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Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress andAbiotic Challenges

Phyton-International Journal of Experimental Botany 2024年第3期93卷 581-609页

作者： Muhammad Farhan Manda Sathish Rafia Kiran aroosa mushtaq Alaa Baazeem Ammarah Hasnain Fahad Hakim Syed Atif Hasan Naqvi Mustansar Mubeen Yasir Iftikhar Aqleem Abbas Muhammad Zeeshan Hassan Mahmoud Moustafa Department of Plant Pathology Faculty of Agricultural Sciences&TechnologyBahauddin Zakariya UniversityMultan60800Pakistan Centro de Investigación de Estudios Avanzados del Maule(CIEAM) Vicerrectoría de Investigación y PostgradoUniversidad Católica del MauleTalca3460000Chile College of Food Science and Nutritional Engineering China Agricultural UniversityBeijingChina Department of Biology College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Biotechnology Faculty of Biological SciencesLahore University of Biological and Applied SciencesLahorePakistan Department of Plant Pathology College of AgricultureUniversity of SargodhaSargodha40100Pakistan Department of Agriculture and Food Technology Karakorum International UniversityGilgitPakistan Department of Biology Faculty of ScienceKing Khalid UniversityAbhaSaudi Arabia

Plant growth and resilience to abiotic stresses,such as soil salinity and drought,depend intricately on nitrogen metabolism.This review explores nitrogen’s regulatory role in plant responses to these challenges,unveiling a dynamic interplay between nitrogen availability and abiotic stress.In the context of soil salinity,a nuanced rela-tionship emerges,featuring both antagonistic and synergistic interactions between salinity and nitrogen levels.Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation;however,excessive nitrogen can exacerbate salinity stress.We delve into the complexities of this interaction and its agri-cultural implications.Nitrogen,a vital element within essential plant structures like chloroplasts,elicits diverse responses based on its availability.This review comprehensively examines manifestations of nitrogen deﬁciency and toxicity across various crop types,including cereals,vegetables,legumes,and fruits.Furthermore,we explore the broader consequences of nitrogen products,such as N_(2)O,NO_(2),and ammonia,on human health.Understand-ing the intricate relationship between nitrogen and salinity,especially chloride accumulation in nitrate-fed plants and sodium buildup in ammonium-fed plants,is pivotal for optimizing crop nitrogen management.However,prudent nitrogen use is essential,as overapplication can exacerbate nitrogen-related issues.Nitrogen Use Efﬁ-ciency(NUE)is of paramount importance in addressing salinity challenges and enhancing sustainable crop productivity.Achieving this goal requires advancements in crop varieties with efﬁcient nitrogen utilization,pre-cise timing and placement of nitrogen fertilizer application,and thoughtful nitrogen source selection to mitigate losses,particularly urea-based fertilizer volatilization.This review article delves into the multifaceted world of plant nitrogen metabolism and its pivotal role in enabling plant resilience to nutritional stress and abiotic challenges.It offers insights into future directions

关键词： Synthetic nitrogen nitrogen signaling sustainable agriculture eutrophication ammonium nitrate

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Phytochemical analysis, antioxidant, acetylcholinesterase, and α-amylase inhibitors from Hippeastrum hybridum extract

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Journal of Traditional Chinese Medicine 2024年第3期44卷 496-504页

作者： Naila Sher mushtaq Ahmed Nadia mushtaq Department of Biotechnology University of Science and Technology Department of Botany University of Science and Technology

