目的:构建一套科学客观的能力评价体系,用于评估临床研究协调员(clinical research coordinator,CRC)在临床研究中的能力水平。方法:通过本中心既往的项目管理工作经验及文献回顾,确定CRC临床研究能力的评估指标,结合临床试验开展流程...目的:构建一套科学客观的能力评价体系,用于评估临床研究协调员(clinical research coordinator,CRC)在临床研究中的能力水平。方法:通过本中心既往的项目管理工作经验及文献回顾,确定CRC临床研究能力的评估指标,结合临床试验开展流程和项目质控结果,搭建CRC的评价体系,并将该评价体系应用于CRC在临床研究中实际工作能力的评估,验证评价体系的客观性、科学性以及可行性。结果:该评价体系结果与既往人工评估结果一致,年资和学历影响临床研究能力。结论:该评价体系能够科学客观地反映CRC的临床研究能力,为CRC的职业发展和管理层的决策提供理论基础。展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third ...Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can...The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.展开更多
A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or l...A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.展开更多
Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges...Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.展开更多
文摘目的:构建一套科学客观的能力评价体系,用于评估临床研究协调员(clinical research coordinator,CRC)在临床研究中的能力水平。方法:通过本中心既往的项目管理工作经验及文献回顾,确定CRC临床研究能力的评估指标,结合临床试验开展流程和项目质控结果,搭建CRC的评价体系,并将该评价体系应用于CRC在临床研究中实际工作能力的评估,验证评价体系的客观性、科学性以及可行性。结果:该评价体系结果与既往人工评估结果一致,年资和学历影响临床研究能力。结论:该评价体系能够科学客观地反映CRC的临床研究能力,为CRC的职业发展和管理层的决策提供理论基础。
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金supported by the National Natural Science Foundation of China(Grant No.82373475).
文摘Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金Hongguang Wu,Both authors contributed equally to this work and share first authorshipLing Dong,Both authors contributed equally to this work and share first authorship。
文摘The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.
基金The authors extend their appreciation to King Saud University,Saudi Arabia for funding this work through the Ongoing Research Funding Program(ORF-2025-704),King Saud University,Riyadh,Saudi Arabia.
文摘A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.
基金supported by the National Natural Science Foundations of China,Nos.82272163,82472164(both MF)。
文摘Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.
