Characterization and pathogenicity of the porcine epidemic diarrhea virus isolated in China.

Piglet diarrhea caused by the porcine epidemic diarrhea virus (PEDV) is a common problem on pig farms in China associated with high morbidity and mortality rates. In this study, three PEDV isolates were successfully detected after the fourth blind passage in Vero cells. The samples were obtained from infected piglet farms in Jilin (Changchun), and Shandong (Qingdao) Provinces of China and were designated as CH/CC-1/2018, CH/CC-2/2018, and CH/QD/2018. According to the analysis of the complete S protein gene sequence, the CH/CC-1/2018 and CH/CC-2/2018 were allocated to the G2b branch, while CH/QD/2018 was located in the G1a interval and was closer to the vaccine strain CV777. Successful detection and identification of the isolated strains were carried out using electron microscopy and indirect immunofluorescence. Meanwhile, animal challenge experiments and viral RNA copies determination were used to compare the pathogenicity. The results showed that CH/CC-1/2018 in Changchun was more pathogenic than CH/QD/2018 in Qingdao. In conclusion, the discovery of these new strains is conducive to the development of vaccines to prevent the pandemic of PEDV, especially that the CH/CC-1/2018, and CH/CC-2/2018 were not related to the classical vaccine strain CV777.

Dysregulation of glutamine/glutamate metabolism in COVID-19 patients: A metabolism study in African population and mini meta-analysis.

Coronavirus disease 2019 (COVID-19) remains a serious global threat. The metabolic analysis had been successfully applied in the efforts to uncover the pathological mechanisms and biomarkers of disease severity. Here we performed a quasi-targeted metabolomic analysis on 56 COVID-19 patients from Sierra Leone in western Africa, revealing the metabolomic profiles and the association with disease severity, which was confirmed by the targeted metabolomic analysis of 19 pairs of COVID-19 patients. A meta-analysis was performed on published metabolic data of COVID-19 to verify our findings. Of the 596 identified metabolites, 58 showed significant differences between severe and nonsevere groups. The pathway enrichment of these differential metabolites revealed glutamine and glutamate metabolism as the most significant metabolic pathway (Impact = 0.5; -log10P = 1.959). Further targeted metabolic analysis revealed six metabolites with significant intergroup differences, with glutamine/glutamate ratio significantly associated with severe disease, negatively correlated with 10 clinical parameters and positively correlated with SPO2 (rs = 0.442, p = 0.005). Mini meta-analysis indicated elevated glutamate was related to increased risk of COVID-19 infection (pooled odd ratio [OR] = 2.02; 95% confidence interval [CI]: 1.17-3.50) and severe COVID-19 (pooled OR = 2.28; 95% CI: 1.14-4.56). In contrast, elevated glutamine related to decreased risk of infection and severe COVID-19, the pooled OR were 0.30 (95% CI: 0.20-0.44), and 0.44 (95% CI: 0.19-0.98), respectively. Glutamine and glutamate metabolism are associated with COVID-19 severity in multiple populations, which might confer potential therapeutic target of COVID-19, especially for severe patients.

The role of selenium in severe fever with thrombocytopenia syndrome: an integrative analysis of surveillance data and clinical data.

OBJECTIVES: Selenium deficiency can be associated with increased susceptibility to some viral infections and even more severe diseases. In this study, we aimed to examine whether this association applies to severe fever with thrombocytopenia syndrome (SFTS). METHOD: An observational study was conducted based on the data of 13,305 human SFTS cases reported in mainland China from 2010 to 2020. The associations among incidence, case fatality rate of SFTS, and crop selenium concentration at the county level were explored. The selenium level in a cohort of patients with SFTS was tested, and its relationship with clinical outcomes was evaluated. RESULTS: The association between selenium-deficient crops and the incidence rate of SFTS was confirmed by multivariate Poisson analysis, with an estimated incidence rate ratio (IRR, 95% confidence interval [CI]) of 4.549 (4.215-4.916) for moderate selenium-deficient counties and 16.002 (14.706-17.431) for severe selenium-deficient counties. In addition, a higher mortality rate was also observed in severe selenium-deficient counties with an IRR of 1.409 (95% CI: 1.061-1.909). A clinical study on 120 patients with SFTS showed an association between serum selenium deficiency and severe SFTS (odds ratio, OR: 2.94; 95% CI: 1.00-8.67) or fatal SFTS (OR: 7.55; 95% CI: 1.14-50.16). CONCLUSION: Selenium deficiency is associated with increased susceptibility to SFTS and poor clinical outcomes.

