The world is fascinated to see how technology evolves each passing day. All too soon, there's an emerging technology that is trending around us, and it is no other technology than smart wearable technology. Less attention is paid to the data that our bodies are radiating and communicating to us, but with the timely arrival of wearable sensors, we now have numerous devices that can be tracking and collecting the data that our bodies are radiating. Apart from numerous benefits that we derive from the functions provided by wearable technology such as monitoring of our fitness levels, etc., one other critical importance of wearable technology is helping the advancement of artificial intelligence (AI) and machine learning (ML). Machine learning thrives on the availability of massive data and wearable technology which forms part of the internet of things (IoT) generates megabytes of data every single day. The data generated by these wearable devices are used as a dataset for the training and learning of machine learning models. Through the analysis of the outcome of these machine learning models, scientific conclusions are made.
One of the significant causes of morbidity and mortality among young children in developing nations is acute respiratory tract infections (ARTIs). It is also highly contagious, widely prevalent, and transmissible from person to person. It risks young children, the elderly, and those with immune system disorders. Acute respiratory infections are thought to cause 2.6 million child deaths annually worldwide, according to the World Health Organization (WHO) [1]. Infections in children with human metapneumovirus (hMPV) and bocavirus (HBoV) are linked to a high prevalence of ARTIs. It has been determined that hMPV is the second-leading cause of infant bronchiolitis, after the respiratory syncytial virus (RSV), of upper and lower respiratory tract infections. Although HBoV was first discovered in children's airways, the high detection rates of other viral pathogens and the discovery of HBoV in stool raise doubts about the virus's significance in respiratory tract infections. According to the published literature, only a few studies have identified ARTIs or demonstrated the importance of early diagnosis and treatment of ARTIs. This review article aims to thoroughly explain the aetiology, epidemiology, clinical characteristics, diagnostic approaches, and management of hMPV and HBoV.
Introduction: The Rubella virus has a worldwide occurrence and congenital Rubella syndromes are widely recognized as an emerging infection in several parts of the world. Miscarriage, perinatal mortality, and stillbirth can develop in pregnancy during the first trimester. The most frequent techniques for laboratory diagnosis of Rubella virus infection are IgM and IgG-based serological detection methods. Such emerging viral and bacterial pathogen emphasizes the development of fast diagnostic devices; there is a need for enhanced and quicker methods. Materials and Methods: Search for peptide vaccine with specific T and B-cell epitopes was identified through bioinformatics-based approaches. These were identified utilizing available Rubella virus E1 glycoprotein sequence databases. The outer-membrane glycoprotein, E1 is a target protein for the prediction of best antigens. Results: Using BepiPred2 program, the potential B-cell epitope PFCNTPHGQLEVQVPPDPGD with high conservation among E1 glycoprotein of rubella virus and the maximum surface exposed residues was identified. Using IEDB, NetMHCpan, and NetCTL programs, T-cell epitope RPVALPRAL was identified. Predicted epitopes were found to have promiscuous class-I major histocompatibility complex binding affinity to major histocompatibility complex super types, antigenicity scores, and high proteasomal cleavage. The three-dimensional modeled structures were created using I-TASSER online server for highlighting the predicted T- and B- cell epitopes. Conclusion: The predicted T and B cell epitope could be used for the development of immunoglobulin assay and vaccine candidate peptide.
TORCH-S is a medical acronym for a set of perinatal infections with known adverse impact on fetal developmental and pregnancy outcome. This includes infections with , Rubella virus, Cytomegalovirus, Herpes simplex virus (1 and 2) and (Syphilis). TORCH-S infections group of prenatal illnesses that have been linked to adverse outcomes in fetal development and pregnancy. Infections caused by TORCH-S can affect anybody, including children, men, and non-pregnant women. However, because they may be passed to the embryo while it is still in the womb, major fetal problems can arise if a mother is exposed during the first 5 months of pregnancy. The cornerstone of congenital infection prevention is the primary prevention of maternal infections during pregnancy. Early identification of TORCH-S infection will help in appropriate treatment and management of these infections.
Human Parvovirus B19 (HPV-B19) infections are reported from different parts of the globe. The infection occurs in all age groups; however, most infections occur in childhood. There is evidence of exposure to the virus in about 80% of adults when screened for specific IgG. HPV-B19 is incriminated in several conditions like erythema infectious, aplastic crisis, hydrops fetalis and arthropathy. HPV-B19 is a cause of the Fifth disease (erythema infectious); it could also cause a febrile illness with or without rash in adults. Many adults especially women develop arthropathy and the condition could be chronic following a febrile illness. Patients (adults) with End Stage Renal Disease (ESRD) are prone to develop aplastic crisis or chronic anemia [1]. This review article aims to comprehensively describe the etiology, epidemiology, clinical features, diagnostic methods, and treatment in the management of HPV-B19.
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