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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.

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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.

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Failure rate after chronic rotator cuff repair is considerably high. Moreover, diabetes mellitus is known as a compromising factor of rotator cuff tear. The effect of Polydeoxyribonucleotide (PDRN) and polynucleotide (PN) on tendon healing and fatty infiltration is unclear as tissue regeneration activator in diabetic state. Therefore, a diabetic rat model with chronic rotator cuff tear was made for mechanical, histologic and blood tests. In the animal study using a diabetic rat cuff repair model, the administration of PDRN and PN increased the load to failure of repaired cuffs and improved tendon healing and decreased fatty infiltration. Also, the plasma levels of vascular endothelial growth factor and fibroblast growth factor were elevated in PDRN and PN administrated groups. We concluded that PDRN and PN appear to boost tendon recovery and reduce the presence of fatty infiltration following cuff repair in diabetic state. Also, PN showed a later onset and a longer duration than PDRN associated with the mean plasma growth factors.

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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.

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BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is the central nervous system demyelinating disease differentiated from multiple sclerosis by the presence of anti-aquaporin 4-antibody (AQP4-ab), which is sometimes accompanied by non-organ-specific autoantibodies. METHODS: We prospectively collected clinical information and profiles of non-organ-specific autoantibodies such as fluorescent antinuclear (FANA), anti-Sjögren's syndrome A (SSA)/Ro, anti-SS B (SSB)/La, anti-neutrophil cytoplasmatic (ANCA), lupus anticoagulant (LA), anti-cardiolipin (ACA), anti-double-stranded DNA (dsDNA), rheumatoid factor (RF), anti-thyroperoxidase, and anti-thyroglobulin antibodies in patients with NMOSD. Clinical characteristics and laboratory findings of patients with NMOSD with or without autoantibodies were analyzed. Cox proportional hazard models were used to identify independent risk factors predicting high disability in patients with NMOSD. RESULTS: A total of 158 patients with NMOSD (Female: Male = 146:12; age, 36.11 ± 14.7) were included. FANA was observed most frequently (33.3 %), followed by anti-SSA (28.6 %), anti-SSB (10.0 %), RF (8.5 %), anti-dsDNA (7.0 %), LA (4.7 %), ACA (4.8 %), and ANCA (2.4 %). High disability (Expanded Disability Status Scale (EDSS) score ≥ 6) was observed more frequently in patients with RF (45.5 %) than in those without RF (14.5 %) (p = 0.02). RF was a significant predictive factor for the high disability (hazard ratio [HR], 3.763; 95 % confidence interval [CI], 1.086-13.038; p = 0.037), age at onset (HR, 1.093; 95 % CI, 1.05-1.14; p ≤0.001), and annual relapse rate (ARR) (HR, 4.212; 95 % CI, 1.867-9.503; p = 0.001). CONCLUSION: Organ-specific and non-organ-specific autoantibodies are frequently observed in Korean patients with AQP4-ab-positive NMOSD. RF may be an independent predictor of high disability, along with age at onset and ARR.

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Background: Ankle fusion is considered a treatment of choice for end-stage ankle arthritis when a total ankle replacement procedure is not indicated. However, the potential risk of secondary arthritis in the adjacent joint after ankle fusion raises arguments on whether preserving the adjacent joint during an isolated tibiotalar (TT) fusion brings about any future benefits with regard to pain and gait discomfort. In this study, we intended to present midterm results following TT or tibiotalocalcaneal (TTC) fusion using an Ilizarov external fixator and to investigate whether spontaneous fusion occurred in the subtalar or midtarsal joint. Methods: This is a retrospective observational study. Medical records of patients who underwent TT or TTC fusion using an Ilizarov external fixator for substantial bone defects around the ankle joint between 1994 and 2018 were manually searched. Forty-one patients were included and the status of the joints adjacent to the fusion site was evaluated in radiographic examinations. Results: Of the 34 patients who underwent TT fusion, 30 patients (88.3%) had a spontaneous fusion in the adjacent joints. Specifically, 11 patients (29.4%) had subtalar joint fusion and 19 patients (55.9%) had both midtarsal joint and subtalar joint fusion. In TTC fusion, the midtarsal joint was spontaneously fused in all 7 patients. Conclusions: In this study, we observed spontaneous adjacent joint fusion following TT or TTC fusion using an Ilizarov external fixator for substantial bone defects around the ankle joint. Although a careful approach should be made since patients treated in this study may not represent typical candidates that need primary joint-sacrificing procedures, we believe that this study may draw attention from surgeons concerned about the fate of the adjacent joint status after TT or TTC fusion.