OBJECTIVE:To investigate the effects of Hippeastrum hybridum（HH） as a free radical scavenger,and an inhibitor of the two enzymes i-e Alpha-amylase（α-amylase） and acetylcholinesterase（AChE）.METHODS:In this study,HH plant was preliminary analyzed for phytochemical screening and then tested for its antioxidant,anti-α-amylase,and anti-AChE efficiency via standard procedures.RESULTS:Phytochemical analysis shows the existence of different compounds;while Coumarins and quinones were absent.The total phenolic,flavonoid,and tannins content were found to be（78.52±0.69） mg GAE/g,（2.01±0.04） mg RUE/g,and（58.12±0.23） mg TAE/g of plant extract respectively.28.02%±0.02% alkaloid and 2.02%±0.05% saponins were present in the HH extract.The HH extract showed the anti-oxidant property with IC50（50%inhibition） of（151.01±0.13）(HH),（79.01±0.04）(Ascorbic acid) for ferric reducing,（91.48±0.13）(HH),（48.02±0.11）(Ascorbic acid) against Ammonium molybdenum,（156.02±0.31）(HH),（52.38±0.21）(Ascorbic acid) against DPPH,136.01±0.21（HH）,52.02±0.31（Ascorbic acid） against H2O2,and 154.12±0.03（HH）,（40.05±0.15）(Ascorbic acid)μg/mL against ABTS respectively.Statistical analysis indicated that HH caused a competitive type of inhibition of α-amylase(Vmaxremained constant and Km increases from 10.65 to84.37%) while Glucophage caused the un-competitive type of inhibition i-e both Km and Vmaxdecreased from40.49 to 69.15%and 38.86 to 69.61%respectively.The Ki,（inhibition constant）;KI,（dissociation constant）,Km,（Michaelis-Menten constant）,and IC50 were found to be62,364,68.1,and 38.08±0.22 for HH and 12,101.05,195,34.01±0.21 for Glucophage.Similarly,HH causes an anon-competitive type of inhibition of AChE i-e Km remains constant while Vmaxdecreases from 60.5%to74.1%.The calculated Ki,KI,Km,and IC50 were found to be 32,36.2,0.05,and 18.117±0.018.CONCLUSION:From the current results,it is concluded that HH extract contains bioactive compounds,and could be a good alternative to controlling oxidants,Alzheimer‘s and Type-Ⅱ diabetic diseases.

关键词： Hippeastrum hybridum acetylcholinesterase alpha-amylase antioxidant phytochemicals

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Cellular preconditioning and mesenchymal stem cell ferroptosis

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World Journal of Stem Cells 2024年第2期16卷 64-69页

作者： Doaa Hussein Zineldeen Mazhar mushtaq Khawaja Husnain Haider Basic Sciences Sulaiman AlRajhi UniversityAlbukairiyah 52736AlQaseemSaudi Arabia Department of Medical Biochemistry and Molecular Biology Faculty of MedicineTanta UniversityTanta 6632110Egypt

In this editorial,we comment on the article published in the recent issue of the World Journal of Stem Cells.They focus on stem cell preconditioning to prevent ferroptosis by modulating the cystathionineγ-lyase/hydrogen sulfide(H_(2)S)pathway as a novel approach to treat vascular disorders,particularly pulmonary hypertension.Preconditioned stem cells are gaining popularity in regenerative medicine due to their unique ability to survive by resisting the harsh,unfavorable microenvironment of the injured tissue.They also secrete various paracrine factors against apoptosis,necrosis,and ferroptosis to enhance cell survival.Ferroptosis,a regulated form of cell death characterized by iron accumulation and oxidative stress,has been implicated in various pathologies encompassing dege-nerative disorders to cancer.The lipid peroxidation cascade initiates and sustains ferroptosis,generating many reactive oxygen species that attack and damage multiple cellular structures.Understanding these intertwined mechanisms provi-des significant insights into developing therapeutic modalities for ferroptosis-related diseases.This editorial primarily discusses stem cell preconditioning in modulating ferroptosis,focusing on the cystathionase gamma/H_(2)S ferroptosis pathway.Ferroptosis presents a significant challenge in mesenchymal stem cell(MSC)-based therapies;hence,the emerging role of H_(2)S/cystathionase gamma/H_(2) S signaling in abrogating ferroptosis provides a novel option for therapeutic intervention.Further research into understanding the precise mechanisms of H_(2)S-mediated cytoprotection against ferroptosis is warranted to enhance the thera-peutic potential of MSCs in clinical settings,particularly vascular disorders.

