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Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors

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World Journal of Diabetes 2024年第1期15卷 53-71页

作者： Min Wang Yang Ou Xiang-Lian Yuan Xiu-Fang Zhu Ben Niu Zhuang Kang Bing Zhang anwar ahmed Guo-Qiang Xing Heng Su School of Chemical Science and Technology Yunnan UniversityKunming 650091Yunnan ProvinceChina Department of Endocrinology The First People’s Hospital of Yunnan ProvinceKunming 650032Yunnan ProvinceChina Clinical Laboratory Nanchong Central Hospital&The Second Clinical Medical College of North Sichuan Medical UniversityNanchong 637000Sichuan ProvinceChina Department of Preventive Medicine and Biostatistics Uniformed Services University of the Health SciencesBethesdaMD 20814United States The Affiliated Hospital and Second Clinical Medical College North Sichuan Medical UniversityNanchong 637000Sichuan ProvinceChina Department of Research and Development Lotus *** LLCGaithersburgMD 20878United States

BACKGROUND The lack of specific predictors for type-2 diabetes mellitus(T2DM)severely impacts early intervention/prevention efforts.Elevated branched-chain amino acids(BCAAs:Isoleucine,leucine,valine)and aromatic amino acids(AAAs:Tyrosine,tryptophan,phenylalanine)show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical studies.However,improvement is needed to support its clinical utility.AIM To evaluate the effects of body mass index(BMI)and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body weight.METHODS Ninety-seven new-onset T2DM patients(<12 mo)differing in BMI[normal weight(NW),n=33,BMI=22.23±1.60;overweight,n=42,BMI=25.9±1.07;obesity(OB),n=22,BMI=31.23±2.31]from the First People’s Hospital of Yunnan Province,Kunming,China,were studied.One-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/AAAs.RESULTS Fasting serum AAAs,BCAAs,glutamate,and alanine were greater and high-density lipoprotein(HDL)was lower(P<0.05,each)in OB-T2DM patients than in NW-T2DM patients,especially in male OB-T2DM patients.Arginine,histidine,leucine,methionine,and lysine were greater in male patients than in female patients.Moreover,histidine,alanine,glutamate,lysine,valine,methionine,leucine,isoleucine,tyrosine,phenylalanine,and tryptophan were significantly correlated with abdominal adiposity,body weight and BMI,whereas isoleucine,leucine and phenylalanine were negatively correlated with HDL.CONCLUSION Heterogeneously elevated amino acids,especially BCAAs/AAAs,across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM development.The higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals,whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW individuals.This potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to be used as the T2DM predictor.

关键词： Hyperaminoacidemia Branched-chain/aromatic amino acids New-onset type-2 diabetes Predictor Obesity Sex

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Visible light-driven photo remediation of hazardous cationic dye via Ce-doped WO_(3) nanostructures

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Journal of Rare Earths 2024年第5期42卷 869-878,I0003页

作者： Azra Haroon Kaseed anwar Arham S.ahmed Department of Physics Aligarh Muslim University202002AligarhIndia Interdisciplinary Nanotechnology Centre Aligarh Muslim University202002AligarhIndia

Ce-doped WO_(3) nanoparticles were successfully synthesized by the sol-gel method and characterized through advanced characterization techniques.The high resolution transmission electron microscopy(HRTEM)and scanning electron microscopy(SEM)results show a reduction in the agglomeration of nanoparticles upon doping.The energy dispersive X-ray(EDX)analysis validates the existence of the Ce element in all the doped samples.X-ray photoelectron spectroscopy(XPS)and Raman spectra justify the presence of structural defects(oxygen vacancies)and successful formation of the monoclinic WO_(3) phase,respectively.The Kubelka-Munk function indicates a decrease in band gap with doping,while photoluminescence(PL)spectra show intense visible and UV emissions,Significantly,all doped samples exhibit higher photocatalytic performance than pure WO_(3) nanoparticles,with the 6 wt%Ce-doped sample displaying the highest degradation rate.Doping with Ce can help to increase the surface area of WO_(3),thereby improving its photoactivity,Moreover,a correlation between PL and photocatalysis is established in the light of oxygen vacancies suggesting a direct dependence of high photocatalytic activity on strong PL signals of WO_(3) nanostructures.Trapping experiments further reveal that the degradation process is primarily driven by active species,providing insight into a plausible photocatalytic mechanism.