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Inhibition of lipid synthesis in sebocytes is essential for acne treatments. The effects of natural product-derived substances on lipid synthesis are unknown. This study investigated the effects of water extract of Mangifera indica leaves (WEML) on lipid synthesis in human sebocytes. Sebocyte differentiation in low serum conditions increased lipid accumulation and proliferator-activated receptor γ expression. WEML treatment significantly inhibited lipid accumulation and adipogenic mRNA expression in sebocytes. Mangiferin, a bioactive compound in WEML, also reduced lipid accumulation and adipogenic mRNA expression via the AKT pathway. Thus, WEML and mangiferin effectively inhibit lipid synthesis in sebocytes, showing promise for acne treatment.

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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.

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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.

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Acute stress caused by short-term exposure to deleterious chemicals can induce the aggregation of RNA-binding proteins (RBPs) in the cytosol and the formation of stress granules (SGs). The cytoplasmic RBP, Ras GTPase-activating protein-binding protein 1 (G3BP1) is a critical organizer of SG, and its aggregation is considered a hallmark of cellular stress. However, assembly of SG is a highly dynamic process that involves RBPs; hence, existing methods based on fixation processes or overexpression of RBPs exhibit limited efficacy in detecting the assembly of SG under stress conditions. In this study, we established a G3BP1- Green fluorescent protein (GFP) reporter protein in a human neuroblastoma cell line to overcome these limitations. GFP was introduced into the G3BP1 genomic sequence via homologous recombination to generate a G3BP1-GFP fusion protein and further analyze the aggregation processes. We validated the assembly of SG under stress conditions using the G3BP1-GFP reporter system. Additionally, this system supported the evaluation of bisphenol A-induced SG response in the established human neuroblastoma cell line. In conclusion, the established G3BP1-GFP reporter system enables us to monitor the assembly of the SG complex in a human neuroblastoma cell line in real time and can serve as an efficient tool for assessing potential neurotoxicity associated with short-term exposure to chemicals.

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Background: Myelin oligodendrocyte glycoprotein antibody (MOG) immunoglobulin G (IgG)-associated disease (MOGAD) has clinical and pathophysiological features that are similar to but distinct from those of aquaporin-4 antibody (AQP4-IgG)-positive neuromyelitis optica spectrum disorders (AQP4-NMOSD). MOG-IgG and AQP4-IgG, mostly of the IgG1 subtype, can both activate the complement system. Therefore, we investigated whether the levels of serum complement components, regulators, and activation products differ between MOGAD and AQP4-NMOSD, and if complement analytes can be utilized to differentiate between these diseases. Methods: The sera of patients with MOGAD (from during an attack and remission; N=19 and N=9, respectively) and AQP4-NMOSD (N=35 and N=17), and healthy controls (N=38) were analyzed for C1q-binding circulating immune complex (CIC-C1q), C1 inhibitor (C1-INH), factor H (FH), C3, iC3b, and soluble terminal complement complex (sC5b-9). Results: In attack samples, the levels of C1-INH, FH, and iC3b were higher in the MOGAD group than in the NMOSD group (all, p<0.001), while the level of sC5b-9 was increased only in the NMOSD group. In MOGAD, there were no differences in the concentrations of complement analytes based on disease status. However, within AQP4-NMOSD, remission samples indicated a higher C1-INH level than attack samples (p=0.003). Notably, AQP4-NMOSD patients on medications during attack showed lower levels of iC3b (p<0.001) and higher levels of C3 (p=0.008), C1-INH (p=0.004), and sC5b-9 (p<0.001) compared to those not on medication. Among patients not on medication at the time of attack sampling, serum MOG-IgG cell-based assay (CBA) score had a positive correlation with iC3b and C1-INH levels (rho=0.764 and p=0.010, and rho=0.629 and p=0.049, respectively), and AQP4-IgG CBA score had a positive correlation with C1-INH level (rho=0.836, p=0.003). Conclusions: This study indicates a higher prominence of complement pathway activation and subsequent C3 degradation in MOGAD compared to AQP4-NMOSD. On the other hand, the production of terminal complement complexes (TCC) was found to be more substantial in AQP4-NMOSD than in MOGAD. These findings suggest a strong regulation of the complement system, implying its potential involvement in the pathogenesis of MOGAD through mechanisms that extend beyond TCC formation.

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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.

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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.

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Quantitative PCR (qPCR) is the gold standard for detecting nucleic acid sequences specific to the target pathogen. For COVID-19 diagnosis, several molecular assays have been developed. In this study, we present an optimization strategy for the measurement of SARS-CoV-2 RNA via multiplex qPCR and digital PCR (dPCR). Compared to qPCR, both droplet and chip-based dPCR, which are known to be more sensitive and accurate, showed a better resilience to suboptimal assay compositions and cycling conditions following the proposed optimizations. In particular, the formation of heterodimers among assays greatly interfered with qPCR results, but only minimally with dPCR results. In dPCR, existing heterodimers lowered the PCR efficiency, producing a dampened fluorescent signal in positive partitions. This can be corrected by adjusting the PCR cycling conditions, after which dPCR shows the capability of measuring the expected copy number. In addition, we present a process to improve the existing RdRp assay by correcting the primer sequences and matching the melting temperature, ultimately producing highly sensitive and robust assays. The results of this study can reduce the cost and time of SARS-CoV-2 diagnosis while increasing accuracy. Furthermore, our results suggest that dPCR is a reliable method for the accurate measurement of nucleic acid targets.

