Background:Locally advanced laryngeal squamous cell carcinoma(LA-LSCC)presents clinical challenges due to the lack of reliable non-invasive biomarkers.This study aimed to evaluate miR-449a as a diagnostic and prognost...Background:Locally advanced laryngeal squamous cell carcinoma(LA-LSCC)presents clinical challenges due to the lack of reliable non-invasive biomarkers.This study aimed to evaluate miR-449a as a diagnostic and prognostic biomarker in LA-LSCC.Methods:miR-449a expression was analyzed in tumor tissues,adjacent normal tissues,and serum from 81 LA-LSCC patients and 50 controls using quantitative real-time reverse transcription polymerase chain reaction(qRT-PCR).We assessed the diagnostic accuracy by Receiver Operating Characteristic curve(ROC curves),clinicopathological associations,survival outcomes(Kaplan-Meier),and treatment response dynamics.Results:miR-449a was significantly downregulated in LA-LSCC tissues(p<0.0001)and serum(p<0.0001),with a strong tissue-serum correlation(R^(2)=0.988).Tissue miR-449a demonstrated a diagnostic accuracy(Area Under the Curve,AUC=0.857),while serum showed moderate accuracy(AUC=0.734).High miR-449a expression correlated with favorable clinicopathological features and improved survival(median overall survival:67.82 vs.23.74 months;p=0.0012).Multivariate analysis confirmed miR-449a as an independent prognostic factor(p<0.001).miR-449a levels increased post-treatment,particularly in responders to chemotherapy/radiation(p<0.0001).Conclusion:miR-449a serves as a non-invasive biomarker for LA-LSCC diagnosis,prognosis,and treatment monitoring.Its dynamic expression highlights potential for risk stratification and therapy response prediction,warranting further validation in larger cohorts.展开更多
Photoreceptor degeneration is a major cause of vision impairment in retinal diseases,for which no effective treatment currently exists.Previous research by our team demonstrated that Lycium barbarum glycopeptide and l...Photoreceptor degeneration is a major cause of vision impairment in retinal diseases,for which no effective treatment currently exists.Previous research by our team demonstrated that Lycium barbarum glycopeptide and luteolin can independently promote photoreceptor survival and function in degenerated mouse retinas,although with limited efficacy.This study evaluated whether a combination of Lycium barbarum glycopeptide and luteolin provides enhanced therapeutic benefits compared with either compound alone.Wild-type mice received a daily oral gavage of Lycium barbarum glycopeptide and luteolin for 7 days prior to intraperitoneal injection of N-nitroso-N-methylurea to induce photoreceptor damage.The treatment continued for an additional week after injury.Retinal structure and function were subsequently assessed using electroretinogram recordings,visual behavior testing,and immunostaining.Western blot analysis was conducted to investigate the underlying protective mechanisms.The results showed that the Lycium barbarum glycopeptide-luteolin mixture significantly increased photoreceptor survival,improved retinal light response,and enhanced visual behavior.Importantly,the combination outperformed either compound alone in protective efficacy.Mechanistic analysis indicated that the mixture suppressed retinal inflammation and modulated the extracellular signal-regulated kinase and Bcl-2-associated X protein/B-cell lymphoma 2 signaling pathways.These findings suggest that the combination of Lycium barbarum glycopeptide and luteolin represents a promising therapeutic strategy for photoreceptor degeneration.展开更多
We explore the potential of conducting an experiment in a low Earth orbit spacecraft and using the Earth as a spin and mass source to constrain beyond-the-standard-model(BSM)long-range spin-and velocity-dependent inte...We explore the potential of conducting an experiment in a low Earth orbit spacecraft and using the Earth as a spin and mass source to constrain beyond-the-standard-model(BSM)long-range spin-and velocity-dependent interactions,which are mediated by the exchange of an ultralight(m_(Z')<10^(-10)eV)or massless intermediate vector boson.The high speed of low-Earth-orbit spacecraft can enhance their sensitivity to velocity-dependent interactions.This periodicity enables efficient signal extraction from background noise,thereby improving the accuracy of the experiment.Combining these advantages,we theoretically demonstrate that the novel spacecraft-Earth model can improve the existing bounds on these exotic interactions by up to three orders of magnitude using the China Space Station(CSS)as a representative low-Earthorbit carrier.If successfully implemented,this model may provide an innovative strategy for detecting ultralight dark matter and yield tighter constraints on certain coupling constants of exotic interactions.展开更多
With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contex...With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contextual understanding,sequential dependencies,and/or data imbalance.This makes distinction between genuine and fabricated news a challenging task.To address this problem,we propose a novel hybrid architecture,T5-SA-LSTM,which synergistically integrates the T5 Transformer for semantically rich contextual embedding with the Self-Attentionenhanced(SA)Long Short-Term Memory(LSTM).The LSTM is trained using the Adam optimizer,which provides faster and more stable convergence compared to the Stochastic Gradient Descend(SGD)and Root Mean Square Propagation(RMSProp).The WELFake and FakeNewsPrediction datasets are used,which consist of labeled news articles having fake and real news samples.Tokenization and Synthetic Minority Over-sampling Technique(SMOTE)methods are used for data preprocessing to ensure linguistic normalization and class imbalance.The incorporation of the Self-Attention(SA)mechanism enables the model to highlight critical words and phrases,thereby enhancing predictive accuracy.The proposed model is evaluated using accuracy,precision,recall(sensitivity),and F1-score as performance metrics.The model achieved 99%accuracy on the WELFake dataset and 96.5%accuracy on the FakeNewsPrediction dataset.It outperformed the competitive schemes such as T5-SA-LSTM(RMSProp),T5-SA-LSTM(SGD)and some other models.展开更多