关键词： Cell survival Cell therapy Hydrogen sulfide Ferroptosis Preconditioning Stem cells Umbilical cord

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Effects of multiple shapes for steady flow with transformer oil+Fe_(3)O_(4)+TiO_(2) between two stretchable rotating disks

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 373-388页

作者： M.RAHMAN M.TURKYILMAZOGLU Z.mushtaq Department of Mathematics Mirpur University of Science and TechnologyMirpur 10250Pakistan Department of Mathematics Hacettepe UniversityBeytepeAnkara 06532Turkiye

In this study,we examine the effects of various shapes of nanoparticles in a steady flow of hybrid nanofluids between two stretchable rotating disks.The steady flow of hybrid nanofluids with transformer oil as the base fluid and Fe_(3)O_(4)+TiO_(2)as the hybrid nanofluid is considered.Several shapes of Fe_(3)O_(4)+TiO_(2)hybrid nanofluids,including sphere,brick,blade,cylinder,and platelet,are studied.Every shape exists in the same volume of a nanoparticle.The leading equations(partial differential equations(PDEs))are transformed to the nonlinear ordinary differential equations(ODEs)with the help of similarity transformations.The system of equations takes the form of ODEs depending on the boundary conditions,whose solutions are computed numerically by the bvp4c MATLAB solver.The outputs are compared with the previous findings,and an intriguing pattern is discovered,such that the tangential velocity is increased for the rotation parameter,while it is decreased by the stretching values because of the lower disk.For the reaction rate parameter,the concentration boundary layer becomes shorter,and the activation energy component increases the rate at which mass transfers come to the higher disk but have the opposite effect on the bottom disk.The ranges of various parameters taken into account are Pr=6.2,Re=2,M=1.0,φ_(1)=φ_(2)=0.03,K=0.5,S=-0.1,Br=0.3,Sc=2.0,α_(1)=0.2,γ=0.1,E_(n)=2.0,and q=1.0,and the rotation factor K is within the range of 0 to 1.

关键词： transformer oil Brinkman number skin friction coefficient double rotating disk Nusselt number Sherwood number

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Acoustofluidic separation of prolate and spherical micro-objects

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Microsystems & Nanoengineering 2024年第1期10卷 217-230页

作者： Muhammad Soban Khan mushtaq Ali Song Ha Lee Keun Young Jang Seong Jae Lee Jinsoo Park Department of Mechanical Engineering Chonnam National University77 Yongbong-roBuk-guGwangju 61186Republic of Korea Department of Polymer Engineering The University of Suwon17 Wauan-gilBongdam-eupHwaseongGyeonggi 18323Republic of Korea

Most microfluidic separation techniques rely largely on object size as a separation marker.The ability to separate micro-objects based on their shape is crucial in various biomedical and chemical assays.Here,we develop an ondemand,label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and torque.The freely rotating non-spherical microobjects were aligned under the progressive acoustic field by the counterrotating radiation torque,and the major axis of the prolate ellipsoids was parallel to the progressive wave propagation.The specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave propagation.As a consequence,the acoustic backscattering decreased,resulting in a decreased magnitude of the radiation force.Through the variation in radiation force,which depended on the micro-object morphology enabled the acoustofluidic shape-based separation.We conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method.A series of experiments with polystyrene microspheres,prolate ellipsoids,and peanut-shaped microparticles were performed for validation.Through quantitative analysis of the separation efficiency,we confirmed the high purity and high recovery rate of the proposed acoustofluidic shapebased separation of micro-objects.As a bioparticle,we utilize Thalassiosira eccentrica to perform shape-based separation,as the species has a variety of potential applications in drug delivery,biosensing,nanofabrication,bioencapsulation and immunoisolation.

