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| 1 | An insight into the diagnosis and pathogenesis of hepatitis C virus infection显示文摘This review focuses on research findings in the area of diagnosis and pathogenesis of hepatitis C virus(HCV)infection over the last few decades.The information based on published literature provides an update on these two aspects of HCV.HCV infection,previously called blood transmitted non-A,non-B infection,is prevalent globally and poses a serious public health problem worldwide.The diagnosis of HCV infection has evolved from serodetection of non-specific and low avidity anti-HCV antibodies to detection of viral nucleic acid in serum using the polymerase chain reaction(PCR)technique.Current PCR assays detect viral nucleic acid with high accuracy and the exact copy number of viral particles.Moreover,multiplex assays using real-time PCR are available for identification of HCV-genotypes and their isotypes.In contrast to previous methods,the newly developed assays are not only fast and eco-nomic,but also resolve the problem of the window period as well as differentiate present from past infection.HCV is a non-cytopathic virus,thus,its pathogenesis is regulated by host immunity and metabolic changes including oxidative stress,insulin resistance and hepatic steatosis.Both innate and adaptive immunity play an important role in HCV pathogenesis.Cytotoxic lymphocytes demonstrate crucial activity during viral eradication or viral persistence and are influenced by viral proteins,HCV-quasispecies and several metabolic factors regulating liver metabolism.HCV pathogenesis is a very complex phenomenon and requires further study to determine the other factors involved. | Mohammad Irshad Dhananjay Singh Mankotia Khushboo Irshad | 2013 | World Journal of Gastroenterology2013，19，44： | 52 |
| 2 | Molecular basis of hepatocellular carcinoma induced by hepatitis C virus infection显示文摘Present study outlines a comprehensive view of published information about the underlying mechanisms operational for progression of chronic hepatitis C virus(HCV) infection to development of hepatocellular carcinoma(HCC). These reports are based on the results of animal experiments and human based studies. Although, the exact delineated mechanism is not yet established, there are evidences available to emphasize the involvement of HCV induced chronic inflammation, oxidative stress, insulin resistance, endoplasmic reticulum stress, hepato steatosis and liver fibrosis in the progression of HCV chronic disease to HCC. Persistent infection with replicating HCV not only initiates several liver alterations but also creates an environment for development of liver cancer. Various studies have reported that HCV acts both directly as well as indirectly in promoting this process. Whereas HCV related proteins, like HCV core, E1, E2, NS3 and NS5A, modulate signal pathways dysregulating cell cycle and cell metabolism, the chronic infection produces similar changes in an indirect way. HCV is an RNA virus and does not integrate with host genome and therefore, HCV induced hepatocarcinogenesis pursues a totally different mechanism causing imbalance between suppressors and proto-oncogenes and genomic integrity. However, the exact mechanism of HCC inducement still needs a full understanding of various steps involved in this process. | Mohammad Irshad Priyanka Gupta Khushboo Irshad | 2017 | World Journal of Hepatology2017，9，36： | 7 |
| 3 | Torque teno virus:Its prevalence and isotypes in North India显示文摘AIM: To investigate the prevalence and genotype dis-tribution of Torque teno virus (TTV) in patients with different liver diseases and chronic renal failure treated at a referral hospital in North India. METHODS: Whereas prevalence of TTV was based on amplification of conserved region of ORF2 of TTV genome,the genotyping of TTV was carried out using restriction fragment length polymorphism (RFLP) procedure on the N22 region of ORF1. RESULTS: TTV-DNA was detected in 137 of 513 (26.7%) patients with liver diseases and 38 of 65 (58.5%) patients with chronic renal failure. TTV was also detected in 27% of healthy controls. The sequence analysis of the PCR product from 10 randomly selected cases failed to show a significant sequence divergence when compared with that of the TRM1 isolate of TTV genotype 1. The results of genotyping in 55 randomly selected patients showed the presence of genotype 1 (G1) in 53 (96.4%) and genotype 2 (G2) in 2 cases (3.6%),respectively. Other genotypes were not identified in this patient subgroup,suggesting that G1 is predominant in this area. The results of genotyping by RFLP were also supported by phylogenetic tree analysis,where G1 was found to be the major genotype. CONCLUSION: These results indicate that TTV is moderately present in Indian patients,with G1 to be the major genotype in North India. The pathogenicity and etiological role of TTV in different diseases is still a question mark and warrant further studies. | Mohammad Irshad Shiwani Singh Khushboo Irshad Sanjay Kumar Agarwal Yogendra Kumar Joshi | 2008 | World Journal of Gastroenterology2008，14，39： | 5 |
| 4 | Multiplex qPCR for serodetection and serotyping of hepatitis viruses: A brief review显示文摘The present review describes the current status of multiplex quantitative real time polymerase chain reaction(q PCR) assays developed and used globally for detection and subtyping of hepatitis viruses in body fluids. Several studies have reported the use of multiplex q PCR for the detection of hepatitis viruses, including hepatitis A virus(HAV), hepatitis B virus(HBV), hepatitis C virus(HCV), hepatitis D virus(HDV), and hepatitis E virus(HEV). In addition, multiplex q PCR has also been developed for genotyping HBV, HCV, and HEV subtypes. Although a single step multiplex q PCR assay for all six hepatitis viruses, i.e., A to G viruses, is not yet reported, it may be available in the near future as the technologies continue to advance. All studies use a conserved region of the viral genome as the basis of amplification and hydrolysis probes as the preferred chemistries for improved detection. Based on a standard plot prepared using varying concentrations of template and the observed threshold cycle value, it is possible to determine the linear dynamic range and to calculate an exact copy number of virus in the specimen. Advantages of multiplex q PCR assay over singleplex or other molecular techniques in samples from patients with co-infection include fast results, low cost, and a single step investigation process. | Mohammad Irshad Priyanka Gupta Dhananjay Singh Mankotia Mohammad Ahmad Ansari | 2016 | World Journal of Gastroenterology2016，22，20： | 5 |
