Camel virus (MERS) reported from Qatar: a threat to the FIFA-2022 and Middle East

Middle East Respiratory Syndrome Coronavirus Could be a Priority Pathogen to Cause Public Health Emergency: Noticeable Features and Counteractive Measures

Middle East respiratory syndrome (MERS) is caused by a specific strain of the 6 types of human coronaviruses (HCoV). MERS-CoV has spread unchecked since it was first discovered in Saudi Arabia in 2012. The virus most likely spreads through nosocomial and zoonotic channels. Genetic analyses suggest that bats were the initial hosts and that the disease spread to camels. Person-to-person transmission occurs with varying frequency, being most prevalent in clinical settings and the least common among the general population and among close relatives. Due to the severity of the illness, high fatality rate, potential for epidemic spread, and lack of adequate medical countermeasures, the World Health Organization (WHO) continues to list MERS-CoV as a priority pathogen. While no specific antiviral medicines exist, a combination of antivirals has shown promise in recent clinical trials. Vaccines against MERS-CoV are critically needed and are currently being developed. Early diagnosis and implementing appropriate infection control measures are keys to preventing hospital-associated outbreaks. Preventive measures include avoiding raw or undercooked meats and other animal products, ensuring proper hand hygiene in healthcare settings and around dromedaries, educating the public and healthcare personnel about the disease, and adhering to other recommended practices. Countries with a high prevalence of MERS should adhere to regulations designed to limit the transmission of the virus. The recent spread of MERS-CoV highlights the importance of public awareness regarding the significance of reporting symptoms so that appropriate control measures can be adopted. The narrative review discusses the incidence of MERS, its clinical presentation, potential transmission routes, recent reports, preventative and control measures, and current therapeutic options.

SARS-CoV-2 seroprevalence determination in pets and camels in Egypt using multispecies enzyme-linked immunosorbent assay

The coronavirus disease 2019 (COVID-19) pandemic has translated into a worldwide economic recession and public health crisis. Bats have been incriminated as the main natural host for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of the COVID-19 pandemic. However, the reservoir and carrier hosts of the virus remain unknown. Therefore, a cross sectional serosurvey study was performed to estimate antibodies to SARS-CoV-2. To assess IgM antibodies to SARS-CoV-2 nucleocapsid protein (NP), a SARS-CoV-2 Double Antigen Multispecies diagnostic enzyme-linked immunosorbent assay kit was used. The seropositive samples were confirmed and validated by measuring IgG antibody titers in sera. The enrolled animals were from different locations in the Giza governorate, Egypt, and were sampled at the time of the pandemic; they comprised 92 companion animals and 92 domestic camels. The study established that 4.76% (1/21 clinical samples) of dogs, 7.69% of cats (1/13 shelter samples) and 1.08% (1/92) of camels, had measurable SARS-CoV-2 NP IgM antibodies. All IgM-seropositive samples were IgG positive with a measurable titer of 34.5, 28.6, and 25.8 UI/mL for dog, cat, and camels, respectively. According to our best knowledge, this study was the first to assess SARS-CoV-2 seroprevalence in the specific animals investigated in Egypt. These results may herald a promising epidemiological role for pet animals and camels in SARS-CoV-2 virus maintenance. Thus, our study's results ought to be confirmed with a nationwide seroprevalence study, and further studies are required to clarify whether these animals act as active or passive carriers.

Deep and Transfer Learning Approaches for Automated Early Detection of Monkeypox (Mpox) Alongside Other Similar Skin Lesions and Their Classification

The world faces multiple public health emergencies simultaneously, such as COVID-19 and Monkeypox (mpox). mpox, from being a neglected disease, has emerged as a global threat that has spread to more than 100 nonendemic countries, even as COVID-19 has been spreading for more than 3 years now. The general mpox symptoms are similar to chickenpox and measles, thus leading to a possible misdiagnosis. This study aimed at facilitating a rapid and high-brevity mpox diagnosis. Reportedly, mpox circulates among particular groups, such as sexually promiscuous gay and bisexuals. Hence, selectively vaccinating, isolating, and treating them seems difficult due to the associated social stigma. Deep learning (DL) has great promise in image-based diagnosis and could help in error-free bulk diagnosis. The novelty proposed, the system adopted, and the methods and approaches are discussed in the article. The present work proposes the use of DL models for automated early mpox diagnosis. The performances of the proposed algorithms were evaluated using the data set available in public domain. The data set adopted for the study was meant for both training and testing, the details of which are elaborated. The performances of CNN, VGG19, ResNet 50, Inception v3, and Autoencoder algorithms were compared. It was concluded that CNN, VGG19, and Inception v3 could help in early detection of mpox skin lesions, and Inception v3 returned the best (96.56%) classification accuracy.

Current Surge of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Variants in China Could Be Threatening as the Asian Games 2023 Flags Off in September: Foolproof Cautionary Measures Are Suggested

Despite normalcy having almost returned in the lives of people throughout the world post-coronavirus disease-19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the danger still looms over the fears of development and propagation of a newer SARS-CoV-2 variant. The movement of people globally has reached the pre-pandemic level, and this augmentation increased surveillance regarding the emergence of lethal SARS-CoV-2 variants. International sports events are among the potential avenues where the virus could cause serious impact. Therefore, the organization of such events should be planned and executed meticulously to avoid viral transmission and minimize the health effects of infections on the sportspersons and the local people. Additionally, there could be dissemination of the infections to the native countries of the participants and visitors while they return to their homes. Through this editorial, we prompt caution to the organizers and the event-hosting nation's administration regarding the potential threat and suggest measures to avoid any medical emergencies related to COVID-19.

System Biology Approach to Identify the Hub Genes and Pathways Associated with Human H5N1 Infection

INTRODUCTION

H5N1 is a highly pathogenic avian influenza virus that can infect humans and has an estimated fatality rate of 53%. As shown by the current situation of the COVID-19 pandemic, emerging and re-emerging viruses such as H5N1 have the potential to cause another pandemic. Thus, this study outlined the hub genes and pathways associated with H5N1 infection in humans.

METHODS

The genes associated with H5N1 infection in humans were retrieved from the NCBI Gene database using "H5N1 virus infection" as the keyword. The genes obtained were investigated for protein-protein interaction (PPI) using STRING version 11.5 and studied for functional enrichment analysis using DAVID 2021. Further, the PPI network was visualised and analysed using Cytoscape 3.7.2, and the hub genes were obtained using the local topological analysis method of the cytoHubba plugin.

RESULTS

A total of 39 genes associated with H5N1 infection in humans significantly interacted with each other, forming a PPI network with 38 nodes and 149 edges modulating 74 KEGG pathways, 76 biological processes, 13 cellular components, and 22 molecular functions. Further, the PPI network analysis revealed that 33 nodes interacted, forming 1056 shortest paths at 0.282 network density, along with a 1.947 characteristic path length. The local topological analysis predicted IFNA1, IRF3, CXCL8, CXCL10, IFNB1, and CHUK as the critical hub genes in human H5N1 infection.

CONCLUSION

The hub genes associated with the H5N1 infection and their pathways could serve as diagnostic, prognostic, and therapeutic targets for H5N1 infection among humans.