Early detection of rumors based on source tweet-word graph attention networks.

The massively and rapidly spreading disinformation on social network platforms poses a serious threat to public safety and social governance. Therefore, early and accurate detection of rumors in social networks is of vital importance before they spread on a large scale. Considering the small-world property of social networks, the source tweet-word graph is decomposed from the global graph of rumors, and a rumor detection method based on graph attention network of source tweet-word graph is proposed to fully learn the structure of rumor propagation and the deep representation of text contents. Specifically, the proposed model can adequately capture the contextual semantic association representation of source tweets during the propagation and extract semantic features. For the data sparseness of the early stage of information dissemination, text attention mechanism based on opinion similarity can aggregate and capture more tweet propagation structure features to help improve the efficiency of early detection of rumors. Through the analysis of the experimental results on real public datasets, the rumor detection performance of the proposed method is better than that of other baseline methods. Especially in the early rumor detection tasks, the proposed method can detect rumors with an accuracy of nearly 90% in the early stage of information dissemination. And it still has good robustness with noise interference.

Preparation and consideration for establishment of an isolation maternity unit in a tertiary hospital during COVID-19 pandemic.

The SARS-CoV-2 pandemic is rapidly evolving and remains a major health challenge worldwide. With an increase in pregnant women with COVID-19 infection, we recognized an urgent need to set up a multidisciplinary taskforce to provide safe and holistic care for this group of women. In this review of practice in a tertiary hospital in Singapore, we discuss the key considerations in setting up an isolation maternity unit and our strategies for peripartum and postpartum care. Through teleconsultation, we involve these women and their families in the discussion of timing and mode of birth, disposition of babies after birth and safety of breastfeeding to enable them to make informed decisions and individualize their care.

The Effects of Pulsed Electric Field On The Interaction Between SARS-Cov-2 And Human ACE2: Y505 Is A Key Target (preprint)

A novel coronavirus has rapidly spread to almost every country in the world, causing over 233 million confirmed cases of coronavirus disease 2019 (COVID-19) and over 209,761,242 deaths by late September 2021. Binding the receptor binding domain (RBD) to the host cell surface receptor protein, angiotensin converter enzyme (ACE2), is a key step in virus infection. In this study, we applied a pulsed electric field to the RBD/ACE2 complex based on molecular dynamics simulation and demonstrated that the electric field affects the structure and binding affinity of the complex. Additionally, residue Y505 is the crucial medium for the effects of electric field on the complex. Overall, these results may help apply an external electric field to virus suppression.

Industry 4.0: Challenges and success factors for adopting digital technologies in airports (preprint)

With the advent of Industry 4.0 technologies in the last decade, airports have undergone digitalisation to capitalise on the purported benefits of these technologies such as improved operational efficiency and passenger experience. The ongoing COVID-19 pandemic with emergence of its variants (e.g. Delta, Omicron) has exacerbated the need for airports to adopt new technologies such as contactless and robotic technologies to facilitate travel during this pandemic. However, there is limited knowledge of recent challenges and success factors for adoption of digital technologies in airports. Therefore, through an industry survey of airport operators and managers around the world (n=102, 0.754

Adoption of Industry 4.0 technologies in airports -- A systematic literature review (preprint)

Airports have been constantly evolving and adopting digital technologies to improve operational efficiency, enhance passenger experience, generate ancillary revenues and boost capacity from existing infrastructure. The COVID-19 pandemic has also challenged airports and aviation stakeholders alike to adapt and manage new operational challenges such as facilitating a contactless travel experience and ensuring business continuity. Digitalisation using Industry 4.0 technologies offers opportunities for airports to address short-term challenges associated with the COVID-19 pandemic while also preparing for future long-term challenges that ensue the crisis. Through a systematic literature review of 102 relevant articles, we discuss the current state of adoption of Industry 4.0 technologies in airports, the associated challenges as well as future research directions. The results of this review suggest that the implementation of Industry 4.0 technologies is slowly gaining traction within the airport environment, and shall continue to remain relevant in the digital transformation journeys in developing future airports.