关键词： separation spherical rotating

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Mesenchymal stem cells’“garbage bags”at work:Treating radial nerve injury with mesenchymal stem cell-derived exosomes

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World Journal of Stem Cells 2024年第5期16卷 467-478页

作者： Mazhar mushtaq Doaa Hussein Zineldeen Muhammad Abdul Mateen Khawaja Husnain Haider Department of Basic Sciences Sulaiman AlRajhi UniversityAlbukairiyah 52736AlQaseemSaudi Arabia Medical Biochemistry and Molecular Biology Department Faculty of MedicineTanta UniversityTanta 6632110Egypt

Unlike central nervous system injuries,peripheral nerve injuries(PNIs)are often characterized by more or less successful axonal regeneration.However,structural and functional recovery is a senile process involving multifaceted cellular and molecular processes.The contemporary treatment options are limited,with surgical intervention as the gold-standard method;however,each treatment option has its associated limitations,especially when the injury is severe with a large gap.Recent advancements in cell-based therapy and cell-free therapy approaches using stem cell-derived soluble and insoluble components of the cell secretome are fast-emerging therapeutic approaches to treating acute and chronic PNI.The recent pilot study is a leap forward in the field,which is expected to pave the way for more enormous,systematic,and well-designed clinical trials to assess the therapeutic efficacy of mesenchymal stem cell-derived exosomes as a bio-drug either alone or as part of a combinatorial approach,in an attempt synergize the best of novel treatment approaches to address the complexity of the neural repair and regeneration.

关键词： Exosome Mesenchymal stem cells Nerve injury Stem cells Secretome Regeneration

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge states.However,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered precursors.Herein,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk Mn3GaC.The as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode materials.Overall,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble

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Computers, Materials & Continua 2024年第2期78卷 2047-2066页

作者： Muhammad Rizwan Muhammad Faheem mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran Ashraf Department of Artificial Intelligence The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Information Technology Khwaja Fareed University of Engineering and ITRYKhan64200Pakistan Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Signal Theory and Communications and Telematic Engineering Unviersity of ValladolidPaseo de Belén 15Valladolid47011Spain Faculty of Social Science and Humanities Universidad Europea del Atlántico Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaCampeche24560México Fundación Universitaria Internacional de Colombia Bogotá111611Colombia Universidad Internacional Iberoamericana AreciboPuerto Rico00613USA Universidade Internacional do Cuanza Cuito46703Angola Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541South Korea

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text.This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus.Furthermore,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic criteria.Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus.Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to baselines.Finally,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances.The proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText alone.The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweet

关键词： Depression classification deep learning FastText machine learning

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A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

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Computers, Materials & Continua 2024年第5期79卷 1875-1901页

作者： K.Umapathi S.Shobana Anand Nayyar Judith Justin R.Vanithamani Miguel Villagómez Galindo mushtaq Ahmad Ansari Hitesh Panchal Department of Biomedical Engineering KIT-Kalaignarkarunanidhi Institute of TechnologyCoimbatore641402India Graduate School Faculty of Information TechnologyDuy Tan UniversityDa Nang550000Viet Nam Department of Biomedical and Instrumentation Engineering Avinashilingam Institute for Home Science and Higher Education forWomenCoimbatore641043India UniversidadMichoacana de SanNicolás de HidalgoAvenida Francisco J.Múgica S/N Ciudad Universitaria MoreliaCP58030Mexico Department of Pharmacology and Toxicology College of PharmacyKing Saud UniversityRiyadh11451Saudi Arabia Department of Mechanical Engineering Gujarat Technological UniveristyNigam NagarChandkhedaAhmedabadGujarat382424India

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced Speckle ReducedAnisotropic Diffusion (SRAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and Random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

关键词： Ultrasound images breast cancer tumor classification segmentation deep learning lesion detection

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