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Evaluation of antihepatotoxic potential of Solanum xanthocarpum fruit extract against antitubercular drugs induced hepatopathy in experimental rodents

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Asian Pacific Journal of Tropical Biomedicine 2012年第6期2卷 454-460页

作者： Talib Hussain Ramesh K Gupta Sweety K mohd sajid khan Md Sarfaraj Hussain Md Arif Arshad Hussain Md Faiyazuddin Chandana Venkateswara Rao Pharmacognosy and Ethnopharmacology Division National Botanical Research Institute Department of Pharmacology and Toxicology Faculty of Pharmacy Integral University Department of Pharmacology Royal College of Pharmacy and Health Sciences Department of Biotechnology Integral University

Objective:To assess the hepatoprotective effect of Solanum xanthocarpum(S. xanthocarpum) fruit extract against antitubercular drug-induced liver toxicity in experimental ***:Ethanolic(50%) fruit extract ofS. xanthocarpum(100, 200 and 400 mg/kg bw) was administered daily for 35 days in experimental animals. Liver toxicity was induced by combination of three antitubercular drugs [isoniazid(I) 7.5 mg/kg, rifampicin(R) 10 mg/kg and pyrazinamide(P) 35 mg/kg] given orally as suspension for 35 days in rats. The hepatoprotective activity was assessed using various biochemical parameters like aspartate aminotransferase(AST), alanine aminotransferase(ALT), alkaline phosphatise(ALP), total bilirubin(TBL), albumin(ALB), total protein(TP), lactate dehydroginase(LDH), and serum cholesterol(CHL). Meanwhile,in vivoantioxidant activities as lipid peroxidation(LPO), reduced glutathione(GSH), superoxide dismutase(SOD) and catalase(CAT) were measured in rat liver homogenate. The biochemical observations were supplemented by histopathological ***:The results demonstrated that treatment ***(P<0.05-P<0.001) and dose-dependently prevented drug induced increase in serum levels of hepatic enzymes. Furthermore,S. xanthocarpumsignificantly(up toP<0.001) reduced the LPO in the liver tissue and restored activities of defence antioxidant enzymes GSH, SOD and CAT towards normal levels. Histopathology of the liver tissue showed that S. xanthocarpumattenuated the hepatocellular necrosis and led to reduction in inflammatory cells ***:The results of this study strongly indicate the protective effect of S. xanthocarpumagainst liver injury which may be attributed to its hepatoprotective activity, and thereby scientifically support its traditional use.

关键词： Solanum xanthocarpum Rifampicin Isoniazid Pyrazinamide Antioxidant Antihepatotoxicity Hepatoprotective effect Antitubercular drug Liver toxicity Liver injury Biochemical parameter Histopathology

Attention-Based Deep Learning Model for Early Detection of Parkinson’s Disease

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Computers, Materials & Continua 2022年第6期71卷 5183-5200页

作者： mohd Sadiq mohd Tauheed khan Sarfaraz Masood Department of Computer Engineering Jamia Millia IslamiaNew Delhi-110025India Department of Math and Computer Science Augustana CollegeRock IslandIllinois-61201USA

Parkinson’s disease(PD),classified under the category of a neurological syndrome,affects the brain of a person which leads to the motor and non-motor *** motor symptoms,one of the major disabling symptom is Freezing of Gait(FoG)that affects the daily standard of living of PD *** treatments target to improve the symptoms of *** of PD at the early stages is an arduous task due to being indistinguishable from a healthy *** work proposed a novel attention-basedmodel for the detection of FoG events and PD,andmeasuring the intensity of PD on the United Parkinson’s Disease Rating *** separate datasets,that is,UCF Daphnet dataset for detection of Freezing of Gait Events and PhysioNet Gait in PD Dataset were used for training and validating on their respective *** results show a definite rise in the various performance metrics when compared to landmark models on these problems using these *** results strongly suggest that the proposed state of the art attention-based deep learning model provide a consistent as well as an efficient solution to the selected *** valueswere obtained for various performance metrics like accuracy of 98.74%for detection FoG,98.72%for detection of PD and 98.05%for measuring the intensity of PD on *** model was also analyzed for robustness against noisy samples,where also model exhibited consistent *** results strongly suggest that the proposed model provides a better classification method for selected problem.

