applying the Deming cycle to continuously improve the course quality. To facilitate better employment of civil aviation graduates under the epidemic, this paper suggests that it is necessary to establish an employment guidance and service system, improve the comprehensive quality of graduates, promote cooperation and mutual assistance between schools and employers, and guide graduates to start their businesses or further study rationally.

14.
J Dig Dis ; 22(5): 271-281, 2021 May.
Article in English | MEDLINE | ID: covidwho-1203819

ABSTRACT

OBJECTIVE: To discern the symptomatic features of coronavirus disease 2019 (COVID-19) and to evaluate the severity and prognosis of the disease. METHODS: In this retrospective cohort study, 932 hospitalized patients with COVID-19 in Wuhan were enrolled, including 52 severe and 880 non-severe cases. All patients were followed up for 3 months after discharge. The symptomatic features and follow-up data of the patients in both groups were analyzed and compared. RESULTS: Of the 932 patients, fever (60.0%), cough (50.8%) and fatigue (36.4%) were the most common symptoms. In total, 32.7% of the severe cases presented with gastrointestinal symptoms at disease onset, including anorexia, nausea, vomiting or diarrhea, which was significantly higher than that of the non-severe group (P = 0.0015). The incidence of olfactory disturbance and dysgeusia was only 3.1% and 6.2%, respectively. After adjusting for age and sex, multivariate regression analysis showed that fever lasting for over 5 days (odds ratio [OR] 1.90, 95% confidence interval [CI] 1.00-3.62, P = 0.0498), anorexia at onset (OR 2.61, 95% CI 1.26-5.40, P = 0.0096), and modified Medical Research Council level above grade 2 when dyspnea occurred (OR 14.19, 95% CI 7.01-28.71, P < 0.0001) were symptomatic risk factors for severe COVID-19. During the follow-up, cough (6.2%), dyspnea (7.2%), fatigue (1.8%), olfactory disturbance and dysgeusia (1.5%) were the significant remaining symptoms. CONCLUSIONS: COVID-19 causes clusters of symptoms with multiple systems involved. Certain symptomatic characteristics have predictive value for severe COVID-19. Short-term follow-up data reveal that most patients have a good prognosis.


Subject(s)
COVID-19/diagnosis , SARS-CoV-2 , Adult , Aged , Aged, 80 and over , COVID-19/complications , Female , Hospitalization , Humans , Male , Middle Aged , Prognosis , Retrospective Studies , Severity of Illness Index
15.
Front Med (Lausanne) ; 8: 604392, 2021.
Article in English | MEDLINE | ID: covidwho-1170090

ABSTRACT

In the COVID-19 outbreak year 2020, a consensus was reached on the fact that SARS-CoV-2 spreads through aerosols. However, finding an efficient method to detect viruses in aerosols to monitor the risk of similar infections and enact effective control remains a great challenge. Our study aimed to build a swirling aerosol collection (SAC) device to collect viral particles in exhaled breath and subsequently detect SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR). Laboratory tests of the SAC device using aerosolized SARS-CoV-2 pseudovirus indicated that the SAC device can produce a positive result in only 10 s, with a collection distance to the source of 10 cm in a biosafety chamber, when the release rate of the pseudovirus source was 1,000,000 copies/h. Subsequent clinical trials of the device showed three positives and 14 negatives out of 27 patients in agreement with pharyngeal swabs, and 10 patients obtained opposite results, while no positive results were found in a healthy control group (n = 12). Based on standard curve calibration, several thousand viruses per minute were observed in the tested exhalations. Furthermore, referring to the average tidal volume data of adults, it was estimated that an exhaled SARS-CoV-2 concentration of approximately one copy/mL is detectable for COVID-19 patients. This study validates the original concept of breath detection of SARS-CoV-2 using SAC combined with RT-PCR.

16.
J Biomed Inform ; 117: 103736, 2021 05.
Article in English | MEDLINE | ID: covidwho-1131456

ABSTRACT

The recent outbreak of COVID-19 has infected millions of people around the world, which is leading to the global emergency. In the event of the virus outbreak, it is crucial to get the carriers of the virus timely and precisely, then the animal origins can be isolated for further infection. Traditional identifications rely on fields and laboratory researches that lag the responses to emerging epidemic prevention. With the development of machine learning, the efficiency of predicting the viral hosts has been demonstrated by recent researchers. However, the problems of the limited annotated virus data and imbalanced hosts information restrict these approaches to obtain a better result. To assure the high reliability of predicting the animal origins on COVID-19, we extend transfer learning and ensemble learning to present a hybrid transfer learning model. When predicting the hosts of newly discovered virus, our model provides a novel solution to utilize the related virus domain as auxiliary to help building a robust model for target virus domain. The simulation results on several UCI benchmarks and viral genome datasets demonstrate that our model outperforms the general classical methods under the condition of limited target training sets and class-imbalance problems. By setting the coronavirus as target domain and other related virus as source domain, the feasibility of our approach is evaluated. Finally, we show the animal reservoirs prediction of the COVID-19 for further analysing.