CR Dhan 310(CRD310),a biofortified rice variety,contains a significantly higher level of grain protein compared with its recurrent parent Naveen(NV),as well as most adapted high-yielding rice varieties in India.Althou...CR Dhan 310(CRD310),a biofortified rice variety,contains a significantly higher level of grain protein compared with its recurrent parent Naveen(NV),as well as most adapted high-yielding rice varieties in India.Although a limited investigation depicted that CRD310 contained higher levels of glutelin and some essential amino acids,detailed biochemical,molecular,and cellular mechanisms remain to be studied.As one of the means to identify the proteins and understand the underlying mechanism of higher proteins accumulation in grains of CRD310,the comparative proteomics was undertaken on grains of CRD310 and NV at the yellow ripening stage.展开更多
Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibi...Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibitory environment for axonal regeneration. Among these inhibitory molecules, myelinassociated inhibitors, including neurite outgrowth inhibitor A, oligodendrocyte myelin glycoprotein, myelin-associated glycoprotein, chondroitin sulfate proteoglycans and repulsive guidance molecule A are of particular importance. Due to their inhibitory nature, they represent exciting molecular targets to study axonal inhibition and regeneration after central injuries. These molecules are mainly produced by neurons, oligodendrocytes, and astrocytes within the scar and in its immediate vicinity. They exert their effects by binding to specific receptors, localized in the membranes of neurons. Receptors for these inhibitory cues include Nogo receptor 1, leucine-rich repeat, and Ig domain containing 1 and p75 neurotrophin receptor/tumor necrosis factor receptor superfamily member 19(that form a receptor complex that binds all myelin-associated inhibitors), and also paired immunoglobulin-like receptor B. Chondroitin sulfate proteoglycans and repulsive guidance molecule A bind to Nogo receptor 1, Nogo receptor 3, receptor protein tyrosine phosphatase σ and leucocyte common antigen related phosphatase, and neogenin, respectively. Once activated, these receptors initiate downstream signaling pathways, the most common amongst them being the Rho A/ROCK signaling pathway. These signaling cascades result in actin depolymerization, neurite outgrowth inhibition, and failure to regenerate after spinal cord injury. Currently, there are no approved pharmacological treatments to overcome spinal cord injuries other than physical rehabilitation and management of the array of symptoms brought on by spinal cord injuries. However, several novel therapies aiming to modulate these inhibitory proteins and/or their receptors are under investigation in ongoing clinical trials. Investigation has also been demonstrating that combinatorial therapies of growth inhibitors with other therapies, such as growth factors or stem-cell therapies, produce stronger results and their potential application in the clinics opens new venues in spinal cord injury treatment.展开更多
High harmonic generation(HHG)provides an experimental method for producing attosecond pulses and probing electron dynamics.Achieving precise dipole phase measurements is critical for tailoring the harmonic emission ph...High harmonic generation(HHG)provides an experimental method for producing attosecond pulses and probing electron dynamics.Achieving precise dipole phase measurements is critical for tailoring the harmonic emission phase and identifying the HHG mechanism.However,achieving this feature by applying traditional two-beam far-field interferometry to solid materials remains challenging.In this study,we present a novel interferometric approach that utilizes a single laser beam to excite two ZnO microwires(MWs)simultaneously,thereby generating coherent high-harmonic sources that form interference fringes in the far-field region.We leverage the diameter-dependent field-enhancement effect in MWs to measure the intensity-dependent fringe shift,revealing that the intraband current mechanism dominates the below-bandgap harmonic,whereas the interband polarization mechanism dominates the above-bandgap harmonic.This study offers a robust method for measuring the dipole phase of solid-state HHG and inspires intensity-modulated high-harmonic applications in coherent imaging and microdevice design.展开更多
Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the clou...Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.展开更多
Layered transition-metal compounds(LTMCs)feature stacked architectures,strong magnetic anisotropy,and tunable magnetic order,making them promising material platforms for low-power spintronic technologies and for enabl...Layered transition-metal compounds(LTMCs)feature stacked architectures,strong magnetic anisotropy,and tunable magnetic order,making them promising material platforms for low-power spintronic technologies and for enabling topological functionalities in the post-Moore era.Here we review recent progress on two-dimensional(2D)magnetism in LTMCs,emphasizing material taxonomy,intrinsic magnetic properties,and external-field controls.This review first presents a classification of LTMCs by crystal structure and chemistry—binary halides,chalcogenides,and ternary families(e.g.,MPX_(3),M_(m)X_(n)Te_(k),MnBi_(2)Te_(4))—followed by a summary of their coupling mechanisms,ordering temperatures,and dimensional effects.It then analyzes the modulation of exchange interactions,magnetic anisotropy,and topological states by electric-field gating,strain engineering,and ion intercalation,with representative experimental demonstrations.Notable advances include room-temperature ferromagnetic metals and semiconductors,observation of the quantum anomalous Hall effect(QAHE)in MnBi2Te4,and synergistic control of magnetic-topological states under multiple external stimuli.Persistent challenges involve the limited availability of intrinsic 2D magnetic semiconductors with high Curie temperatures(Tc),incomplete understanding of the microscopic couplings at interfaces and under quantum confinement,and device-level stability.We conclude by outlining opportunities that lie in the integration of multiscale characterization,first-principles theory,and cross-scale fabrication to precisely co-engineer magnetism,topology,and electronic structure,thereby advancing LTMCs toward spintronic and topological-quantum applications.展开更多
It was in the 1980s that research on somatostatin(SST)in Alzheimer’s disease(AD)truly gained traction,demonstrating consistent colocalization with amyloid-β(Aβ),along with massive SST/SST cell losses(Almeida,2024)....It was in the 1980s that research on somatostatin(SST)in Alzheimer’s disease(AD)truly gained traction,demonstrating consistent colocalization with amyloid-β(Aβ),along with massive SST/SST cell losses(Almeida,2024).Although the field already had some grasp over the neuroendocrine and hypothalamic functions of the peptide,very little was known about the GABAergic interneurons(SST-INs)that synthesize it in cortical/hippocampal regions.Quite excitingly,over 40 years later,research has grown effervescent.展开更多
