Recent Advances of Nipah Virus Disease: Pathobiology to Treatment and Vaccine Advancement.

The zoonotic infection of the Nipah virus (NiV) has yet again appeared in 2023 in Kerala state, India. The virus, which has a mortality rate ranging from about 40 to 70%, has already infected India five times, the first being in 2001. The current infection is the sixth virus outbreak in the Indian population. In 1998, the first NiV infection was noted in one village in Malaysia. After that, outbreaks from other South and Southeast Asian countries have been reported periodically. It can spread between humans through contact with body fluids. Therefore, it is unlikely to generate a new pandemic. However, there is a considerable knowledge gap in the different areas of NiV. To date, no approved vaccines or treatments have been available. To fulfil the knowledge gap, the review article provided a detailed overview of the genome and genome-encoded proteins, epidemiology, transmission, pathobiology, immunobiology, diagnosis, prevention and control measures, therapeutics (monoclonal antibodies and drug molecules), and vaccine advancement of the emerging and deadly pathogen. The advanced information will help researchers to develop safe and effective NiV vaccine and treatment regimens worldwide.

Evolution and mutational landscape of highly pathogenic avian influenza strain A(H5N1) in the current outbreak in the USA and global landscape.

The emergence of highly pathogenic avian influenza strain A (H5N1) in the USA is a high concern. Here, we illustrated the evolution, divergence, transmission pattern, infection pattern, entropy diversity, nucleotide diversity, and mutational landscape of HPAI(H5N1). We depicted three phylogenetic trees, i.e., from three perspectives: considering the HPAI H5N1 genome of the current outbreak in the USA (n = 971), considering the HPAI H5N1 spared in different hosts (cattle, hunan, avian, and nonhuman primates) and using the global genome sequences (n = 3154). We found that the clade 2.3.4.4b was responsible for the present infection. We noted that the USA's divergence rate is 3.43e-3 subs per site per year, and the global divergence rate is 5.21e-3 subs per site per year. We reported significant nucleotide changes to illustrate the genome. Similarly, we observe several point mutations in some proteins, such as PB2, PA, HA, NA, and NS1. Among point mutations, some common mutations are noted in PB2 (E362G, M631L) and PA (L219I, K497R). However, elimination strategies should be a high priority for dairy farm workers, domestic cattle, and poultry birds to limit future outbreaks.

Autoantibodies in COVID-19 and Other Viral Diseases: Molecular, Cellular, and Clinical Perspectives.

Autoantibodies are immune system-produced antibodies that wrongly target the body's cells and tissues for attack. The COVID-19 pandemic has made it possible to link autoantibodies to both the severity of pathogenic infection and the emergence of several autoimmune diseases after recovery from the infection. An overview of autoimmune disorders and the function of autoantibodies in COVID-19 and other infectious diseases are discussed in this review article. We also investigated the different categories of autoantibodies found in COVID-19 and other infectious diseases including the potential pathways by which they contribute to the severity of the illness. Additionally, it also highlights the probable connection between vaccine-induced autoantibodies and their adverse outcomes. The review also discusses the therapeutic perspectives of autoantibodies. This paper advances our knowledge about the intricate interaction between autoantibodies and COVID-19 by thoroughly assessing the most recent findings.

The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges.

Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug discovery has come to the forefront. It reduces the time and expenditure. Due to these advantages, pharmaceutical industries are concentrating on AI-driven drug discovery. Several drug molecules have been discovered using AI-based techniques and tools, and several newly AI-discovered drug molecules have already entered clinical trials. In this review, we first present the data and their resources in the pharmaceutical sector for AI-driven drug discovery and illustrated some significant algorithms or techniques used for AI and ML which are used in this field. We gave an overview of the deep neural network (NN) models and compared them with artificial NNs. Then, we illustrate the recent advancement of the landscape of drug discovery using AI to deep learning, such as the identification of drug targets, prediction of their structure, estimation of drug-target interaction, estimation of drug-target binding affinity, design of de novo drug, prediction of drug toxicity, estimation of absorption, distribution, metabolism, excretion, toxicity; and estimation of drug-drug interaction. Moreover, we highlighted the success stories of AI-driven drug discovery and discussed several collaboration and the challenges in this area. The discussions in the article will enrich the pharmaceutical industry.

