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1.
Chinese Journal of School Health ; 43(3):413-416, 2022.
Article in Chinese | GIM | ID: covidwho-1865667

ABSTRACT

Objective: To understand social anxiety and relevant factors among graduate students under the normalization stage of COVID-19 epidemic prevention and control.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329930

ABSTRACT

Background: Infectious illness outbreaks, particularly the corona-virus 19 pandemics in recent years, have wreaked havoc on human society, and the growing number of infected patients has put a strain on medical facilities. It’s necessary to forecast early warning signals of potential outbreaks of Covid-19, which would facilitate the health ministry to take some suitable control measures timely to prevent or slow the spread of Covid-19. However, since the intricacy of Covid-19 transmission, which connects biological and social systems, it is a difficult task to predict outbreaks of Covid-19 epidemics timely. Results: : In this work, we developed a new model-free approach, called, the landscape network entropy based on Auto-Reservoir Neural Network (ARNN-LNE), for quantitative analysis of Covid-19 propagation, by mining dynamic information from regional networks and short-term high-dimensional time-series data. Through this approach, we successfully identified the early warning signals in six nations or areas based on historical data of Covid-19 infections. Conclusion: Based on the newly published data on new Covid-19 disease, the ARNN-LNE method can give early warning signals for the outbreak of Covid-19. It’s worth noting that ARNN-LNE only relies on small samples data, Thus, it has great application potential for monitoring outbreaks of infectious diseases.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324805

ABSTRACT

The outbreak of Coronavirus Disease 2019 (COVID-19) is getting worse every day all over the world. The present study aimed to review the epidemiological characteristics of patients infected with COVID-19 in Shenzhen city, a super megacity of China, to provide some references for fighting to the coronavirus. We collected data of 417 patients with laboratory-confirmed COVID-19 of Shenzhen through March 7 th , 2020. The epidemiological characteristics of the patients were analyzed. Besides, we collected the governmental measures of Shenzhen city, and the the dynamic changes of the epidemic outbreak. Governmental strategies such as early detection, early hospitalization and popular science etc. are effective for the prevention and control of the epidemic. Nearly 80% confirmed patients with COVID-19 in Shenzhen were in normal or mild conditions, and the mortality was less than 1%. Age, gender, exposure to source of transmission within 14 days and basic diseases are major risk factors for severe patients. Patients in characters of elder, male, with exposure of Wuhan and carried basic diseases had higher risk to be in severe condition (P<0.01;P<0.001). There were 368 patients discharged from hospital by the end of March 7 th , 2020. Patients in severe conditions took more time from onset to discharge (P<0.001), so as those elder one (P<0.001) or who carried basic diseases (P<0.01). The differences of epidemiological characteristics between children and the elderly are still not clear. The nucleic acid test of some discharged patients returned to positive again, and the potential mechanisms need to be further explored. In conclusion, timely administrative intervention is necessary for prevention and control of the COVID-19 outbreak. Patients in characters of elder, male and carried basic diseases worthy more attention. The management of discharged patients, especially the investigation of the recurrence of positive SARS-CoV-2 RNA will be the focus on for the next step. Authors Bo Yuan and Ya-Wen An contributed equally to this work.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-311936

ABSTRACT

The COVID-19 outbreak was announced as a global pandemic by the World Health Organisation in March 2020 and has affected a growing number of people in the past few weeks. In this context, advanced artificial intelligence techniques are brought to the fore in responding to fight against and reduce the impact of this global health crisis. In this study, we focus on developing some potential use-cases of intelligent speech analysis for COVID-19 diagnosed patients. In particular, by analysing speech recordings from these patients, we construct audio-only-based models to automatically categorise the health state of patients from four aspects, including the severity of illness, sleep quality, fatigue, and anxiety. For this purpose, two established acoustic feature sets and support vector machines are utilised. Our experiments show that an average accuracy of .69 obtained estimating the severity of illness, which is derived from the number of days in hospitalisation. We hope that this study can foster an extremely fast, low-cost, and convenient way to automatically detect the COVID-19 disease.

5.
Preprint in English | bioRxiv | ID: ppbiorxiv-470392

ABSTRACT

The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LY-CoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.

6.
Preprint in English | bioRxiv | ID: ppbiorxiv-448958

ABSTRACT

The spike (S) protein receptor-binding domain (RBD) of SARS-CoV-2 is an attractive target for COVID-19 vaccine developments, which naturally exists in a trimeric form. Here, guided by structural and computational analyses, we present a mutation-integrated trimeric form of RBD (mutI tri-RBD) as a broadly protective vaccine candidate, in which three RBDs were individually grafted from three different circulating SARS-CoV-2 strains including the prototype, Beta (B.1.351) and Kappa (B.1.617). The three RBDs were then connected end-to-end and co-assembled to possibly mimic the native trimeric arrangements in the natural S protein trimer. The recombinant expression of the mutI tri-RBD, as well as the homo-tri-RBD where the three RBDs were all truncated from the prototype strain, by mammalian cell exhibited correct folding, strong bio-activities, and high stability. The immunization of both the mutI tri-RBD and homo-tri-RBD plus aluminum adjuvant induced high levels of specific IgG and neutralizing antibodies against the SARS-CoV-2 prototype strain in mice. Notably, regarding to the "immune-escape" Beta (B.1.351) variant, mutI tri-RBD elicited significantly higher neutralizing antibody titers than homo-tri-RBD. Furthermore, due to harboring the immune-resistant mutations as well as the evolutionarily convergent hotspots, the designed mutI tri-RBD also induced strong broadly neutralizing activities against various SARS-CoV-2 variants, especially the variants partially resistant to homo-tri-RBD. Homo-tri-RBD has been approved by the China National Medical Products Administration to enter clinical trial (No. NCT04869592), and the superior broad neutralization performances against SARS-CoV-2 support the mutI tri-RBD as a more promising vaccine candidate for further clinical developments.

7.
Molecules ; 26(1):57, 2021.
Article in English | ScienceDirect | ID: covidwho-984996

ABSTRACT

The novel coronavirus disease (2019-nCoV) has been affecting global health since the end of 2019, and there is no sign that the epidemic is abating. Targeting the interaction between the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptor is a promising therapeutic strategy. In this study, surface plasmon resonance (SPR) was used as the primary method to screen a library of 960 compounds. A compound 02B05 (demethylzeylasteral, CAS number: 107316-88-1) that had high affinities for S-RBD and ACE2 was discovered, and binding affinities (KD, μM) of 02B05-ACE2 and 02B05-S-RBD were 1.736 and 1.039 μM, respectively. The results of a competition experiment showed that 02B05 could effectively block the binding of S-RBD to ACE2 protein. Furthermore, pseudovirus infection assay revealed that 02B05 could inhibit entry of SARS-CoV-2 pseudovirus into 293T cells to a certain extent at nontoxic concentration. The compoundobtained in this study serve as references for the design of drugs which have potential in the treatment of COVID-19 and can thus accelerate the process of developing effective drugs to treat SARS-CoV-2 infections.

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