Bone resorption is a vital physiological process that enables skeletal remodeling,maintenance,and adaptation to mechanical forces throughout life.While tightly regulated under the physiological state,its dysregulation...Bone resorption is a vital physiological process that enables skeletal remodeling,maintenance,and adaptation to mechanical forces throughout life.While tightly regulated under the physiological state,its dysregulation contributes to pathological conditions such as osteoporosis,rheumatoid arthritis,and periodontitis.Periodontitis is a highly prevalent chronic inflammatory disease driven by dysbiotic biofilms that disrupt the oral microbiome,leading to the progressive breakdown of the periodontal ligament,cementum,and alveolar bone and ultimately resulting in tooth loss.This review outlines the molecular and cellular mechanisms underlying periodontitis,focusing on osteoclastogenesis,the differentiation and activation of osteoclasts,the primary mediators of bone resorption.Key transcriptional regulators,including NFATc1,c-Fos,and c-Src are discussed alongside major signaling pathways such as Mitogen Activated Protein Kinase(MAPK),Janus Tyrosine Kinase/Signal Transducer and Activator of Transcription(JAK/STAT),Nuclear Factor Kappa B(NF-κB),and Phosphoinositide 3-kinase(PI3K)/Akt,to elucidate their roles in the initiation and progression of periodontal bone loss.These pathways orchestrate the inflammatory response and osteoclast activity,underscoring their relevance in periodontitis and other osteolytic conditions.Hallmark features of periodontitis,including chronic inflammation,immune dysregulation,and tissue destruction are highlighted,with emphasis on current and emerging therapeutic strategies targeting these molecular pathways.Special attention is given to small molecules,biologics,and natural compounds that have the potential to modulate key signaling pathways.Although advances in understanding these mechanisms have identified promising therapeutic targets,translation into effective clinical interventions remains challenging.Continued research into regulating bone-resorptive signaling pathways is essential for developing more effective treatments for periodontitis and related inflammatory bone diseases.展开更多
Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to instal...Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.展开更多
This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels.To evaluate the effect of ra...This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels.To evaluate the effect of raw material morphology on panel’s performance,two types of cotton stalk-based panels were developed:one using long strips,maintaining fiber continuity,and the other using ground particles,representing conventional processing.A wood strand-based panel made from commercial southern yellow pine strands served as the control.All panels were bonded using phenol-formaldehyde resin and hot-pressed to a target thickness of 12.7 mm and density of 640 kg/m^(3).Their mechanical and physical properties were evaluated through internal bond,bending,thickness swelling,and water absorption tests.Both cotton stalk-based panels showed improved bonding performance compared to the control.The internal bond of the strip-based panel was nearly four times higher than that of the control,while the particlebased panel exceeded it by a factor of two.The strip-based panel showed approximately 15% lower bending stiffness than the wood strand-based panel,yet it surpassed it in load-carrying capacity by 5%.In contrast,the particleboard showed significantly lower bending performance than the strip-based and control panels,despite particle processing being a more conventional method.Both cotton stalk-based panels exhibited higher water absorption and thickness swelling than the wood strand panel.Overall,cotton stalk-based panels—particularly those using strip processing—show promisingmechanical properties,suggesting potential applications in sheathing,furniture,and interior paneling.However,improvements in dimensional stability are needed for broader use.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.展开更多
Ascorbate(Asc),commonly known as vitamin C,is a vital molecule for plant growth,development,and stress resilience.It is also known to play a crucial role in various physiological processes,including photosynthesis,cel...Ascorbate(Asc),commonly known as vitamin C,is a vital molecule for plant growth,development,and stress resilience.It is also known to play a crucial role in various physiological processes,including photosynthesis,cell division,and differentiation.This article thoroughly explores the processes governing the metabolism of Asc in plants and its roles in physiological functions.It lays down a robust theoretical groundwork for delving into Asc production,transportation,functions,and its potential applications in stress alleviation and horticulture.Furthermore,recent studies indicate that Asc plays a role in regulating fruit development and affecting postharvest storage characteristics,thereby influencing fruit ripening and resilience to stress.Hence,there is a growing importance in studying the synthesis and utilization of Asc in plants.Although the critical role of Asc in controlling plant redox signals has been extensively studied,the precise mechanisms by which it manages cellular redox homeostasis to maintain the equilibrium between reactive oxygen scavenging and cell redox signaling remain elusive.This gap in knowledge presents fresh opportunities to explore how the production of Asc in plants is regulated and how plants react to environmental stressors.Furthermore,this article delves into the potential for a comprehensive investigation into the essential function of Asc in fruits,the development of Asc-rich fruits,and the enhancement of postharvest storage properties.展开更多
Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders...Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.展开更多
Different forms of programmed cell death have been described to participate in the degeneration of dopaminergic neurons in Parkinson’s disease(PD).Given the critical role that disturbance of mitochondrial homeostasis...Different forms of programmed cell death have been described to participate in the degeneration of dopaminergic neurons in Parkinson’s disease(PD).Given the critical role that disturbance of mitochondrial homeostasis plays in the pathogenesis of PD,apoptosis can be reasonably considered as one of the cell death pathways involved in neuronal loss(Schon and Przedborski,2011).Multiple lines of evidence support that proposal such as the observations in postmortem human brain samples of PD patients including mitochondrial complex I deficiency,reactive oxygen species generation,and oxidative damage to lipids,proteins,and DNA,among others.展开更多