关键词： WO_(3) Rare-earth element Environmental crisis Oxygen vacancies Luminescence Photocatalysis

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Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

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Computer Systems Science & Engineering 2024年第2期48卷 363-394页

作者： Nasser Alshammari Shumaila Shahzadi Saad Awadh Alanazi Shahid Naseem Muhammad anwar Madallah Alruwaili Muhammad Rizwan Abid Omar Alruwaili ahmed Alsayat Fahad Ahmad Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72341Saudi Arabia Department of Computer Sciences Kinnaird College forWomenLahorePunjab54700Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72341Saudi Arabia Computer Science Florida Polytechnic UniversityLakelandFlorida33805USA Delta3T LahorePunjab54700Pakistan Department of Basic Sciences Common First YearJouf UniversitySakaka72341Saudi Arabia

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

关键词： Software defined network network function virtualization network function virtualization management and orchestration virtual infrastructure manager virtual network function Kubernetes Kubectl artificial intelligence machine learning

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Relationship between Seed Priming Mediated Seedling Vigor and Yield Performance of Spring Wheat

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1159-1177页

作者： Md.Parvez anwar Masuma Akhter Sharmin Aktar Sinthia Afsana Kheya A.K.M.Mominul Islam Sabina Yeasmin ahmed Khairul Hasan Md.Harun Or Rashid Department of Agronomy Bangladesh Agricultural UniversityMymensingh2202Bangladesh

Seed priming is a pre-germinated technique that can enhance seed germination percentage,faster and synchro-nized germination,better seedling growth,and yield under stress conditions.To ascertain the most effective seed priming method that would ensure the potential yield of wheat in Bangladesh,two experiments were carried out from December 2021 to March 2022 at the Department of Agronomy,Bangladesh Agricultural University.Two wheat varieties namely BARI Gom-28 and BWMRI Gom-1 were subjected to a range of priming chemicals in both lab and pot tests.These compounds included the following:control(no priming),hydropriming(distilled water),10000 ppm KNO_(3),15000 ppm KNO_(3),40000 ppm Mannitol,60000 ppm Mannitol,10000 ppm NaCl,20000 ppm NaCl,100 ppm PEG,150 ppm PEG,500 ppm NaOCl,1000 ppm NaOCl,10000 ppm CaCl_(2),20000 ppm CaCl_(2),10000 ppm KCl and 20000 ppm KCl.A complete randomized design(CRD)with three repli-cations was used to set up the experiments.The results showed that BARI Gom-28 and BWMRI Gom-1 responded best to KCl priming in terms of rapid seed germination and strong seedling development.On the other hand,the best priming agents for plant growth and productivity turned out to be CaCl_(2) and KCL.The results of this study support the possibility of using seed priming as a technique to improve wheat plant development and output by raising seed emergence and survival rates.

关键词： Priming seedling percentage germination growth yield wheat

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Pregnancy outcome of day 3versus day 5 embryo transfer: A retrospective analysis

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Asian pacific Journal of Reproduction 2017年第2期6卷 89-92页

作者： Samaher Alfaraj Fatima Alzaher Sahar Alshwaiaer anwar ahmed Department of Obstetrics and Gynecology Reproductive Endocrinology and Infertility UnitKing Abdul-Aziz Medical CityRiyadhSaudi Arabia Department of Obstetrics and Gynecology Ministry of HealthDammamSaudi Arabia Assistant Professor of Biostatistics Department of Epidemiology and Biostatistics College of Public Health and Health Informatics King Saud Bin Abdulaziz University for Health Sciences National Guard Health Affairs RiyadhKSA

Objective:To compare the pregnancy rate between day 3 and day 5 transfer regardless grades of embryos and number of transferred embryo.Methods: Retrospective cohort, a total of seven hundred and four patients met our inclusion criteria, with 411 had day 3 embryo transfer and 293 had day 5 embryo transfer. The patients who were older than 40 years old were excluded. Embryo transfer was carried out in all patients in both transfer groups.Results:Both clinical pregnancy rate and implantation rate did not show any statistically significant difference between the day 3 and day five transfer groups. These were 44%vs. 45% withP=0.82 and 19%vs. 19% withP=0.99 respectively. An increase of miscarriage rate with day 5 embryo transferred compare with day 3 (12.0%vs. 4.4%,P=0.01), but no significant difference was found about biochemical pregnancy rate (P=0.52).Conclusions:Transferring embryo at day 5 may not provide any additional benefit over day 3 transfers to patients. In addition, it increases the risk of miscarriage. Further studies of this issue needed for confirming our findings.

