A model of spirituality for ageing Muslims

Spirituality’s influence on general well-being and its association with healthy ageing has been studied extensively. However, a different perspective has to be brought in when dealing with spirituality issues of ageing Muslims. Central to this perspective is the intertwining of religion and spirituality in Islam. This article will contribute to the understanding of the nature of Islamic spirituality and its immense importance in the life of a practicing ageing Muslim. Consequently, it will help care providers to include appropriate spiritual care in the care repertoire of a Muslim care recipient. It is assumed that the framework for a model of spirituality based on Islamic religious beliefs would help contextualise the relationship between spirituality and ageing Muslims. Not only challenges, but also the opportunities that old age provides for charting the spiritual journey have underpinned this model

Accuracy of MRI in Diagnosis of Invasive Placenta by Taking Per Operative Findings as Gold Standard

Objective: To assess the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting invasive placentas using per-operative findings as the gold standard.Methodology: A prospective cross-sectional study was conducted in the diagnostic radiology department of KRL General Hospital Islamabad during Oct 2019 to Sep 2021. Sixty prenatal individuals were identified as having a high risk of invasive placenta and underwent MRI (Phillips 1.5 T) to confirm the diagnosis. A trainee radiologist and a consultant radiologist reviewed the images. The MRI's sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was calculated using a 2×2 contingency tables. Results: Ten cases of invasive placenta were detected postoperatively (gold standard). The MRI had a sensitivity of 90%, a specificity of 93%, a positive predictive value of 90%, a negative predictive value of 90%, and an accuracy of 92.3 percent, respectively. Conclusion: The study concluded that magnetic resonance imaging (MRI) offers a good diagnostic accuracy and is a reproducible technology for prenatal identification of invasive placentas

Expression variation of OGG1 and HPRT gene and DNA damage in arsenic exposed industrial workers

Arsenic exposure alters redox balance, induces DNA damage, and deregulates many genes. OGG1 gene involved in base repair mechanism, for excision of 8-oxoguanine (8-oxoG) from DNA formed as a result of accumulation of ROS in cell. HPRT gene encode transferase enzymes involved in purine recycling mechanism. The main focus of the study was to evaluate the expression variation in HPRT, OGG1 gene expression, and DNA damage of industrial workers. Blood samples of 300 occupational workers were collected from welding, brick kiln, furniture, pesticide, and paint industry (n = 60/industry) to evaluate the expression variation in HPRT, OGG1 gene expression, and DNA damage in blood cells by comet assay along with age and gender matched 300 control individuals. Blood arsenic content was higher (P\u3c0.001) in an industrial group compared to the control. OGG1 and HPRT expression were (P\u3c0.05) downregulated in exposed workers compared to controls. Spearman correlation analysis showed a significant positive correlation between HPRT vs OGG1 (P\u3c 0.0001) in exposed workers compared to controls. Altered expression of both genes was observed between workers with \u3c25years and \u3e25years of age as well as between workers with \u3c10years and \u3e10year exposure. Reduced expression (P\u3c0.05) of both genes and a high extent of DNA damage was evident in exposed smokers compared to respective non-smokers. DNA fragmentation was higher (P\u3c0.05) in the furniture, welding and brick kiln group compared to control, and other industries. The present study suggests that altered expression of OGG1 and HPRT gene induce oxidative stress, showed a negative impact on the recycling of purines leading to DNA damage which increase the vulnerability of workers to carcinogenicity

Automated Detection of Drowsiness using Machine Learning Approach

Nowadays, there is a steady rise in the number of traffic accidents. The primary causes of these accidents are impaired driving due to alcohol consumption and driver fatigue. The primary goal is to create a system capable of measuring a driver’s degree of sleepiness. If drowsiness is identified, a warning will be sent out via integration with an alert warning system and text message system. Drowsiness detection is built using OpenCV, Python, and Machine Learning. A significant number of annotated driver images depicting different levels of drowsiness, alongside images of diverse driving scenarios and lighting conditions, were utilized in the research to enhance the dataset. The system for detecting driver drowsiness provides a viable method to avert car accidents resulting from driver tiredness. It examines the driver’s eye and alerts them when necessary. Further improvements could increase the alarm system’s accuracy by minimizing the number of false warnings

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS‐COV‐2 by Comprehensive Immunoinformatic and Molecular Modelling Approach

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the world health organization declared it pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. In this urgency situation, development of SARS-CoV-2 based vaccines is immediately required. Immunoinformatic and molecular modelling are generally used time-efficient methods to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines is proved to be a promising immunization strategy against viruses and pathogens, which induce more comprehensive protective immunity. The current study demonstrated a comprehensive in-silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in-silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in E. Coli. Despite this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can present to be a better prophylactic solution against COVID-19.status: publishe

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the World Health Organization has declared it a pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. The urgency of the situation requires the development of SARS-CoV-2-based vaccines. Immunoinformatic and molecular modelling are time-efficient methods that are generally used to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines has proved to be a promising immunization strategy against viruses and pathogens, thus inducing more comprehensive protective immunity. The current study demonstrated a comprehensive in silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in Escherichia coli. Despite that this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can be present as a better prophylactic solution against COVID-19.status: publishe

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the World Health Organization has declared it a pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. The urgency of the situation requires the development of SARS-CoV-2-based vaccines. Immunoinformatic and molecular modelling are time-efficient methods that are generally used to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines has proved to be a promising immunization strategy against viruses and pathogens, thus inducing more comprehensive protective immunity. The current study demonstrated a comprehensive in silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in Escherichia coli. Despite that this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can be present as a better prophylactic solution against COVID-19

Identification of NS2B-NS3 Protease Inhibitors for Therapeutic Application in ZIKV Infection: A Pharmacophore-Based High-Throughput Virtual Screening and MD Simulations Approaches

Zika virus (ZIKV) pandemic and its implication in congenital malformations and severe neurological disorders had created serious threats to global health. ZIKV is a mosquito-borne flavivirus which spread rapidly and infect a large number of people in a shorter time-span. Due to the lack of effective therapeutics, this had become paramount urgency to discover effective drug molecules to encounter the viral infection. Various anti-ZIKV drug discovery efforts during the past several years had been unsuccessful to develop an effective cure. The NS2B-NS3 protein was reported as an attractive therapeutic target for inhibiting viral proliferation, due to its central role in viral replication and maturation of non-structural viral proteins. Therefore, the current in silico drug exploration aimed to identify the novel inhibitors of Zika NS2B-NS3 protease by implementing an e-pharmacophore-based high-throughput virtual screening. A 3D e-pharmacophore model was generated based on the five-featured (ADPRR) pharmacophore hypothesis. Subsequently, the predicted model is further subjected to the high-throughput virtual screening to reveal top hit molecules from the various small molecule databases. Initial hits were examined in terms of binding free energies and ADME properties to identify the candidate hit exhibiting a favourable pharmacokinetic profile. Eventually, molecular dynamic (MD) simulations studies were conducted to evaluate the binding stability of the hit molecule inside the receptor cavity. The findings of the in silico analysis manifested affirmative evidence for three hit molecules with −64.28, −55.15 and −50.16 kcal/mol binding free energies, as potent inhibitors of Zika NS2B-NS3 protease. Hence, these molecules holds the promising potential to serve as a prospective candidates to design effective drugs against ZIKV and related viral infections