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OBJECTIVES: This study aimed to assess the impact of the reimbursement regulation of medical devices (Regulation), introduced by the National Health Insurance Administration (NHIA) in 2013, on patients' access to innovative medical devices in Taiwan. METHODS: Analysis of the amount of time needed from application for NHIA reimbursement for new medical devices to receiving the decision from NHIA was done using the nonreimbursement product list featured on the NHIA website. Additionally, Welch analysis of variance was used to compare the amount of time it took from application to NHIA with reimbursement decisions made by the NHIA for different nonreimbursement code categories. Further, related Pharmaceutical Benefit Reimbursement Scheme meeting minutes were analyzed to obtain more detailed information concerning medical devices' reimbursement or not. RESULTS: From December 2012 to June 2021, the overall reimbursement percentage was 56.7%, and the average amount of time between application and reimbursement was 856.7 ± 474.7 days. The mandatory reimbursement rate was about 45%. NHIA reimbursement decisions as special medical devices also take a longer amount of time, because the applicants need to agree to the decision (P < .05). The NHIA decision-making process for nonreimbursement medical devices requires a significantly longer amount of time than for general materials (eg, suture, etc) decisions. CONCLUSIONS: Although the Regulation resolves payment issues, it also increases the amount of time to reach reimbursement decisions, thus hindering patient access to innovative medical devices. The study suggests that the review process needs to be simplified concerning reimbursement notification, using local real-world data to support reimbursement decisions.

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In-memory computing represents an effective method for modeling complex physical systems that are typically challenging for conventional computing architectures but has been hindered by issues such as reading noise and writing variability that restrict scalability, accuracy, and precision in high-performance computations. We propose and demonstrate a circuit architecture and programming protocol that converts the analog computing result to digital at the last step and enables low-precision analog devices to perform high-precision computing. We use a weighted sum of multiple devices to represent one number, in which subsequently programmed devices are used to compensate for preceding programming errors. With a memristor system-on-chip, we experimentally demonstrate high-precision solutions for multiple scientific computing tasks while maintaining a substantial power efficiency advantage over conventional digital approaches.

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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.

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Under various cellular stress conditions, including exposure to toxic chemicals, RNA-binding proteins (RBPs), including Ras GTPase-activating protein-binding protein 1 (G3BP1), aggregate and form stress granule complexes, which serve as hallmarks of cellular stress. The existing methods for analyzing stress granule assembly have limitations in the rapid detection of dynamic cellular stress and ignore the effects of constitutively overexpressed RBP on cellular stress and stress-related processes. Therefore, to overcome these limitations, we established a G3BP1-GFP reporter in a human lung epithelial cell line using CRISPR/Cas9-based knock-in as an alternative system for stress granule analysis. We showed that the G3BP1-GFP reporter system responds to stress conditions and forms a stress granule complex similar to that of native G3BP1. Furthermore, we validated the stress granule response of an established cell line under exposure to various household chemicals. Overall, this novel G3BP1-GFP reporter human lung cell system is capable of monitoring stress granule dynamics in real time and can be used for assessing the lung toxicity of various substances in vitro.

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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.

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Modern biological science is trying to solve the fundamental complex problems of molecular biology, which include protein folding, drug discovery, simulation of macromolecular structure, genome assembly, and many more. Currently, quantum computing (QC), a rapidly emerging technology exploiting quantum mechanical phenomena, has developed to address current significant physical, chemical, biological issues, and complex questions. The present review discusses quantum computing technology and its status in solving molecular biology problems, especially in the next-generation computational biology scenario. First, the article explained the basic concept of quantum computing, the functioning of quantum systems where information is stored as qubits, and data storage capacity using quantum gates. Second, the review discussed quantum computing components, such as quantum hardware, quantum processors, and quantum annealing. At the same time, article also discussed quantum algorithms, such as the grover search algorithm and discrete and factorization algorithms. Furthermore, the article discussed the different applications of quantum computing to understand the next-generation biological problems, such as simulation and modeling of biological macromolecules, computational biology problems, data analysis in bioinformatics, protein folding, molecular biology problems, modeling of gene regulatory networks, drug discovery and development, mechano-biology, and RNA folding. Finally, the article represented different probable prospects of quantum computing in molecular biology.

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