Rational Design of a Multi-epitope Vaccine Using Neoantigen Against Colorectal Cancer Through Structural Immunoinformatics and ML-Enabled Simulation Approach.

Colorectal cancer poses a substantial global health burden. Regarding WHO, the global burden of colorectal cancer will be about 3.2 million new cases by the year 2040. Simultaneously, it indicated that this cancer will cause 6 million deaths per year. Despite advancements in chemotherapy and monoclonal antibody therapy, the disease remains a significant challenge due to the resistance of cancer stem cells. This study endeavors to design a multi-epitopic peptide (9-mer epitopes) neoantigen-based vaccine targeting the TLR4/MD2 complex as a potential vaccine candidate. These tumor-specific neoantigens (TSA) are considered novel antigens that can be used for vaccine development against cancer. To develop the neoantigen vaccine candidate, we used the SPENCER database, and 140 lncRNA-derived epitopes were retrieved. From 140 epitopes, we selected seven neoantigens with high antigenic properties for the vaccine construct. A novel vaccine containing epitopes, linkers (EAAAK and CPCPG), and adjuvants (ribosomal [50S] protein L7L12) was formulated utilizing immunoinformatics tools. The vaccine's biophysical properties were evaluated, revealing its antigenicity (0.6469), stability (instability index: 37.05), and potential for immune system interaction. In-depth structural analyses, molecular docking studies, and ML-enabled immune simulation profiling underscored the vaccine's structural integrity, binding affinity with TLR4, and ability to elicit robust immune responses against colorectal cancer antigens. These findings suggest that the multi-epitopic vaccine holds promise as a next-generation approach to combat colorectal cancer. Our in silico studies exhibit potentiality of the vaccine candidate; however, further in vivo and in vitro investigations are crucial to validate immunogenicity, safety, and efficacy before clinical implementation. Our study developed a first-time lncRNA-derived neoantigen-based cancer vaccine.

Recent Advances in Immunological Landscape and Immunotherapeutic Agent of Nipah Virus Infection.

Over the last two decades, the Nipah virus (NiV) emerged as a highly lethal zoonotic pathogen to humans. Outbreaks occurred occasionally in South and Southeast Asia. Therefore, a safe and effective vaccine against the virus is needed to fight against the deadly virus. Understanding the immunological landscape during this lethal virus infection is necessary in this direction. However, we found scattered information on the immunological landscape of the virus's reservoir, as well as hosts such as humans and livestock. The review provides a recent understanding of the immunological landscape of the virus's reservoir, human hosts, monoclonal antibodies, and vaccines for NiV infection. To describe the immunological landscape, we divided our review article into some points. Firstly, we illustrated bats' immune response as a reservoir during the NiV infection. Secondly, we illustrated an overview of the molecular mechanisms underlying the immune response to the NiV infection, various immune cells, humans' innate immune response, adaptive immunity, and the landscape of cytokines and chemokines. We also discussed INF escape, NET evasion, the T cell landscape, and the B cell landscape during virus infection. Thirdly, we also demonstrated the potential monoclonal antibody therapeutics, and vaccines. Finally, neutralizing antibodies (nAbs) of NiV and potentially other therapeutic strategies were discussed. The review will help researchers for better understanding the immunological landscape, mAbs, and vaccines, enabling them to develop their next-generation versions.

Therapeutic Potential of Quercetin as an Antioxidant for Bone-Muscle-Tendon Regeneration and Aging.