| 5 | HCV-Core Region: Its Significance in HCV-Genotyping and Type Dependent Genomic Expression显示文摘 | Mohammad Ansari Raghavendra Lingaiah Mohammad Irshad | 2012 | Macedonian Journal of Medical Sciences2012，，1： | 1 |
| 6 | Novel single‐step multiplex real‐time polymerase chain reaction assay for simultaneous quantification of hepatitis virus A , B , C , and E in serum显示文摘 | Mohammad Irshad Mohammad Ahmad Ansari Khushboo Irshad Raghavendra Lingaiah | 2013 | J Gastroenterol Hepatol2013，，12： | 1 |
| 7 | Purification and propertiesof an α-amylase protein-inhibitor from arachis hyogaea seeds显示文摘 | Mohammad Irshad Chandra B Sharama | 1981 | Biochimica et Biophysica Acta1981，659，： | 1 |
| 8 | Expression of the full-length HCV core subgenome from HCV gentoype-1a and genotype-3a and evaluation of the antigenicity of translational products显示文摘 | Mohammad A. Ansari Mohammad Irshad Sanjay Kumar Agarwal Kunzang Chosdol | 2013 | European Journal of Gastroenterology & Hepatology2013，，7： | 1 |
| 9 | Smart MobiNet:A Deep Learning Approach for Accurate Skin Cancer Diagnosis显示文摘The early detection of skin cancer,particularly melanoma,presents a substantial risk to human health.This study aims to examine the necessity of implementing efficient early detection systems through the utilization of deep learning techniques.Nevertheless,the existing methods exhibit certain constraints in terms of accessibility,diagnostic precision,data availability,and scalability.To address these obstacles,we put out a lightweight model known as Smart MobiNet,which is derived from MobileNet and incorporates additional distinctive attributes.The model utilizes a multi-scale feature extraction methodology by using various convolutional layers.The ISIC 2019 dataset,sourced from the International Skin Imaging Collaboration,is employed in this study.Traditional data augmentation approaches are implemented to address the issue of model overfitting.In this study,we conduct experiments to evaluate and compare the performance of three different models,namely CNN,MobileNet,and Smart MobiNet,in the task of skin cancer detection.The findings of our study indicate that the proposed model outperforms other architectures,achieving an accuracy of 0.89.Furthermore,the model exhibits balanced precision,sensitivity,and F1 scores,all measuring at 0.90.This model serves as a vital instrument that assists clinicians efficiently and precisely detecting skin cancer. | Muhammad Suleman Faizan Ullah Ghadah Aldehim Dilawar Shah Mohammad Abrar Asma Irshad Sarra Ayouni | 2023 | Computers, Materials & Continua2023，77，12： | 0 |
| 10 | Energy efficient indoor localisation for narrowband internet of things显示文摘There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops quickly.The high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these devices.To maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a relay.Based on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot scheduling.As a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is optimised.We investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT criterion.The current work primarily considers the NOMA Narrow Band IoT network under a single EH relay.However,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance enhancement.Through simulation,the proposed approach is successfully shown.These improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%. | Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
| 11 | A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health显示文摘Artificial Intelligence(AI)is finding increasing application in healthcare monitoring.Machine learning systems are utilized for monitoring patient health through the use of IoT sensor,which keep track of the physiological state by way of various health data.Thus,early detection of any disease or derangement can aid doctors in saving patients’lives.However,there are some challenges associated with predicting health status using the common algorithms,such as time requirements,chances of errors,and improper classification.We propose an Artificial Krill Herd based on the Random Forest(AKHRF)technique for monitoring patients’health and eliciting an optimal prescription based on their health status.To begin with,various patient datasets were collected and trained into the system using IoT sensors.As a result,the framework developed includes four processes:preprocessing,feature extraction,classification,and result visibility.Additionally,preprocessing removes errors,noise,and missing values from the dataset,whereas feature extraction extracts the relevant information.Then,in the classification layer,we updated the fitness function of the krill herd to classify the patient’s health status and also generate a prescription.We found that the results fromthe proposed framework are comparable to the results from other state-of-the-art techniques in terms of sensitivity,specificity,Area under the Curve(AUC),accuracy,precision,recall,and F-measure. | Md.Moddassir Alam Md Mottahir Alam Muhammad Moinuddin Mohammad Tauheed Ahmad Jabir Hakami Anis Ahmad Chaudhary Asif Irshad Khan Tauheed Khan Mohd | 2023 | Computers, Materials & Continua2023，，5： | 0 |
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