Microbe-based soil inoculants offer a promising approach to sustainable agriculture by reducing reliance on agrochemicals and minimizing environmental damages.The heavy use of chemicals in conventional agriculture pos...Microbe-based soil inoculants offer a promising approach to sustainable agriculture by reducing reliance on agrochemicals and minimizing environmental damages.The heavy use of chemicals in conventional agriculture poses significant challenges to crop production and environmental health.This review explores the integration of microbe-based inoculants,strigolactones(SLs),and nanotechnology to enhance agricultural sustainability.Nanobiofertilizers containing nanoparticles such as Ag,Zn,Fe,ZnO,TiO_(2),SiO_(2),and MgO can provide essential crop protection,while algae species like Chlorella spp.,Arthrospira spp.,and Dunaliella spp.serve as promising biostimulants and biofertilizers.Additionally,plant growth-promoting microorganisms such as Rhizobium,Azotobacter,Azospirillum,Pseudomonas,Bacillus,and Trichoderma,alongside synthetic SLs like GR24,contribute to improving crop yield and stress tolerance.Strigolactone signaling pathways have also been explored for their roles in plant growth and resilience.Recent innovations in biofertilizer research,particularly in genomics,transcriptomics,and metabolomics,have advanced our understanding of plant-microbe interactions.These omics-based technologies help develop tailored biofertilizer formulations suited to specific crops,soils,and environmental conditions.The combination of biofertilizers,nanoparticles,and SLs fosters nutrient uptake,enhances stress tolerance,and promotes overall plant growth.Case studies from various agroecosystems show that biofertilizers can improve soil health,boost crop yields,reduce chemical fertilizer dependency,and lower environmental impacts.With precision farming,biofertilizers offer sustainable solutions to various challenges,including climate change,soil degradation,and food security.This review discusses the mechanisms by which GR24,nanoparticle,and microbe-based biofertilizers benefit plants,emphasizing their potential for sustainable agriculture and future challenges.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
The visual system of teleost fish grows continuously,which is a useful model for studying regeneration of the central nervous system.Glial cells are key for this process,but their contribution is still not well define...The visual system of teleost fish grows continuously,which is a useful model for studying regeneration of the central nervous system.Glial cells are key for this process,but their contribution is still not well defined.We followed oligodendrocytes in the visual system of adult zebrafish during regeneration of the optic nerve at 6,24,and 72 hours post-lesion and at 7 and 14 days post-lesion via the sox10:tagRFP transgenic line and confocal microscopy.To understand the changes that these oligodendrocytes undergo during regeneration,we used Sox2 immunohistochemistry,a stem cell marker involved in oligodendrocyte differentiation.We also used the Click-iT™ Plus TUNEL assay to study cell death and a BrdU assay to determine cell proliferation.Before optic nerve crush,sox10:tagRFP oligodendrocytes are located in the retina,in the optic nerve head,and through all the entire optic nerve.Sox2-positive cells are present in the peripheral germinal zone,the mature retina,and the optic nerve.After optic nerve crush,sox10:tagRFP cells disappeared from the optic nerve crush zone,suggesting that they died,although they were not TUNEL positive.Concomitantly,the number of Sox2-positive cells increased around the crushed area,the optic nerve head,and the retina.Then,between 24 hours post-lesion and 14 days post-lesion,double sox10:tagRFP/Sox2-positive cells were detected in the retina,optic nerve head,and whole optic nerve,together with a proliferation response at 72 hours post-lesion.Our results confirm that a degenerating process may occur prior to regeneration.First,sox10:tagRFP oligodendrocytes that surround the degenerated axons stop wrapping them,change their“myelinating oligodendrocyte”morphology to a“nonmyelinating oligodendrocyte”morphology,and die.Then,residual oligodendrocyte progenitor cells in the optic nerve and retina proliferate and differentiate for the purpose of remyelination.As new axons arise from the surviving retinal ganglion cells,new sox10:tagRFP oligodendrocytes arise from residual oligodendrocyte progenitor cells to guide,nourish and myelinate them.Thus,oligodendrocytes play an active role in zebrafish axon regeneration and remyelination.展开更多
基金The authors extend their appreciation to Taif University,Saudi Arabia,for supporting this work through project No.(TU-DSPP-2024-54).
文摘Background:Locally advanced laryngeal squamous cell carcinoma(LA-LSCC)presents clinical challenges due to the lack of reliable non-invasive biomarkers.This study aimed to evaluate miR-449a as a diagnostic and prognostic biomarker in LA-LSCC.Methods:miR-449a expression was analyzed in tumor tissues,adjacent normal tissues,and serum from 81 LA-LSCC patients and 50 controls using quantitative real-time reverse transcription polymerase chain reaction(qRT-PCR).We assessed the diagnostic accuracy by Receiver Operating Characteristic curve(ROC curves),clinicopathological associations,survival outcomes(Kaplan-Meier),and treatment response dynamics.Results:miR-449a was significantly downregulated in LA-LSCC tissues(p<0.0001)and serum(p<0.0001),with a strong tissue-serum correlation(R^(2)=0.988).Tissue miR-449a demonstrated a diagnostic accuracy(Area Under the Curve,AUC=0.857),while serum showed moderate accuracy(AUC=0.734).High miR-449a expression correlated with favorable clinicopathological features and improved survival(median overall survival:67.82 vs.23.74 months;p=0.0012).Multivariate analysis confirmed miR-449a as an independent prognostic factor(p<0.001).miR-449a levels increased post-treatment,particularly in responders to chemotherapy/radiation(p<0.0001).Conclusion:miR-449a serves as a non-invasive biomarker for LA-LSCC diagnosis,prognosis,and treatment monitoring.Its dynamic expression highlights potential for risk stratification and therapy response prediction,warranting further validation in larger cohorts.