Quercetin (QC), a naturally occurring bioflavonoid found in various fruits and vegetables, possesses many potential health benefits, primarily attributed to its robust antioxidant properties. The generation of oxidative stress in bone cells is a key modulator of their physiological behavior. Moreover, oxidative stress status influences the pathophysiology of mineralized tissues. Increasing scientific evidence demonstrates that manipulating the redox balance in bone cells might be an effective technique for developing bone disease therapies. The QC antioxidant abilities in skeletal muscle significantly enhance muscle regeneration and reduce muscle atrophy. In addition, QC has been shown to have protective effects against oxidative stress, inflammation, apoptosis, and matrix degradation in tendons, helping to maintain the structural integrity and functionality of tendons. Thus, the antioxidant properties of QC might be crucial for addressing age-related musculoskeletal disorders like osteoporosis, sarcopenia, and tendon-related inflammatory conditions. Understanding how QC influences redox signaling pathways involved in musculoskeletal disorders, including their effect on bone, muscle, and tendon differentiation, might provide insights into the diverse advantages of QC in promoting tissue regeneration and preventing cellular damage. Therefore, this study reviewed the intricate relationship among oxidative stress, inflammation, and tissue repair, affected by the antioxidative abilities of QC, in age-related musculoskeletal tissues to improve the overall health of bones, muscles, and tendons of the skeletal system. Also, reviewing the ongoing clinical trials of QC for musculoskeletal systems is encouraging. Given the positive effect of QC on musculoskeletal health, further scientific investigations and controlled human intervention studies are necessary to explore the therapeutic potential to its optimum strength.

Gene expression profiling and the isocitrate dehydrogenase mutational landscape of temozolomide­resistant glioblastoma.

Glioblastoma multiforme (GBM) is an aggressive brain cancer that occurs more frequently than other brain tumors. The present study aimed to reveal a novel mechanism of temozolomide resistance in GBM using bioinformatics and wet lab analyses, including meta-Z analysis, Kaplan-Meier survival analysis, protein-protein interaction (PPI) network establishment, cluster analysis of co-expressed gene networks, and hierarchical clustering of upregulated and downregulated genes. Next-generation sequencing and quantitative PCR analyses revealed downregulated [tyrosine kinase with immunoglobulin and epidermal growth factor homology domains 1 (TIE1), calcium voltage-gated channel auxiliary subunit α2Δ1 (CACNA2D1), calpain 6 (CAPN6) and a disintegrin and metalloproteinase with thrombospondin motifs 6 (ADAMTS6)] and upregulated [serum amyloid (SA)A1, SAA2, growth differentiation factor 15 (GDF15) and ubiquitin specific peptidase 26 (USP26)] genes. Different statistical models were developed for these genes using the Z-score for P-value conversion, and Kaplan-Meier plots were constructed using several patient cohorts with brain tumors. The highest number of nodes was observed in the PPI network was for ADAMTS6 and TIE1. The PPI network model for all genes contained 35 nodes and 241 edges. Immunohistochemical staining was performed using isocitrate dehydrogenase (IDH)-wild-type or IDH-mutant GBM samples from patients and a significant upregulation of TIE1 (P<0.001) and CAPN6 (P<0.05) protein expression was demonstrated in IDH-mutant GBM in comparison with IDH-wild-type GBM. Structural analysis revealed an IDH-mutant model demonstrating the mutant residues (R132, R140 and R172). The findings of the present study will help the future development of novel biomarkers and therapeutics for brain tumors.

Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox.

BACKGROUND: Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets. METHODS: GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules. RESULTS: Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development. RESULTS: MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

Reverse Zoonotic Transmission of SARS-CoV-2 and Monkeypox Virus: A Comprehensive Review.

Reverse zoonosis reveals the process of transmission of a pathogen through the human-animal interface and the spillback of the zoonotic pathogen. In this article, we methodically demonstrate various aspects of reverse zoonosis, with a comprehensive discussion of SARS-CoV-2 and MPXV reverse zoonosis. First, different components of reverse zoonosis, such as humans, different pathogens, and numerous animals (poultry, livestock, pets, wild animals, and zoo animals), have been demonstrated. Second, it explains the present status of reverse zoonosis with different pathogens during previous occurrences of various outbreaks, epidemics, and pandemics. Here, we present 25 examples from literature. Third, using several examples, we comprehensively illustrate the present status of the reverse zoonosis of SARS-CoV-2 and MPXV. Here, we have provided 17 examples of SARS-CoV-2 reverse zoonosis and two examples of MPXV reverse zoonosis. Fourth, we have described two significant aspects of reverse zoonosis: understanding the fundamental aspects of spillback and awareness. These two aspects are required to prevent reverse zoonosis from the current infection with two significant viruses. Finally, the One Health approach was discussed vividly, where we urge scientists from different areas to work collaboratively to solve the issue of reverse zoonosis.