Subject(s)
COVID-19 , Disease Reservoirs , Machine Learning , Animals , Disease Outbreaks , Humans , Reproducibility of Results , SARS-CoV-2
17.
SciFinder; 2020.
Preprint | SciFinder | ID: ppcovidwho-5005

ABSTRACT

A review. Based on the clin. manifestations of COVID-19, professor XUE Bo-Shou combined with the academic thoughts and clin. experience of Mr. PU Fu-zhou proposed the diagnosis thought and therapeutic method of COVID-19. He thought that COVID-19 was cold and dampness epidemic and the disease location was mainly in the lungs. The treatment should be paid attention to seasonal climate influences and brought the academic medical experience of "typhoid fever" "warm disease" "plague" together and understand thoroughly, selected the best and use them, especially not ignore Treatise on Febrile Disease. The treatment should be attached importance to the etiol. of the disease. At the beginning of the epidemic, we should pay attention to dispel external pathogenic factor and attach importance to the overall treatment, especially strengthening qi and protecting stomach qi.

18.
Sci Bull (Beijing) ; 66(9): 884-888, 2021 May 15.
Article in English | MEDLINE | ID: covidwho-1019467

ABSTRACT

Coronavirus disease-2019 (COVID-19) has become a major global epidemic. Facilitated by HTS2 technology, we evaluated the effects of 578 herbs and all 338 reported anti-COVID-19 TCM formulae on cytokine storm-related signaling pathways, and identified the key targets of the relevant pathways and potential active ingredients in these herbs. This large-scale transcriptional study innovatively combines HTS2 technology with bioinformatics methods and computer-aided drug design. For the first time, it systematically explores the molecular mechanism of TCM in regulating the COVID-19-related cytokine storm, providing an important scientific basis for elucidating the mechanism of action of TCM in treating COVID-19.

19.
J Med Virol ; 93(5): 2857-2866, 2021 05.
Article in English | MEDLINE | ID: covidwho-979852

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is sweeping the world since the end of 2019. The titer change of antibodies against SARS-CoV-2 needs to be further clarified, the clinical and preventive value of antibodies still needs to be further investigated. An enzyme-linked immunosorbent assay (ELISA) was established by coating with SARS-CoV-2 recombinant spike protein and used to detect serum immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies against SARS-CoV-2 in coronavirus disease 2019 patients to evaluate the pattern of changes of antibodies. The specificity of the ELISA for detection SARS-CoV-2 IgM and IgG were 96% (144/150) and 100% (150/150), respectively. The sensitivity of ELISA was 100% (150/150) for IgM, and 99.3% (149/150) for IgG. SARS-CoV-2-SP-IgM and SP-IgG antibodies could be detected on Day 1 of hospitalization in 12.5% patients, and SP-IgM began to decrease after reaching its peak at around 22-28 days, and become negative at Month 3 in 30% patients and negative at Month 7 in 79% of these patients after onset; IgG reached its peak around Day 22-28 and kept at a high level within the longest observation period for 4 months, it dropped very sharply at 7 months. The positive rates of SP-IgM and SP-IgG were higher than those of reverse transcription-polymerase chain reaction on Day 7 and 4. The established indirect ELISA has good specificity and sensitivity. IgM and IgG against SARS-CoV-2 appeared almost simultaneously in the early stage, and the level of IgG antibodies could not maintain a high plateau in the observation period of 7 months. Our data will help develop the diagnosis and vaccine of SARS-CoV-2.


Subject(s)
Antibodies, Viral/blood , COVID-19 Serological Testing/methods , COVID-19/diagnosis , COVID-19/immunology , Enzyme-Linked Immunosorbent Assay/methods , Immunoglobulin G/blood , Immunoglobulin M/blood , Adolescent , Adult , Aged , COVID-19 Nucleic Acid Testing/methods , Humans , Middle Aged , Recombinant Proteins/immunology , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Sensitivity and Specificity , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology , Time Factors , Young Adult
20.
Cell Res ; 31(4): 415-432, 2021 04.
Article in English | MEDLINE | ID: covidwho-759580

ABSTRACT

Aging is a major risk factor for many diseases, especially in highly prevalent cardiopulmonary comorbidities and infectious diseases including Coronavirus Disease 2019 (COVID-19). Resolving cellular and molecular mechanisms associated with aging in higher mammals is therefore urgently needed. Here, we created young and old non-human primate single-nucleus/cell transcriptomic atlases of lung, heart and artery, the top tissues targeted by SARS-CoV-2. Analysis of cell type-specific aging-associated transcriptional changes revealed increased systemic inflammation and compromised virus defense as a hallmark of cardiopulmonary aging. With age, expression of the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) was increased in the pulmonary alveolar epithelial barrier, cardiomyocytes, and vascular endothelial cells. We found that interleukin 7 (IL7) accumulated in aged cardiopulmonary tissues and induced ACE2 expression in human vascular endothelial cells in an NF-κB-dependent manner. Furthermore, treatment with vitamin C blocked IL7-induced ACE2 expression. Altogether, our findings depict the first transcriptomic atlas of the aged primate cardiopulmonary system and provide vital insights into age-linked susceptibility to SARS-CoV-2, suggesting that geroprotective strategies may reduce COVID-19 severity in the elderly.


Subject(s)
Aging , SARS-CoV-2/physiology , Transcriptome , Alveolar Epithelial Cells/cytology , Alveolar Epithelial Cells/metabolism , Alveolar Epithelial Cells/virology , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/metabolism , Animals , Ascorbic Acid/pharmacology , COVID-19/pathology , COVID-19/virology , Cell Line , Endothelial Cells/cytology , Endothelial Cells/metabolism , Endothelial Cells/virology , Humans , Interleukin-7/metabolism , Interleukin-7/pharmacology , Macaca fascicularis , Myocytes, Cardiac/cytology , Myocytes, Cardiac/metabolism , Myocytes, Cardiac/virology , RNA-Seq , SARS-CoV-2/isolation & purification , Single-Cell Analysis , Transcriptome/drug effects
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