关键词： Parkinson’s disease freezing of gait the attention mechanism hyperparameter tuning attentive-FoGPDNet

DNNBoT: Deep Neural Network-Based Botnet Detection and Classification

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Computers, Materials & Continua 2022年第4期71卷 1729-1750页

作者： mohd Anul Haq mohd Abdul Rahim khan Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah 11952Saudi Arabia

The evolution and expansion of IoT devices reduced human efforts,increased resource utilization, and saved time;however, IoT devices createsignificant challenges such as lack of security and privacy, making them morevulnerable to IoT-based botnet attacks. There is a need to develop efficientand faster models which can work in real-time with efficiency and stability. The present investigation developed two novels, Deep Neural Network(DNN) models, DNNBoT1 and DNNBoT2, to detect and classify well-knownIoT botnet attacks such as Mirai and BASHLITE from nine compromisedindustrial-grade IoT devices. The utilization of PCA was made to featureextraction and improve effectual and accurate Botnet classification in IoTenvironments. The models were designed based on rigorous hyperparameterstuning with GridsearchCV. Early stopping was utilized to avoid the effects ofoverfitting and underfitting for both DNN models. The in-depth assessmentand evaluation of the developed models demonstrated that accuracy andefficiency are some of the best-performed models. The novelty of the presentinvestigation, with developed models, bridge the gaps by using a real datasetwith high accuracy and a significantly lower false alarm rate. The results wereevaluated based on earlier studies and deemed efficient at detecting botnetattacks using the real dataset.

关键词： Botnet network monitoring machine learning deep neural network IoT threat

Fungicide tolerant Bradyrhizobium japonicum mitigate toxicity and enhance greengram production under hexaconazole stress

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Journal of Environmental Sciences 2019年第4期31卷 92-108页

作者： Mohammad Shahid mohd.Saghir khan Department of Agricultural Microbiology Faculty of Agricultural SciencesAligarh Muslim University

Bacterial strain RV9 recovered from greengram nodules tolerated 2400 μg/mL of hexaconazole and was identified by 16 S rDNA sequence analysis as Bradyrhizobium japonicum(KY940048). Strain RV9 produced IAA(61.6 μg/mL), ACC deaminase(51.7 mg/(protein·hr)), solubilized TCP(105 μg/mL), secreted 337.6 μg/mL EPS, and produced SA(52.2 μg/mL) and 2,3-DHBA(28.3 μg/mL). Exopolysaccharides produced by strain RV9 was quantified and characterized by SEM, AFM, EDX and FTIR. Beyond tolerance limit,hexaconazole caused cellular impairment and reduced the viability of strain RV9 revealed by SEM and CLSM. Hexaconazole distorted the root tips and altered nodule structure leading thereby to reduction in the performance of greengram. Also, the level of antioxidant enzymes, proline, TBARS, ROS and cell death was increased in hexaconazole treated *** images revealed a concentration dependent increase in the characteristic green and blue fluorescence of hexaconazole treated roots. The application of B. japonicum strain RV9 alleviated the fungicide toxicity and improved the measured plant characteristics. Also,rhizobial cells were localized inside tissues as revealed by CLSM. Colonization of *** strain RV9 decreased the levels of CAT, POD, APX, GPX and TBARS by 80%, 5%,13%, 13% and 19%, respectively over plants grown at 80 μg/(hexaconazole·kg) soil. The ability to detoxify hexaconazole, colonize plant tissues, secrete PGP bioactive molecules even under fungicide pressure and its unique ability to diminish oxidative stress make *** an attractive choice for remediation of fungicide polluted soils and to concurrently enhance greengram production under stressed environment.

关键词： Hexaconazole toxicity Greengram Bradyrhizobium japonicum Cellular damage Nodule ultrastructure Oxidative stress

Micelle Catalyzed Oxidation of D-Mannose by Cerium (IV) in Sulfuric Acid

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物理化学学报 2008年第5期24卷 810-816页

作者： KABIR-UD-DIN ALI mohd. sajid khan Zaheer Chemistry Department Aligarh Muslim University Aligarh 202002 UP India Chemistry Department Jamia Millia Islamia Jamia Nagar New Delhi 110025 India

Kinetics of D-mannose oxidation by cerium (IV) was studied in a sulfuric acid medium at 40 ℃ both in absence and presence of ionic micelles. In both cases, the rate of the reaction was first-order in D-mannose and in cerium (IV), which decreased with increasing [H2SO4]. This suggested that the redox reaction followed the same mechanism. The reaction proceeded through formation of an intermediate complex, which was proved by kinetic method. The complex underwent slow unimolecular decomposition to a free radical that reacted with cerium (IV) to afford the product. The catalytic role of cationic cetyltrimethylammonium bromide (CTAB) micelles was best explained by the Menger-Portnoy model. The study of the effect of CTAB also indicated that a negatively charged species was reactive form of cerium (IV). From the kinetic data, micelle-cerium (IV) binding and rate constants in micellar medium were evaluated. The anionic micelle of sodium dodecyl sulfate plays no catalytic role. The oxidation has the rate expression: -d[Ce(IV)]= k1Kc1[D-mannose][Ce(IV)]dt Different activation parameters for micelle catalyzed and uncatalyzed paths were also calculated and discussed.