FLip mutations (L455F + F456L) in newly emerging VOI, JN.1: Its antibody and immune escape.

During the COVID-19 pandemic, one of the biggest challenges was the continuous evolution of SARS-CoV-2 through various mutations. This has resulted in the emergence of several variants and subvariants. The escape mutations are reported as significant mutations in several variants and subvariants responsible for immune, antibody, and nAb escape. It has been reported that FLip mutations (L455F and F456L) in the spike RBD are responsible for immune evasion and antibody escape. Recently, WHO has included a new SARS-CoV-2 VOI, JN.1 lineage, a descendent of BA.2.86. The variant is reported from more than 41 countries, including France, the USA, Canada, the UK, Singapore, Sweden, and India. It contains FLip mutations in the spike protein in RBD (L455F and F456L). The risk assessment of the variant by WHO shows it has increased transmission, immune escape, and antibody escape due to the mutations. The article illustrated that FLip mutations in RBD (L455F and F456L) are responsible for augmented transmission and immune and antibody escape.

Current landscape of long COVID clinical trials.

Long COVID was reported as a multi-systemic condition after the infection of SARS-CoV-2, and more than 65 million people are suffering from this disease. It has been noted that around 10% of severe SARS-CoV-2 infected individuals are suffering from the enduring effects of long COVID. The symptoms of long COVID have also been noted in several mild or asymptomatic SARS-CoV-2 infected individuals. While limited reports on clinical trials investigating new therapeutics for long COVID exist, there is an abundance of scattered information available regarding these trials. This review explores the extensive literature search, and complete clinical trial database search to map the current status of long COVID clinical trials worldwide. The study listed about 110 long COVID clinical trials. In addition to conducting extensive long COVID clinical trials, we have comprehensively presented an overview of the condition, its symptoms, notable manifestations, associated clinical trials, the unique challenges it poses, and our recommendations for addressing long COVID.

SARS-CoV-2 Omicron Spike shows strong binding affinity and favourable interaction landscape with the TLR4/MD2 compared to other variants.

Emergences of SARS-CoV-2 variants have made the pandemic more critical. Toll-like receptor 4 (TLR4) recognizes the molecular patterns of pathogens and activates the production of proinflammatory cytokines to restrain the infection. We have identified a molecular basis of interaction between the Spike and TLR4 of SARS-CoV-2 and its present and past VOCs (variant- of concern) through in silico analysis. The interaction of wild type Spike with TLR4 showed 15 number hydrogen bonds formation. Similarly, the Alpha variants' Spike with the TLR4 has illustrated that 14 hydrogen bonds participated in the interaction. However, the Delta Spike and TLR4 interaction interface showed that 17 hydrogen bonds were formed during the interaction. Furthermore, Omicron S-glycoprotein and TLR4 interaction interface was depicted (interaction score: -170.3), and 16 hydrogen bonds were found to have been formed in the interaction. Omicron S-glycoprotein shows stronger binding affinity with the TLR4 than wild type, Alpha, and Delta variants. Similarly, the Alpha Spike shows higher binding affinity with TLR4 than the wild type and Delta variant. Now, it is an open question of the molecular basis of the interaction of Spike and TLR4 and the activated downstream signaling events of TLR4 for SARS-CoV-2 and its variants.