基金Natural Science Foundation of Guangdong Province,No.2023A1515012397(to YX)the National Natural Science Foundation of China,No.82074169(to XM)+2 种基金the Guangdong Basic and Applied Basic Research Foundation,No.2021A1515012473(to XM)and Project of Administration of Traditional Chinese Medicine of Guangdong Province,No.20202045(to XM)Aier Eye Hospital Group,No.AF2019001(to ST,KFS,YX,and XM).
文摘Photoreceptor degeneration is a major cause of vision impairment in retinal diseases,for which no effective treatment currently exists.Previous research by our team demonstrated that Lycium barbarum glycopeptide and luteolin can independently promote photoreceptor survival and function in degenerated mouse retinas,although with limited efficacy.This study evaluated whether a combination of Lycium barbarum glycopeptide and luteolin provides enhanced therapeutic benefits compared with either compound alone.Wild-type mice received a daily oral gavage of Lycium barbarum glycopeptide and luteolin for 7 days prior to intraperitoneal injection of N-nitroso-N-methylurea to induce photoreceptor damage.The treatment continued for an additional week after injury.Retinal structure and function were subsequently assessed using electroretinogram recordings,visual behavior testing,and immunostaining.Western blot analysis was conducted to investigate the underlying protective mechanisms.The results showed that the Lycium barbarum glycopeptide-luteolin mixture significantly increased photoreceptor survival,improved retinal light response,and enhanced visual behavior.Importantly,the combination outperformed either compound alone in protective efficacy.Mechanistic analysis indicated that the mixture suppressed retinal inflammation and modulated the extracellular signal-regulated kinase and Bcl-2-associated X protein/B-cell lymphoma 2 signaling pathways.These findings suggest that the combination of Lycium barbarum glycopeptide and luteolin represents a promising therapeutic strategy for photoreceptor degeneration.
基金partially supported by the National Key R&D Program of China (Grant No.2023YFA16067003)the National Science Foundation of China (Grant Nos.12435007 and 12522505)。
文摘We explore the potential of conducting an experiment in a low Earth orbit spacecraft and using the Earth as a spin and mass source to constrain beyond-the-standard-model(BSM)long-range spin-and velocity-dependent interactions,which are mediated by the exchange of an ultralight(m_(Z')<10^(-10)eV)or massless intermediate vector boson.The high speed of low-Earth-orbit spacecraft can enhance their sensitivity to velocity-dependent interactions.This periodicity enables efficient signal extraction from background noise,thereby improving the accuracy of the experiment.Combining these advantages,we theoretically demonstrate that the novel spacecraft-Earth model can improve the existing bounds on these exotic interactions by up to three orders of magnitude using the China Space Station(CSS)as a representative low-Earthorbit carrier.If successfully implemented,this model may provide an innovative strategy for detecting ultralight dark matter and yield tighter constraints on certain coupling constants of exotic interactions.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R195)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contextual understanding,sequential dependencies,and/or data imbalance.This makes distinction between genuine and fabricated news a challenging task.To address this problem,we propose a novel hybrid architecture,T5-SA-LSTM,which synergistically integrates the T5 Transformer for semantically rich contextual embedding with the Self-Attentionenhanced(SA)Long Short-Term Memory(LSTM).The LSTM is trained using the Adam optimizer,which provides faster and more stable convergence compared to the Stochastic Gradient Descend(SGD)and Root Mean Square Propagation(RMSProp).The WELFake and FakeNewsPrediction datasets are used,which consist of labeled news articles having fake and real news samples.Tokenization and Synthetic Minority Over-sampling Technique(SMOTE)methods are used for data preprocessing to ensure linguistic normalization and class imbalance.The incorporation of the Self-Attention(SA)mechanism enables the model to highlight critical words and phrases,thereby enhancing predictive accuracy.The proposed model is evaluated using accuracy,precision,recall(sensitivity),and F1-score as performance metrics.The model achieved 99%accuracy on the WELFake dataset and 96.5%accuracy on the FakeNewsPrediction dataset.It outperformed the competitive schemes such as T5-SA-LSTM(RMSProp),T5-SA-LSTM(SGD)and some other models.
基金supported by the director of Indian Council of Agricultural Research and International Rice Research Institute (ICAR-CRRI), Cuttack, Indiathe coordinator of the ICAR-sponsored project ‘C-reactive protein (CRP) in Biofortification in Selected Crops’, India
文摘CR Dhan 310(CRD310),a biofortified rice variety,contains a significantly higher level of grain protein compared with its recurrent parent Naveen(NV),as well as most adapted high-yielding rice varieties in India.Although a limited investigation depicted that CRD310 contained higher levels of glutelin and some essential amino acids,detailed biochemical,molecular,and cellular mechanisms remain to be studied.As one of the means to identify the proteins and understand the underlying mechanism of higher proteins accumulation in grains of CRD310,the comparative proteomics was undertaken on grains of CRD310 and NV at the yellow ripening stage.
