ACP-Dnnel: Anti-coronavirus Peptides Prediction based on Deep Neural Network Ensemble Learning (preprint)

Background The ongoing COVID-19 pandemic has caused global economic crisis and dramatic loss of human life. There is an urgent need for safe and efficient anti-coronavirus infection drugs. Anti-coronavirus peptides (ACovPs) can inhibit coronavirus infection. With high-efficiency, low-toxicity, and broad-spectrum inhibitory effects on coronaviruses, they are promising candidates to be developed into a new type of anti-coronavirus drug. Experiment is the traditional way of ACovPs identification, which is less efficient and more expensive. With the accumulation of experimental data on ACovPs, computational prediction provides a cheaper and faster way to find anti-coronavirus peptides candidates.Methods In this study, we integrated several state-of-the-art machine learning methodologies to build nine classification models for the prediction of ACovPs. These models were pretrained using deep neural networks, and the performance of our ensemble model, ACP-Dnnel, was evaluated across three datasets and independent dataset.Results The highest accuracy of ACP-Dnnel reaches 98%, and the MCC value exceeds 0.9. On three different datasets, its average accuracy is 96.33%. After the latest independent data set validation, ACP-Dnnel improved at MCC, Sn and ACC values by 10.1%, 16.4% and 7.3% respectively. It is suggested that ACP-Dnnel can be helpful for the laboratory identification of ACovPs, speeding up the anti-coronavirus peptide drug discovery and development. We constructed the web server of anti-coronavirus peptides prediction and it is available at http://150.158.148.228:5000/.

Beneficial effects of Chinese patent medicine ZhengQi tablet on treating the mild COVID-19 (preprint)

Objectives: This study aimed to assess the effectiveness of a Chinese patent medicine called ZhengQi tablet in the treatment of mild COVID-19 patients. Methods: A prospective cohort trial was carried out in the mobile cabin hospital of City Footprint Hall in Shanghai (ChiCTR2200058693). A total of 800 mild COVID-19 patients were enrolled in this clinical trial and assigned to receive 7 days of treatment with ZhengQi tablet (ZQT group) or TCM placebo (control group) by oral administration per day. The nucleic acid conversion rate of SARS-CoV-2 was the percentage of subjects who got two negative results of Nucleic Acid Amplification Tests (NAATs) at a 24-hour interval out of the total number. The primary clinical indicators included the nucleic acid conversion rate of SARS-CoV-2 and the incidence rate of common COVID-19. The secondary ones, including the time of negative conversion of SARS-CoV-2 RNA and the hospitalization duration were evaluated. Results: A total of 850 mild COVID-19 patients were recruited, and 800 patients were qualified to undergo the clinical trial, with 423 patients assigned for ZQT and 377 patients for TCM placebo. Finally, 390 patients in the ZQT group and 368 patients in the control group completed the follow-up assessments. The nucleic acid conversion rates in ZQT group at 2-day, 3-day and 4-day post-treatment were higher than that in the control group (27.9%vs.9.2%, P<0.001; 38.2%vs.16.6%, P<0.001; 45.4%vs.36.1%, P=0.010). There were no patients who developed into a severe disease. The median time of negative conversion in ZQT group was higher than that in the control group (4[2-6]vs.5[4-6]days, P=0.001). The median hospitalization durations were not different between ZQT group and the control group (5[3-7]vs.6[5-6]days , P=0.065). In terms of the improvement of clinical symptoms, the difference in diarrhea between two groups was statistically significant (100.0%vs.83.3%, P=0.026). There was no significant difference in the improvement of other clinical symptoms. No serious adverse events were reported in both groups. Conclusions: ZhengQi tablet showed beneficial effectiveness in treating patients with mild COVID-19 viaimproving the nucleic acid conversion rate of SARS-CoV-2 and shortening the time of negative conversion.

A four-generation family transmission chain of COVID-19 along the China–Myanmar border in October to November 2021