Emergency medicine clerkship goes online: Evaluation of a telesimulation programme

Introduction: COVID-19 challenged a graduate medical student Emergency Medicine Clinical Clerkship to transform a 160-hour face-to-face clinical syllabus to a remotely delivered e-learning programme comprising of live streamed lectures, case-based discussions, and telesimulation experiences. This paper outlines the evaluation of the telesimulation component of a programme that was designed as a solution to COVID-19 restriction. Methods: A mixed methods approach was used to evaluate the telesimulation educational activities. Via a post-course online survey student were asked to rate the pre-simulation preparation, level of engagement, confidence in recognising and responding to the four clinical presentations and to evaluate telesimulation as a tool to prepare for working in the clinical environment. Students responded to open-ended questions describing their experience in greater depth. Results: Forty-two (72.4%) out of 58 students responded. 97.62% agreed that participating in the simulation was interesting and useful and 90.48% felt that this will provide a good grounding prior to clinical work. Four key themes were identified: Fidelity, Realism, Engagement and Knowledge, Skills and Attitudes Outcomes. Limitations of telesimulation included the inability to examine patients, perform procedures and experience non-verbal cues of team members and patients;but this emphasised importance of non-verbal cues and close looped communication. Additionally, designing the telesimulation according to defined objectives and scheduling it after the theory teaching contributed to successful execution. Conclusion: Telesimulation is an effective alternative when in-person teaching is not possible and if used correctly, can sharpen non-tactile aspects of clinical care such as history taking, executing treatment algorithms and team communication. [ABSTRACT FROM AUTHOR] Copyright of Asia Pacific Scholar is the property of Centre for Medical Education (CenMed) 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 abstract 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 abstract. (Copyright applies to all Abstracts.)

Attitudes of teaching faculty towards clinical teaching of medical students in an emergency department of a teaching institution in Singapore during the COVID-19 pandemic

Introduction: Singapore experienced the COVID-19 outbreak from January 2020 and Emergency Departments (ED) were at the forefront of healthcare activity during this time. Medical students who were attached to the EDs had their clinical training affected. Methods: We surveyed teaching faculty in a tertiary teaching hospital in Singapore to assess if they would consider delivering clinical teaching to medical students during the outbreak and conducted a thematic analysis of their responses. Results: 53.6% felt that medical students should not undergo clinical teaching in the ED and 60.7% did not wish to teach medical students during the outbreak. Three themes arose during the analysis of the data - Cognitive Overload of Clinical Teachers, Prioritisation of Clinical Staff Welfare versus Medical Students, and Risk of Viral Exposure versus Clinical Education. Conclusion: During a pandemic, a balance needs to be sought between clinical service and education, and faculty attitudes towards teaching in high-risk environments can shift their priorities in favour of providing the former over the latter. [ABSTRACT FROM AUTHOR] Copyright of Asia Pacific Scholar is the property of Centre for Medical Education (CenMed) 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 abstract 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 abstract. (Copyright applies to all Abstracts.)

TRPV2-spike protein interaction mediates the entry of SARS-CoV-2 into macrophages in febrile conditions.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel strain of highly contagious coronaviruses that infects humans. Prolonged fever, particularly that above 39.5 °C, is associated with SARS-CoV-2 infection. However, little is known about the pathological effects of fever caused by SARS-CoV-2. Methods: Primary bovine alveolar macrophages (PBAMs), RAW264.7 mouse macrophages, and THP-1 human cells were transfected with plasmids carrying the genes encoding the SARS-CoV-2 spike (S) protein or receptor-binding domain (RBD). Proteins in the macrophages interacting with S-RBD at 39.5 °C or 37 °C were identified by immunoprecipitation-mass spectrometry. Glutathione S-transferase pulldown, surface plasmon resonance, and immunofluorescence were performed to evaluate the transient receptor potential vanilloid 2 (TRPV2) interaction with SARS-CoV-2-S-RBD at 39.5 °C. Using an RNA sequencing-based approach, cytokine gene expression induced by SARS-CoV-2 S transfection at 39.5 °C and 37.5 °C in primary alveolar macrophages was measured. Fluo-4 staining and enzyme-linked immunosorbent assays were used to assess the regulatory function of TRPV2 in intracellular Ca 2+ and cytokines under SARS-CoV-2-S-RBD at 39.5 °C. Additionally, cytokine release was examined after TRPV2 knockdown with shRNA oligonucleotides or inhibition using the SKF-96365 antagonist. Results: We identified an interaction between the primary alveolar macrophage receptor TRPV2 and S-RBD under febrile conditions. Febrile temperature promotes Ca2+ influx through SARS-CoV-2 infection in PBAMs, further activates the NF-κB p65 signaling pathway, and enhances the secretion of cytokines. Furthermore, knockdown or antagonist (with SKF-96365) of TRPV2 significantly decreased the release of cytokines that drive the inflammatory response. Conclusion: Collectively, our findings identified TRPV2 as a receptor of SARS-CoV-2 in conditions of febrile temperature, providing insight into critical interactions of SARS-CoV-2 with macrophages, as well as a useful resource and potential drug target for coronavirus disease 2019.