基金a Ph D fellowship by FCT-Fundacao para a Ciência Tecnologia (SFRH/BD/135868/2018)(to SSC)。
文摘Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibitory environment for axonal regeneration. Among these inhibitory molecules, myelinassociated inhibitors, including neurite outgrowth inhibitor A, oligodendrocyte myelin glycoprotein, myelin-associated glycoprotein, chondroitin sulfate proteoglycans and repulsive guidance molecule A are of particular importance. Due to their inhibitory nature, they represent exciting molecular targets to study axonal inhibition and regeneration after central injuries. These molecules are mainly produced by neurons, oligodendrocytes, and astrocytes within the scar and in its immediate vicinity. They exert their effects by binding to specific receptors, localized in the membranes of neurons. Receptors for these inhibitory cues include Nogo receptor 1, leucine-rich repeat, and Ig domain containing 1 and p75 neurotrophin receptor/tumor necrosis factor receptor superfamily member 19(that form a receptor complex that binds all myelin-associated inhibitors), and also paired immunoglobulin-like receptor B. Chondroitin sulfate proteoglycans and repulsive guidance molecule A bind to Nogo receptor 1, Nogo receptor 3, receptor protein tyrosine phosphatase σ and leucocyte common antigen related phosphatase, and neogenin, respectively. Once activated, these receptors initiate downstream signaling pathways, the most common amongst them being the Rho A/ROCK signaling pathway. These signaling cascades result in actin depolymerization, neurite outgrowth inhibition, and failure to regenerate after spinal cord injury. Currently, there are no approved pharmacological treatments to overcome spinal cord injuries other than physical rehabilitation and management of the array of symptoms brought on by spinal cord injuries. However, several novel therapies aiming to modulate these inhibitory proteins and/or their receptors are under investigation in ongoing clinical trials. Investigation has also been demonstrating that combinatorial therapies of growth inhibitors with other therapies, such as growth factors or stem-cell therapies, produce stronger results and their potential application in the clinics opens new venues in spinal cord injury treatment.
基金supported by the National Key R&D Program of China (Grant Nos.2023YFA1406801 and 2022YFA1604301)the National Natural Science Foundation of China (Grant Nos.12434013,12595343,12404393,and 12174011)。
文摘High harmonic generation(HHG)provides an experimental method for producing attosecond pulses and probing electron dynamics.Achieving precise dipole phase measurements is critical for tailoring the harmonic emission phase and identifying the HHG mechanism.However,achieving this feature by applying traditional two-beam far-field interferometry to solid materials remains challenging.In this study,we present a novel interferometric approach that utilizes a single laser beam to excite two ZnO microwires(MWs)simultaneously,thereby generating coherent high-harmonic sources that form interference fringes in the far-field region.We leverage the diameter-dependent field-enhancement effect in MWs to measure the intensity-dependent fringe shift,revealing that the intraband current mechanism dominates the below-bandgap harmonic,whereas the interband polarization mechanism dominates the above-bandgap harmonic.This study offers a robust method for measuring the dipole phase of solid-state HHG and inspires intensity-modulated high-harmonic applications in coherent imaging and microdevice design.
基金Supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R896).
文摘Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.
基金supported by the National KeyR&D Program of China(Grant No.2024YFB3817400)the National Natural Science Foundation of China(Grants No.12274276 and No.U24A6002)+1 种基金the Natural Science Foundation of Shanxi Province(China)(Grant No.202403021223008)Supported by Scientific and Technology Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2024Q017 and No.2025L043).
文摘Layered transition-metal compounds(LTMCs)feature stacked architectures,strong magnetic anisotropy,and tunable magnetic order,making them promising material platforms for low-power spintronic technologies and for enabling topological functionalities in the post-Moore era.Here we review recent progress on two-dimensional(2D)magnetism in LTMCs,emphasizing material taxonomy,intrinsic magnetic properties,and external-field controls.This review first presents a classification of LTMCs by crystal structure and chemistry—binary halides,chalcogenides,and ternary families(e.g.,MPX_(3),M_(m)X_(n)Te_(k),MnBi_(2)Te_(4))—followed by a summary of their coupling mechanisms,ordering temperatures,and dimensional effects.It then analyzes the modulation of exchange interactions,magnetic anisotropy,and topological states by electric-field gating,strain engineering,and ion intercalation,with representative experimental demonstrations.Notable advances include room-temperature ferromagnetic metals and semiconductors,observation of the quantum anomalous Hall effect(QAHE)in MnBi2Te4,and synergistic control of magnetic-topological states under multiple external stimuli.Persistent challenges involve the limited availability of intrinsic 2D magnetic semiconductors with high Curie temperatures(Tc),incomplete understanding of the microscopic couplings at interfaces and under quantum confinement,and device-level stability.We conclude by outlining opportunities that lie in the integration of multiscale characterization,first-principles theory,and cross-scale fabrication to precisely co-engineer magnetism,topology,and electronic structure,thereby advancing LTMCs toward spintronic and topological-quantum applications.
文摘It was in the 1980s that research on somatostatin(SST)in Alzheimer’s disease(AD)truly gained traction,demonstrating consistent colocalization with amyloid-β(Aβ),along with massive SST/SST cell losses(Almeida,2024).Although the field already had some grasp over the neuroendocrine and hypothalamic functions of the peptide,very little was known about the GABAergic interneurons(SST-INs)that synthesize it in cortical/hippocampal regions.Quite excitingly,over 40 years later,research has grown effervescent.
基金supported by grant provided by the Sao Paulo Research Foundation-FAPESP.Grant#2023/15750-7。
文摘Bone resorption is a vital physiological process that enables skeletal remodeling,maintenance,and adaptation to mechanical forces throughout life.While tightly regulated under the physiological state,its dysregulation contributes to pathological conditions such as osteoporosis,rheumatoid arthritis,and periodontitis.Periodontitis is a highly prevalent chronic inflammatory disease driven by dysbiotic biofilms that disrupt the oral microbiome,leading to the progressive breakdown of the periodontal ligament,cementum,and alveolar bone and ultimately resulting in tooth loss.This review outlines the molecular and cellular mechanisms underlying periodontitis,focusing on osteoclastogenesis,the differentiation and activation of osteoclasts,the primary mediators of bone resorption.Key transcriptional regulators,including NFATc1,c-Fos,and c-Src are discussed alongside major signaling pathways such as Mitogen Activated Protein Kinase(MAPK),Janus Tyrosine Kinase/Signal Transducer and Activator of Transcription(JAK/STAT),Nuclear Factor Kappa B(NF-κB),and Phosphoinositide 3-kinase(PI3K)/Akt,to elucidate their roles in the initiation and progression of periodontal bone loss.These pathways orchestrate the inflammatory response and osteoclast activity,underscoring their relevance in periodontitis and other osteolytic conditions.Hallmark features of periodontitis,including chronic inflammation,immune dysregulation,and tissue destruction are highlighted,with emphasis on current and emerging therapeutic strategies targeting these molecular pathways.Special attention is given to small molecules,biologics,and natural compounds that have the potential to modulate key signaling pathways.Although advances in understanding these mechanisms have identified promising therapeutic targets,translation into effective clinical interventions remains challenging.Continued research into regulating bone-resorptive signaling pathways is essential for developing more effective treatments for periodontitis and related inflammatory bone diseases.