Background Foreign imported patients and within-household transmission have been the focus and difficulty of coronavirus disease 2019 (COVID-19) prevention and control, which has also posed challenges to border areas' management. However, household transmission caused by foreign imported cases has not been reported in China's border areas. This study aimed to reveal a clear family clustering transmission chain of COVID-19 caused by contact with Myanmar refugees along the China–Myanmar border during an outbreak in October to November 2021. Methods During the outbreak, detailed epidemiological investigations were conducted on confirmed patients with COVID-19 and their close contacts in daily activities. Patients were immediately transported to a designated hospital for treatment and quarantine, and their close contacts were quarantined at designated sites. Regular nucleic acid testing and SARS-CoV-2 antibody testing were provided to them. Results A clear four-generation family clustering transmission involving five patients with COVID-19 was found along the China–Myanmar border. The index case (Patient A) was infected by brief conversations with Myanmar refugees across border fences during work. His wife (Patient B) and 9-month-old daughter (Patient C) were second-generation cases infected by daily contact with him. His 2-year-old daughter (Patient D) was the third-generation case infected by her mother and sister during quarantine in the same room and then transmitted the virus to her grandmother (Patient E, the fourth-generation case) who looked after her after Patients B and C were diagnosed and transported to the hospital. The household secondary attack rate was 80.0%, the average latent period was 4 days, and the generation time was 3 days. Ten of 942 close contacts (1.1%) of this family had positive IgM antibody during the medical observation period. In total 73.9% (696/942) of them were positive for IgG antibody and 8.3% (58/696) had IgG levels over 20 S/CO (optical density of the sample/cut-off value of the reagent). Conclusion This typical transmission chain indicated that it is essential to strengthen COVID-19 prevention and control in border areas, and explore more effective children care approaches in quarantine sites.

Navigating nursing curriculum change during COVID-19 pandemic: A systematic review and meta-synthesis.

AIM: To consolidate the evidence around the experiences of nursing undergraduates and faculty members navigating through remote and online education during the COVID-19 pandemic. BACKGROUND: The Coronavirus disease 2019 caused by the SARS-CoV-2 Virus (COVID-19) has placed massive pressure on healthcare, economic and education systems globally. Restrictive social distancing policies and public health measures necessitated educational institutions to switch from face-to-face to remote and online education to sustain the learning process. These changes have created an uncertain path and undue stress for healthcare learners and faculty, especially for professional roles that traditionally require more hands-on and access to clinical practice particularly pre-licensure nursing students. As such, there is an urgent need to consolidate evidence on the experiences of nursing undergraduates and faculty members as they navigate the rapid transition from face-to-face to remote and online education to ensure continuity of learning in achieving optimal learning outcomes and to support them during current and future public health crises. DESIGN: A systematic review and meta-synthesis of the qualitative literature was undertaken using Sandelowski and Barroso's approach. METHODS: Six electronic databases, CINAHL, Embase, ERIC, PsycINFO, PubMed and Scopus, were searched systematically using the eligibility criteria from December 2019 to September 2022. The Critical Appraisal Skills Program checklist for qualitative studies was used to conduct the critical appraisal of the selected articles. RESULTS: Forty-seven studies were included in this review, which encapsulates the experiences of 3052 undergraduates and 241 faculty members. An overarching meta-theme 'Remote and online education: a rollercoaster ride', emerged along with three main meta-themes: (1) Transition to remote and online education: A turbulent road, (2) Acceptance of the untravelled road, (3) Hopes and recommendations for the road ahead. CONCLUSION: To improve nursing undergraduates' and faculty member's navigation of remote and online education, more institutions should move towards establishing hybrid education as the new 'normal' and exercise prudence in the organisation and delivery of curriculum, teaching, well-being and clinical attachment contingencies of their healthcare courses.

A Complete Information Interaction-Based Bus Passenger Flow Control Model for Epidemic Spread Prevention

Because the strategy of stopping bus lines during an epidemic can negatively impact residents, this study proposes a bus passenger flow control model to optimize the safety of and access to bus transport. The information interaction environment can provide a means for the two-way regulation of buses and passengers. In this model, passengers first request their pick-up and drop-off location, and then the bus feeds back information on whether it accepts the request. Through this method, passenger flow control can be realized through complete information interaction. The study aimed to establish a multi-objective function that minimizes the weighted total cost of the safety cost, the passenger travel cost, and the bus travel cost during an epidemic. The constraints were the full load and riding rates of urban buses in peak periods under the condition of epidemic prevention and control. The results showed that, in the morning peak period, the passenger flow control scheme reduced the passenger infection probability by 17.89%, compared with no passenger flow control scheme. The weighted total cost of the epidemic safety cost, the passenger travel cost, and the bus operation cost was reduced by 8.04%. The optimization effect of the passenger flow control scheme of this model is good, and not only reduces the probability of passengers being infected, but also meets the requirements of epidemic prevention and the travel needs of residents.