关键词： Embryo transfer Blastocyst Early cleavage stage Pregnancy outcomes Sequential culture media

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Characterization and anticancer potential of Withania somnifera fruit bioactives(a native species to Pakistan)using gas chromatography-mass spectrometer,nuclear magnetic resonance and liquid chromatography-mass spectrometry-electrospray ionization

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Journal of Traditional Chinese Medicine 2022年第6期42卷 908-914页

作者： Qudsia Tabassam Tahir Mehmood Sibtain ahmed Farooq anwar Abdul Rauf Raza Institute of Chemistry University of SargodhaSargodha-40100Pakistan Institute of Biochemistry and Biotechnology University of Veterinary and Animal Sciences-UVAS54000-Lahore.Pakistan University of California San Diego 9500 Gilman Drive La JollaCA 92093USA

INTRODUCTION:Withania somnifera(W.somnifera)is a plant with remarkable pharmacological properties.The plant has an impressive profile of medicinal uses in the folk medicine system of several civilizations.AIM:This comprehensive study is aimed to characterize phytochemicals in fruit of W.somnifera and tested for in vitro anticancer potential to find out active candidate in disease prevention and treatment.METHODS:The bioactive components from W.somnifera fruit were extracted with polar and non-polar solvents.Anticancer potential of the isolated bioactive was assessed against different cancer cell lines through MTT assay and Incucytes imaging analysis.The extracts were characterized for secondary metabolites using GCMS(gas chromatography-mass spectrometer),LCMS(liquid(electrospray Ionization)and 1H-NMR(electrospray Ionization)techniques.RESULTS:Both freeze-dried and rotary evaporator condensed extracts exhibited anticancer potential against MDA-MB-231,MCF7-SKOV3 and SKBR3 cell lines.The tested extracts have cell growth inhibition potential against mammalian cancer cell line.Hexacosanedioic acid purified from n-hexane extract through HPLC was investigated for its cytotoxicity against breast cancer cell line SKBR3 by using Incucytes imaging analysis.Conclusion:We found that a variety of bioactive compounds existed in this plant.One identified compound that was not investigated for cytotoxicity in previous studies was purified and its application showed cytotoxicity on breast cancer cell lines.A number of bioactive identified from W.somnifera fruit may have an effective potential for development into chemotherapy drugs.

关键词： phytochemicals plants medicinal anti-cancer activities purification state-of-the-art techniques

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Bio-Inspired Modelling of Disease Through Delayed Strategies

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Computers, Materials & Continua 2022年第12期73卷 5717-5734页

作者： Arooj Nasir Dumitru Baleanu Ali Raza Pervez anwar Nauman ahmed Muhammad Rafiq Tahir Nawaz Cheema Baqai Medical University Karachi75340Pakistan Shalamar Medical and Dental College Lahore54000Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung40402Taiwan Institute of Space Sciences Magurele-Bucharest077125Romania Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Department of Biochemistry University of SialkotSialkot51310Pakistan Department of Mathematics and Statistics The University of LahoreLahore54590Pakistan Department of Mathematics Faculty of SciencesUniversity of Central PunjabLahore54000Pakistan Department of Mathematics University of GujratGujrat52000Pakistan

In 2020,the reported cases were 0.12 million in the six regions to the official report of the World Health Organization(WHO).For most children infected with leprosy,0.008629 million cases were detected under fifteen.The total infected ratio of the children population is approximately 4.4 million.Due to theCOVID-19 pandemic,the awareness programs implementation has been disturbed.Leprosy disease still has a threat and puts people in danger.Nonlinear delayed modeling is critical in various allied sciences,including computational biology,computational chemistry,computational physics,and computational economics,to name a few.The time delay effect in treating leprosy delayed epidemic model is investigated.The whole population is divided into four groups:those who are susceptible,those who have been exposed,those who have been infected,and those who have been vaccinated.The local and global stability of well-known conclusions like the Routh Hurwitz criterion and the Lyapunov function has been proven.The parameters’sensitivity is also examined.The analytical analysis is supported by computer results that are presented in a variety of ways.The proposed approach in this paper preserves equilibrium points and their stabilities,the existence and uniqueness of solutions,and the computational ease of implementation.