基金funded by Princess Nourah bint Abdulrahman University Researchers Support-ing Project number(PNURSP2026R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Motor imbalance is a critical failure mode in rotating machinery,potentially causing severe equipment damage if undetected.Traditional vibration-based diagnostic methods rely on direct sensor contact,leading to installation challenges and measurement artifacts that can compromise accuracy.This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar.A dataset of 1802 experimental trials was sourced,covering four imbalance levels(0,10,20,30 g)across varying motor speeds(500–1500 rpm)and load torques(0–3 Nm).Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second for 30-s intervals,preserving both amplitude and phase information for analysis.A multi-domain feature extraction methodology captured imbalance signatures in time,frequency,and complex signal domains.From 65 initial features,statistical analysis using Kruskal–Wallis tests identified significant descriptors,and recursive feature elimination with Random Forest reduced the feature set to 20 dimensions,achieving 69%dimensionality reduction without loss of performance.Six machine learning algorithms,Random Forest,Extra Trees Classifier,Extreme Gradient Boosting,Categorical Boosting,Support Vector Machine with radial basis function kernel,and k-Nearest Neighbors were evaluated with grid-search hyperparameter optimization and five-fold cross-validation.The Extra Trees Classifier achieved the best performance with 98.52%test accuracy,98%cross-validation accuracy,and minimal variance,maintaining per-class precision and recall above 97%.Its superior performance is attributed to its randomized split selection and full bootstrapping strategy,which reduce variance and overfitting while effectively capturing the nonlinear feature interactions and non-normal distributions present in the dataset.The model’s average inference time of 70 ms enables near real-time deployment.Comparative analysis demonstrates that the radar-based framework matches or exceeds traditional contact-based methods while eliminating their inherent limitations,providing a robust,scalable,and noninvasive solution for industrial motor condition monitoring,particularly in hazardous or space-constrained environments.
基金supported by the intramural research program of the U.S.Department of Agriculture,National Institute of Food and Agriculture,Biobased Economy Through Biobased Products,under Award#2023-68016-40132.
文摘This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels.To evaluate the effect of raw material morphology on panel’s performance,two types of cotton stalk-based panels were developed:one using long strips,maintaining fiber continuity,and the other using ground particles,representing conventional processing.A wood strand-based panel made from commercial southern yellow pine strands served as the control.All panels were bonded using phenol-formaldehyde resin and hot-pressed to a target thickness of 12.7 mm and density of 640 kg/m^(3).Their mechanical and physical properties were evaluated through internal bond,bending,thickness swelling,and water absorption tests.Both cotton stalk-based panels showed improved bonding performance compared to the control.The internal bond of the strip-based panel was nearly four times higher than that of the control,while the particlebased panel exceeded it by a factor of two.The strip-based panel showed approximately 15% lower bending stiffness than the wood strand-based panel,yet it surpassed it in load-carrying capacity by 5%.In contrast,the particleboard showed significantly lower bending performance than the strip-based and control panels,despite particle processing being a more conventional method.Both cotton stalk-based panels exhibited higher water absorption and thickness swelling than the wood strand panel.Overall,cotton stalk-based panels—particularly those using strip processing—show promisingmechanical properties,suggesting potential applications in sheathing,furniture,and interior paneling.However,improvements in dimensional stability are needed for broader use.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
基金supported by the Lendület/Momentum Programme of the Hungarian Academy of Sciencesthe National Research, Development, and Innovation Office, Hungary (Grant Nos. LP2024/21 and K146791)+2 种基金Bayers fellowship program MEDHA and Department of Botany, University of Calicutthe financial assistance provided in the form of Junior Research Fellowship from the University Grants Commission (UGC), Indiathe financial assistance provided by the Council for Scientific and Industrial Research(CSIR), India
文摘Ascorbate(Asc),commonly known as vitamin C,is a vital molecule for plant growth,development,and stress resilience.It is also known to play a crucial role in various physiological processes,including photosynthesis,cell division,and differentiation.This article thoroughly explores the processes governing the metabolism of Asc in plants and its roles in physiological functions.It lays down a robust theoretical groundwork for delving into Asc production,transportation,functions,and its potential applications in stress alleviation and horticulture.Furthermore,recent studies indicate that Asc plays a role in regulating fruit development and affecting postharvest storage characteristics,thereby influencing fruit ripening and resilience to stress.Hence,there is a growing importance in studying the synthesis and utilization of Asc in plants.Although the critical role of Asc in controlling plant redox signals has been extensively studied,the precise mechanisms by which it manages cellular redox homeostasis to maintain the equilibrium between reactive oxygen scavenging and cell redox signaling remain elusive.This gap in knowledge presents fresh opportunities to explore how the production of Asc in plants is regulated and how plants react to environmental stressors.Furthermore,this article delves into the potential for a comprehensive investigation into the essential function of Asc in fruits,the development of Asc-rich fruits,and the enhancement of postharvest storage properties.
基金supported by the NIA/NIH(1K01AG060040).Studies performed by JN were funded by the NICHD/NIH(5R00HD096117)Microscopy Core Facility supported,in part,with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.