Conceptualizing and Assessing the Competitiveness of Slow Tourism Destinations: Evidence From the First Accredited Cittàslow in China

Characterized with in-depth interactions and self-reflections, slow tourism has been gaining growing popularity in recent years thanks to the importance attached to quality of life and self-actualization of tourists in the post modern era, which has all been necessitated by the challenges wrought by the Covid-19 pandemic. In response to the current research lacuna of competitiveness analyses of specialized small-scale destinations, this study comprehensively proposes and empirically evaluates the competitiveness of slow tourism destinations as indicated by the values perceived by the slow tourists, and explores the mechanism of competitiveness of slow tourism destinations with investigation of the interrelationships between competitiveness and tourist attitude, consumption emotion and behavioral intentions through Structural Equation Modeling (SEM). The Gaochun District, which was the first accredited Cittàslow in China, was selected as the research site. Findings yielded four major competitiveness dimensions of community ambiance and service, tourist, and comprehensive management, cultural resources and values and natural resources and protection, and confirmed that perceived values are positively related to attitude, consumption emotion, and behavioral intentions. In addition to offering a valid scale measuring the competitiveness of slow tourism destinations, this study suggests the integration of cultural components in better planning and management of slow tourism destinations.

Examples of modified Maxing Ganshi Decoction for the treatment of COVID-19

TCM has a long history of anti-epidemic diseases and has obvious efficacy. This article introduced the satisfactory efficacy achieved by modified Maxing Ganshi Decoction combined with antiviral therapy in the treatment of COVID-19 based on medical cases, which showed that modified Maxing Ganshi Decoction could alleviate the adverse reactions such as diarrhea in patients caused by antiviral therapy.

SARS-CoV-2 Variant Identification Using a Genome Tiling Array and Genotyping Probes (preprint)

With over three million deaths worldwide attributed to the respiratory disease COVID-19 caused by the novel coronavirus SARS-CoV-2, it is essential that continued efforts be made to track the evolution and spread of the virus globally. We previously presented a rapid and cost-effective method to sequence the entire SARS-CoV-2 genome with 95% coverage and 99.9% accuracy. This method is advantageous for identifying and tracking variants in the SARS-CoV-2 genome when compared to traditional short read sequencing methods which can be time consuming and costly. Herein we present the addition of genotyping probes to our DNA chip which target known SARS-CoV-2 variants. The incorporation of the genotyping probe sets along with the advent of a moving average filter have improved our sequencing coverage and accuracy of the SARS-CoV-2 genome.

Clinical characteristics and therapeutic procedure for a critical case of novel coronavirus pneumonia treated with glucocorticoids and non-invasive ventilator treatment

The novel coronavirus pneumonia (NCP) outbreak occurred in Wuhan, China at the end of 2019. Here, we report the clinical characteristics and therapeutic procedure for a case of severe NCP. The patient was started on glucocorticoids and non-invasive ventilator treatment. After treatment, the patient's symptoms improved, and the status was confirmed as NCP negative. Our results may provide clues for the treatment of NCP.

Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients (preprint)

Dysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic up-regulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19.

Modeling the Opening SARS-CoV-2 Spike: an Investigation of its Dynamic Electro-Geometric Properties (preprint)

The recent COVID-19 pandemic has brought about a surge of crowd-sourced initiatives aimed at simulating the proteins of the SARS-CoV-2 virus. A bottleneck currently exists in translating these simulations into tangible predictions that can be leveraged for pharmacological studies. Here we report on extensive electrostatic calculations done on an exascale simulation of the opening of the SARS-CoV-2 spike protein, performed by the Folding@home initiative. We compute the electric potential as the solution of the non-linear Poisson-Boltzmann equation using a parallel sharp numerical solver. The inherent multiple length scales present in the geometry and solution are reproduced using highly adaptive Octree grids. We analyze our results focusing on the electro-geometric properties of the receptor-binding domain and its vicinity. This work paves the way for a new class of hybrid computational and data-enabled approaches, where molecular dynamics simulations are combined with continuum modeling to produce high-fidelity computational measurements serving as a basis for protein bio-mechanism investigations.

Characteristics of Peripheral Blood Cells in COVID-19 Patients Revealed by a Retrospective Cohort Study (preprint)

Background Peripheral hematological changes in severe COVID-19 patients may reflect the immune reaction during SARS-CoV-2 infection. Characteristics of peripheral blood cells as early signals were needed to be investigated for clarifying its associations with the fatal outcomes in COVID-19 patients. Methods A retrospective cohort study was performed and the hospitalized COVID-19 patients were recruited in wards of Tongji Hospital (Wuhan, China). Characteristics of peripheral blood cells in survivors and non-survivors were analyzed. Also the comparison among patients with different level of eosinophils was performed. Results198 patients were included in this study, of whom 185 were discharged and 13 died in hospital. Compared to the survivors, counts of lymphocytes, monocytes, eosinophils and basophils were significantly decreased in non-survivors. According to the level of eosinophils, patients were divided into low EOS group (< 0.02×109/L) and normal EOS group (≥ 0.02×109/L). Patients in the low EOS group showed a significantly higher fever compared to normal EOS group. The proportion of patients in low EOS group who used glucocorticoids increased significantly than the other group. Death rate in the low EOS group was higher and no patient death in normal EOS group. Moreover, positive correlation was found between the counts of lymphocytes and eosinophils in patients with glucocorticoids use but not in patients without the treatment. Conclusions Hematological changes differed between survivors and non-survivors with COVID-19. Lymphopenia and eosinopenia could serve to predict the poor prognosis of COVID-19 patients. Initial counts of eosinophils may guide us in usage of glucocorticoids for COVID-19 treatment. 