关键词： Leprosy disease delayed model stability analysis computer results

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Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

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Computer Modeling in Engineering & Sciences 2023年第7期136卷 257-275页

作者： Ali Raza Dumitru Baleanu Zafar Ullah Khan Muhammad Mohsin Nauman ahmed Muhammad Rafiq Pervez anwar Department of Mathematics Government Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung40402Taiwan Institute of Space Sciences Magurele-Bucharest077125Romania Department of Dermatology Rashid Latif Medical College LahoreLahore54000Pakistan Department of Mathematics Technische Universitat ChemnitzChemnitz6209111Germany Department of Mathematics and Statistics The University of LahoreLahore54590Pakistan Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Biochemistry University of SialkotSialkot51311Pakistan

Most developing countries such as Afghanistan,Pakistan,India,Bangladesh,and many more are still fighting against poliovirus.According to the World Health Organization,approximately eighteen million people have been infected with poliovirus in the last two decades.In Asia,still,some countries are suffering from the virus.The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied.Some basic properties of the deterministic model are studied,equilibria,local stability around the stead states,and reproduction number.Euler Maruyama,stochastic Euler,and stochastic Runge-Kutta study the behavior of complex stochastic differential equations.The main target of this study is to develop a nonstandard computational method that restores dynamical features like positivity,boundedness,and dynamical consistency.Unfortunately,the existing methods failed to fix the actual behavior of the disease.The comparison of the proposed approach with existing methods is investigated.

关键词： Poliovirus model differential equations methods analysis

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Fuzzy-HLSTM(Hierarchical Long Short-Term Memory)for Agricultural Based Information Mining

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Computers, Materials & Continua 2023年第2期74卷 2397-2413页

作者： ahmed Abdu Alattab Mohammed Eid Ibrahim Reyazur Rashid Irshad anwar Ali Yahya Amin A.Al-Awady Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajranSaudi Arabia Department of Computer Science College of Computer Science&Information SystemsNajran UniversityNajranSaudi Arabia Computer Skills Department Deanship of Preparatory YearNajran UniversityNajranSaudi Arabia

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation.In case-based reasoning systems,case representation is critical,and thus,researchers have thoroughly investigated textual,attribute-value pair,and ontological representations.As big databases result in slow case retrieval,this research suggests a fast case retrieval strategy based on an associated representation,so that,cases are interrelated in both either similar or dissimilar cases.As soon as a new case is recorded,it is compared to prior data to find a relative match.The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches.Hierarchical Long Short-Term Memory(HLSTM)is used to evaluate the efficiency,similarity of the models,and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year.Based on the results,the proposed approaches allows for rapid case retrieval with high accuracy.

关键词： Machine learning agriculture IoT HLSTM fuzzy rules

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Detection of Left Ventricular Cavity from Cardiac MRI Images Using Faster R-CNN

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Computers, Materials & Continua 2023年第1期74卷 1819-1835页

作者： Zakarya Farea Shaaf Muhammad Mahadi Abdul Jamil Radzi Ambar ahmed Abdu Alattab anwar Ali Yahya Yousef Asiri Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn MalaysiaParit RajaBatu Pahat86400JohorMalaysia Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajran61441Saudi Arabia Department of Computer Science Faculty of Computer Science and Info.SystemsThamar UniversityDhamar87246Yemen Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

The automatic localization of the left ventricle(LV)in short-axis magnetic resonance(MR)images is a required step to process cardiac images using convolutional neural networks for the extraction of a region of interest(ROI).The precise extraction of the LV’s ROI from cardiac MRI images is crucial for detecting heart disorders via cardiac segmentation or registration.Nevertheless,this task appears to be intricate due to the diversities in the size and shape of the LV and the scattering of surrounding tissues across different slices.Thus,this study proposed a region-based convolutional network(Faster R-CNN)for the LV localization from short-axis cardiac MRI images using a region proposal network(RPN)integrated with deep feature classification and regression.Themodel was trained using images with corresponding bounding boxes(labels)around the LV,and various experiments were applied to select the appropriate layers and set the suitable hyper-parameters.The experimental findings showthat the proposed modelwas adequate,with accuracy,precision,recall,and F1 score values of 0.91,0.94,0.95,and 0.95,respectively.This model also allows the cropping of the detected area of LV,which is vital in reducing the computational cost and time during segmentation and classification procedures.Therefore,itwould be an ideal model and clinically applicable for diagnosing cardiac diseases.

关键词： Cardiac short-axis MRI images automatic left ventricle localization deep learning models faster R-CNN

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