文摘Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.
基金supported by the Spanish Ministerio de Ciencia e Innovación/Agencia Española de Investigación(PID2021-124096OB-I00)(to JLV)JGR was granted by Demensfonden,The Royal Physiografic Society of Lund,Neurofonden,The Greta och Johan Kocks stiftelser,and Bertil och Ebon Norlins stiftelse.
文摘Different forms of programmed cell death have been described to participate in the degeneration of dopaminergic neurons in Parkinson’s disease(PD).Given the critical role that disturbance of mitochondrial homeostasis plays in the pathogenesis of PD,apoptosis can be reasonably considered as one of the cell death pathways involved in neuronal loss(Schon and Przedborski,2011).Multiple lines of evidence support that proposal such as the observations in postmortem human brain samples of PD patients including mitochondrial complex I deficiency,reactive oxygen species generation,and oxidative damage to lipids,proteins,and DNA,among others.
基金Siksha‘O’Anusandhan(Deemed to be University),IndiaGraphic Era(Deemed to be University),India+1 种基金Bankura Sammilani College,IndiaRaiganj University,India for their support。
文摘Microbe-based soil inoculants offer a promising approach to sustainable agriculture by reducing reliance on agrochemicals and minimizing environmental damages.The heavy use of chemicals in conventional agriculture poses significant challenges to crop production and environmental health.This review explores the integration of microbe-based inoculants,strigolactones(SLs),and nanotechnology to enhance agricultural sustainability.Nanobiofertilizers containing nanoparticles such as Ag,Zn,Fe,ZnO,TiO_(2),SiO_(2),and MgO can provide essential crop protection,while algae species like Chlorella spp.,Arthrospira spp.,and Dunaliella spp.serve as promising biostimulants and biofertilizers.Additionally,plant growth-promoting microorganisms such as Rhizobium,Azotobacter,Azospirillum,Pseudomonas,Bacillus,and Trichoderma,alongside synthetic SLs like GR24,contribute to improving crop yield and stress tolerance.Strigolactone signaling pathways have also been explored for their roles in plant growth and resilience.Recent innovations in biofertilizer research,particularly in genomics,transcriptomics,and metabolomics,have advanced our understanding of plant-microbe interactions.These omics-based technologies help develop tailored biofertilizer formulations suited to specific crops,soils,and environmental conditions.The combination of biofertilizers,nanoparticles,and SLs fosters nutrient uptake,enhances stress tolerance,and promotes overall plant growth.Case studies from various agroecosystems show that biofertilizers can improve soil health,boost crop yields,reduce chemical fertilizer dependency,and lower environmental impacts.With precision farming,biofertilizers offer sustainable solutions to various challenges,including climate change,soil degradation,and food security.This review discusses the mechanisms by which GR24,nanoparticle,and microbe-based biofertilizers benefit plants,emphasizing their potential for sustainable agriculture and future challenges.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金supported by the Lanzadera TCUE and C2 program(Universidad de Salamanca)(to ASL)the Spanish National Research Council(CSIC)funded by the Junta de Castilla y León and co-financed by the European Regional Development Fund(ERDF“Europe drives our growth”):Internationalization Project“CL-EI-2021-08-IBFG Unit of Excellence”,Grant(PID2022-138478OA-100)funded by MICIU/AEI/10.13039/501100011033 and,by FEDER,UE(to MGM)+3 种基金Junta de Castilla y León(SA225P23)Gerencia Regional de Salud(2701/A1/2023)(to AV)the Plan Especial Grado Medicina(USAL)(to CPM)a Ramón y Cajal researcher:Grant RYC2021-033684-I funded by MICIU/AEI/10.13039/501100011033 and,by European Union NextGenerationEU/PRTR.
文摘The visual system of teleost fish grows continuously,which is a useful model for studying regeneration of the central nervous system.Glial cells are key for this process,but their contribution is still not well defined.We followed oligodendrocytes in the visual system of adult zebrafish during regeneration of the optic nerve at 6,24,and 72 hours post-lesion and at 7 and 14 days post-lesion via the sox10:tagRFP transgenic line and confocal microscopy.To understand the changes that these oligodendrocytes undergo during regeneration,we used Sox2 immunohistochemistry,a stem cell marker involved in oligodendrocyte differentiation.We also used the Click-iT™ Plus TUNEL assay to study cell death and a BrdU assay to determine cell proliferation.Before optic nerve crush,sox10:tagRFP oligodendrocytes are located in the retina,in the optic nerve head,and through all the entire optic nerve.Sox2-positive cells are present in the peripheral germinal zone,the mature retina,and the optic nerve.After optic nerve crush,sox10:tagRFP cells disappeared from the optic nerve crush zone,suggesting that they died,although they were not TUNEL positive.Concomitantly,the number of Sox2-positive cells increased around the crushed area,the optic nerve head,and the retina.Then,between 24 hours post-lesion and 14 days post-lesion,double sox10:tagRFP/Sox2-positive cells were detected in the retina,optic nerve head,and whole optic nerve,together with a proliferation response at 72 hours post-lesion.Our results confirm that a degenerating process may occur prior to regeneration.First,sox10:tagRFP oligodendrocytes that surround the degenerated axons stop wrapping them,change their“myelinating oligodendrocyte”morphology to a“nonmyelinating oligodendrocyte”morphology,and die.Then,residual oligodendrocyte progenitor cells in the optic nerve and retina proliferate and differentiate for the purpose of remyelination.As new axons arise from the surviving retinal ganglion cells,new sox10:tagRFP oligodendrocytes arise from residual oligodendrocyte progenitor cells to guide,nourish and myelinate them.Thus,oligodendrocytes play an active role in zebrafish axon regeneration and remyelination.