Analysis SARS-CoV-2 Genomes of G20 Areas on Phylogeny Tree, t-SNE based on Machine Learning (preprint)

The new coronavirus disease (COVID-19) broke out earlier in Wuhan, and the plague spread rapidly from multiple resources of different countries. COVID-19 has caused millions of diagnosed people worldwide, causing many deaths and posing a severe threat to public health in countries around the world. Facing this urgent situation, in-depth research on the emerging SARS-CoV-2 to understand the related pathogenic mechanism and epidemiological characteristics is urgent. This type of activity would be useful to determine its origin to formulate effective prevention and treatment strategies for affected patients.This paper adopts t-SNE based on machine learning to draw a phylogenetic tree from collected genomic sequences to analyze G20 countries’ samples. The phylogenetic tree of the generating mechanism was described, and intermediate results were illustrated. The results of this research showed that viruses in many countries have similar or similar relationships among the gene sequences.

The Effect of Neutropenia and Filgrastim (G-CSF) in Cancer Patients With COVID-19 Infection (preprint)

BackgroundNeutropenia is commonly encountered in cancer patients, and recombinant human granulocyte colony-stimulating factor (G-CSF, filgrastim) is widely given to oncology patients to counteract neutropenia and prevent infection. G-CSF is both a growth factor and cytokine that initiates proliferation and differentiation of mature granulocytes. However, the clinical impact of neutropenia and G-CSF use in cancer patients, who are also afflicted with coronavirus disease 2019 (COVID-19), remains unknown. MethodsAn observational cohort of 304 hospitalized patients with COVID-19 at Memorial Sloan Kettering Cancer Center was assembled to investigate links between concurrent neutropenia (N=55) and G-CSF administration (N=16) on COVID-19-associated respiratory failure and death. These factors were assessed as time-dependent predictors using an extended Cox model, controlling for age and underlying cancer diagnosis. To determine whether the degree of granulocyte response to G-CSF affected outcomes, a similar model was constructed with patients that received G-CSF, categorized into "high"- and "low"- response, based on the level of absolute neutrophil count (ANC) rise 24 hours after growth factor administration. ResultsNeutropenia (ANC < 1 K/mcL) during COVID-19 course was not independently associated with severe respiratory failure or death (HR: 0.71, 95% Cl: 0.34-1.50, P value: 0.367) in hospitalized COVID-19 patients. When controlling for neutropenia, G-CSF administration was associated with increased need for high oxygen supplementation and death (HR: 2.97, 95% CI: 1.06-8.28, P value: 0.038). This effect was predominantly seen in patients that exhibited a "high" response to G-CSF based on their ANC increase post-G-CSF administration (HR: 5.18, 95% CI: 1.61-16.64, P value: 0.006). ConclusionPossible risks versus benefits of G-CSF administration should be weighed in neutropenic cancer patients with COVID-19 infection, as G-CSF may lead to worsening clinical and respiratory status in this setting.

Ultrafast Preliminary Screening of COVID-19 by Machine Learning Analysis of Exhaled NO (preprint)

Background A new coronavirus, SARS-CoV-2, has caused the coronavirus disease-2019 (COVID-19) epidemic. Current diagnostic methods mainly include nucleic acid detection, antibody detection, antigen detection, and chest computed tomography (CT) imaging. Although these methods are crucial for the diagnosis of COVID-19, there is a lack of a rapid and economical method for preliminary screening COVID-19.Methods We measured the FeNO concentrations of 103 subjects without COVID-19 and 46 patients with COVID-19. Using machine learning (ML) method, we build a ML model based on fractional exhaled nitric oxide (FeNO) concentration and features of age, and body size for rapid preliminary screening COVID-19 suspects with low-cost.Findings The statistical analysis t-test show that there is a significant difference between the FeNO of healthy people and patients with COVID-19. The ML model can screen out the patients with COVID-19 or other diseases, which show abnormal FeNO distributions. An area under the curve of 0.982 and a sensitivity 0.917 have been achieved for preliminary screening COVID-19 suspects. This non-invasive detection method which takes in two minutes and costs less than a dollar could provide a direction for the control of the rapid spread COVID-19.Interpretation During the COVID-19 pandemic, large numbers and extensive testing of COVID-19 patients remains a problem. Public healthy efforts to limit SARS-CoV-2 spread need to find a more economical and faster screening method.