Regulatory role of miRNAs in the human immune and inflammatory response during the infection of SARS-CoV-2 and other respiratory viruses: A comprehensive review.

miRNAs are single-stranded ncRNAs that act as regulators of different human body processes. Several miRNAs have been noted to control the human immune and inflammatory response during severe acute respiratory infection syndrome (SARS-CoV-2) infection. Similarly, many miRNAs were upregulated and downregulated during different respiratory virus infections. Here, an attempt has been made to capture the regulatory role of miRNAs in the human immune and inflammatory response during the infection of SARS-CoV-2 and other respiratory viruses. Firstly, the role of miRNAs has been depicted in the human immune and inflammatory response during the infection of SARS-CoV-2. In this direction, several significant points have been discussed about SARS-CoV-2 infection, such as the role of miRNAs in human innate immune response; miRNAs and its regulation of granulocytes; the role of miRNAs in macrophage activation and polarisation; miRNAs and neutrophil extracellular trap formation; miRNA-related inflammatory response; and miRNAs association in adaptive immunity. Secondly, the miRNAs landscape has been depicted during human respiratory virus infections such as human coronavirus, respiratory syncytial virus, influenza virus, rhinovirus, and human metapneumovirus. The article will provide more understanding of the miRNA-controlled mechanism of the immune and inflammatory response during COVID-19, which will help more therapeutics discoveries to fight against the future pandemic.

Blueprint of differentially expressed genes reveals the dynamic gene expression landscape and the gender biases in long COVID.

BACKGROUND: Long COVID has appeared as a significant global health issue and is an extra burden to the healthcare system. It affects a considerable number of people throughout the globe. However, substantial research gaps have been noted in understanding the mechanism and genomic landscape during the long COVID infection. A study has aimed to identify the differentially expressed genes (DEGs) in long COVID patients to fill the gap. METHODS: We used the RNA-seq GEO dataset acquired through the GPL20301 Illumina HiSeq 4000 platform. The dataset contains 36 human samples derived from PBMC (Peripheral blood mononuclear cells). Thirty-six human samples contain 13 non-long COVID individuals' samples and 23 long COVID individuals' samples, considered the first direction analysis. Here, we performed two-direction analyses. In the second direction analysis, we divided the dataset gender-wise into four groups: the non-long COVID male group, the long COVID male group, the non-long COVID female group, and the long COVID female group. RESULTS: In the first analysis, we found no gene expression. In the second analysis, we identified 250 DEGs. During the DEG profile analysis of the non-long COVID male group and the long COVID male group, we found three upregulated genes: IGHG2, IGHG4, and MIR8071-2. Similarly, the analysis of the non-long COVID female group and the long COVID female group reveals eight top-ranking genes. It also indicates the gender biases of differentially expressed genes among long COVID individuals. We found several DEGs involved in PPI and co-expression network formation. Similarly, cluster enrichment and gene list enrichment analysis were performed, suggesting several genes are involved in different biological pathways or processes. CONCLUSIONS: This study will help better understand the gene expression landscape in long COVID. However, it might help the discovery and development of therapeutics for long COVID.

A Domain-Specific Next-Generation Large Language Model (LLM) or ChatGPT is Required for Biomedical Engineering and Research.

Large language models or ChatGPT have recently gained extensive media coverage. At the same time, the use of ChatGPT has increased deistically. Biomedical researchers, engineers, and clinicians have shown significant interest and started using it due to its diverse applications, especially in the biomedical field. However, it has been found that ChatGPT sometimes provided incorrect or partly correct information. It is unable to give the most recent information. Therefore, we urgently advocate a domain-specific next-generation, ChatBot for biomedical engineering and research, providing error-free, more accurate, and updated information. The domain-specific ChatBot can perform diversified functions in biomedical engineering, such as performing innovation in biomedical engineering, designing a medical device, etc. The domain-specific artificial intelligence enabled device will revolutionize biomedical engineering and research if a biomedical domain-specific ChatBot is produced.

Need an AI-Enabled, Next-Generation, Advanced ChatGPT or Large Language Models (LLMs) for Error-Free and Accurate Medical Information.

Recently, the interest in AI-guided ChatGPT has increased day-to-day, and different applications have been explored, including the medical field. The publication number is also increasing. At the same time, people are trying to get medical information from this Chartbot. However, researchers found that ChatGPT also provides partly correct or false information. Therefore, in this article, we urge the researchers to develop an AI-enabled, next-generation, advanced ChatGPT or large language models (LLMs) so that people can get accurate and error-free medical information.