A graphene oxide coated tapered microfiber acting as a super-sensor for rapid detection of SARS-CoV-2.

COVID-19 is a new strain of highly contagious coronavirus, and at present, more than 221.4 million people have been infected with this virus, and the death toll exceeds 2793398. Early and fast detection of COVID-19 from infected individuals is critical to limit its spreading. Here, we report an innovative approach to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) protein by combining DNA/RNA oligomers as aptamers and a graphene oxide (GO) coated optical microfiber as a sensor system. The DNA/RNA aptamers can effectively capture the SARS-CoV-2 N protein in vitro, with the GO coated optical microfiber aptasensor for real-time monitoring of the SARS-CoV-2 N protein. Due to the extremely high surface-to-volume ratio and excellent optical and biochemical properties of the GO surface layer, the fixing effect of the microfiber surface is significantly improved and the lowest limit of detection (LOD) is 6.25 × 10-19 M. Furthermore, in order to prove the feasibility of this sensing method in clinical applications, we use this sensor to detect the N protein mixed in fetal bovine serum (FBS) samples. The experimental results show that the biosensor can quickly and effectively detect the N protein (1 × 10-9 M) in a complex sample matrix within 3 minutes. These findings suggest that this approach can be utilized for quantitative monitoring of coronavirus particles due to its high sensitivity, which can help to quickly exclude patients who do not have the infection. Collectively, the optical microfiber sensor system could be expected to become an important platform for the diagnosis of coronavirus due to its simple detection scheme and easy miniaturization.

Potential effects of SARS-CoV-2 on the gastrointestinal tract and liver.

COVID-19 is a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early reported symptoms include fever, cough, and respiratory symptoms. There were few reports of digestive symptoms. However, with COVID-19 spreading worldwide, symptoms such as vomiting, diarrhoea, and abdominal pain have gained increasing attention. Research has found that angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 receptor, is strongly expressed in the gastrointestinal tract and liver. Whether theoretically or clinically, many studies have suggested a close connection between COVID-19 and the digestive system. In this review, we summarize the digestive symptoms reported in existing research, discuss the impact of SARS-CoV-2 on the gastrointestinal tract and liver, and determine the possible mechanisms and aetiology, such as cytokine storm. In-depth exploration of the relationship between COVID-19 and the digestive system is urgently needed.

Machine learning based early warning system enables accurate mortality risk prediction for COVID-19.

Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients' clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464-0.9778), 0.9760 (0.9613-0.9906), and 0.9246 (0.8763-0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.

COVID-19 and early-stage lung cancer both featuring ground-glass opacities: a propensity score-matched study.

BACKGROUND: Radiological manifestations of coronavirus disease 2019 (COVID-19) featured ground-glass opacities (GGOs), especially in the early stage, which might create confusion in differential diagnosis with early lung cancer. We aimed to specify the radiological characteristics of COVID-19 and early lung cancer and to unveil the discrepancy between them. METHODS: One hundred and fifty-seven COVID-19 patients and 374 early lung cancer patients from four hospitals in China were retrospectively enrolled. Epidemiological, clinical, radiological, and pathological characteristics were compared between the two groups using propensity score-matched (PSM) analysis. RESULTS: COVID-19 patients had more distinct symptoms, tended to be younger (P<0.0001), male (P<0.0001), and had a higher body mass index (P=0.014). After 1:1 PSM, 121 matched pairs were identified. Regarding radiological characteristics, patients with a single lesion accounted for 17% in COVID-19 and 89% in lung cancer (P<0.0001). Most lesions were peripherally found in both groups. Lesions in COVID-19 involved more lobes (median 3.5 vs. 1; P<0.0001) and segments (median 6 vs. 1; P<0.0001) and tended to have multiple types (67%) with patchy form (54%). Early lung cancer was more likely to have a single type (92%) with oval form (66%). Also, COVID-19 and early lung cancer either had some distinctive features on computed tomography (CT) images. CONCLUSIONS: Both COVID-19 and early lung cancers showed GGOs, with similar but independent features. The imaging characteristics should be fully understood and combined with epidemiological history, pathogen detection, laboratory tests, short-term CT reexamination, and pathological results to aid differential diagnosis.