关键词：甘露糖胶束催化剂硫磺酸化学分析

Development of PCCNN-Based Network Intrusion Detection System for EDGE Computing

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Computers, Materials & Continua 2022年第4期71卷 1769-1788页

作者： mohd Anul Haq mohd Abdul Rahim khan Talal AL-Harbi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah 11952Saudi Arabia

Intrusion Detection System(IDS)plays a crucial role in detecting and identifying the DoS and DDoS type of attacks on IoT ***,anomaly-based techniques do not provide acceptable accuracy for efficacious intrusion ***,we found many difficulty levels when applying IDS to IoT devices for identifying attempted *** this background,we designed a solution to detect intrusions using the Convolutional Neural Network(CNN)for Enhanced Data rates for GSM Evolution(EDGE)*** created two separate categories to handle the attack and non-attack events in the *** findings of this study indicate that this approach was significantly *** attempted both multiclass and binary *** the case of binary,we clustered all malicious traffic data in a single ***,we developed 13 layers of Sequential 1-D CNN for IDS detection and assessed them on the public dataset *** Component Analysis(PCA)was implemented to decrease the size of the feature vector based on feature extraction and *** approach proposed in the current investigation obtained accuracies of 99.34%and 99.13%for binary and multiclass classification,respectively,for the NSL-KDD *** experimental outcomes showed that the proposed Principal Component-based Convolution Neural Network(PCCNN)approach achieved greater precision based on deep learning and has potential use in modern intrusion detection for IoT systems.

关键词： IDS edge computing machine learning NSL-KDD IoT

Traceability implementation in food supply chain: A grey-DEMATEL approach

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Information Processing in Agriculture 2019年第3期6卷 335-348页

作者： Abid Haleem Shahbaz khan mohd Imran khan Department of Mechanical Engineering Faculty of Engineering and TechnologyJamia Millia IslamiaNew Delhi 110025India

Numerous incidents of food adulteration,fraudulence and foodborne disease outbreaks have shaken the consumer confidence towards the food they *** incidents compel the Food Supply Chain(FSC)partners to implement an appropriate traceability system in their respective supply chains to sustain the consumer *** objective of this research is to identify the drivers(major factors)which play a significant role in the successful implementation of the traceability system in FSC and evaluate the causal relationships developing *** drivers are identified towards implementation of the traceability system in FSC through literature review and supported with expert’s *** grey-based DEMATEL approach is identified to evaluate these relationships among the drivers according to their net ***,these drivers ranked based on the prominence and effect *** finding of this research shows that the drivers are clustered into two groups namely:influential(cause)and influenced(effect)*** drivers belong to the influential group,and remaining eight are from the influenced *** most influential driver is the “food safety and quality”which provide a significant effect on the implementation of a traceability *** research can be a building block to develop a framework to implement the traceability system within FSC and assist the policymakers,and practitioners to identify and evaluate drivers related to the implementation of traceability system in *** paper also provides a useful insight&support to the practitioners and managers in decision making for traceability implementation related issues。

关键词： Drivers Decision making trial and evaluation laboratory(DEMATEL) Food safety and quality Food Supply Chain(FSC) Traceability

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 357-384页

作者： mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

Rare earth element signatures of Paleoproterozoic Sallopat phosphorites of Aravalli Basin,India:implications for diagenetic effects and depositional environment

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Acta Geochimica 2023年第4期42卷 726-738页

作者： Samsuddin khan Shamim A.Dar K.F.khan mohd Shuaib Department of Geology Aligarh Muslim UniversityAligarhUttar Pradesh 202002India Department of Geology Centre of Advanced StudyInstitute of ScienceBanaras Hindu UniversityVaranasi 221005India

As a repository of REE,the Paleoproterozoic phosphorite of the Aravalli Basin in India is explored time to *** phosphorite deposits of the Sallopat sub-basin Banswara district of the Aravalli Supergroup show moderate REE concentrations much lower than that of average marine *** ratios and PAAS-normalized REE distribution patterns reflect MREE enrichment over LREE and HREE in these *** enrichment confirmed by(Sm/Yb)Nversus(Sm/Pr)Nrelationship and attributed to the selective uptake by cyanobacteria and mixing of riverine inputs.Y/Ho,La/Ce and Er/Nd ratios confirm that the REE in Sallopat phosphorites might have been affected by the argillaceous terrigenous and plagioclase-rich sediments probably derived from Banded Gneissic *** modeling indicates that REE were concentrated during early diagenetic processes with limited weathering *** negative to low Ce anomaly depicts oxic to sub-oxic conditions of seawater due to oxidation of Ce^(3+)to Ce^(4+)whereas Eu^(3+)reduced to Eu^(2+)indicating positive Euanomaly and reducing conditions as well during the *** anomalies may be due to the stratified restricted marine environment of upwelling and mingling of organic-rich anoxic deep water with oxic upper seawater prior to the formation of phosphorite deposits in the *** of REE in Sallopat phosphorite relies on various physico-chemical *** phosphorites may have been formed in restricted marine water which was influenced by extra clastic sediment input carried out by fluvial systems.

关键词： Stromatolite Lower Aravalli Group Apatite-(CaF) Alkaline environment Diagenesis