Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Unveiling the brain’s symphony:exploring the necessity and sufficiency of neural networks in behavior control

Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully attributable to specific brain areas alone.Instead,they involve connectivity among brain areas,whether close or distant.At that time,this approach was considered the optimal way to dissect brain circuitry and function.These pioneering efforts opened the field to explore the necessity or sufficiency of brain areas in controlling behavior and hence dissecting brain function.However,the connectivity of the brain and the mechanisms through which various brain regions regulate specific behaviors,either individually or collaboratively,remain largely elusive.Utilizing animal models,researchers have endeavored to unravel the necessity or sufficiency of specific brain areas in influencing behavior;however,no clear associations have been firmly established.

Women in visual neural regeneration research

The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).

Commentary on:“Human neural stem cell-derived artificial organelles to improve oxidative phosphorylation”

Mitochondrial function is fundamental to neuroregeneration,particularly in neurons,where high energy demands are essential for repair and recovery(Patrón and Zinsmaier,2016;Beckervordersandforth et al.,2017;Iwata et al.,2023).Mitochondrial dysfunction,characterized by an imbalance in ATP levels and excessive production of mitochondrial reactive oxygen species,is a key factor that impedes neural regeneration in neurodegenerative diseases and after neuronal injury(Han et al.,2016,2020;Zheng et al.,2016;Zong et al.,2024).

Global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary order.The HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered class.The total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,respectively.The proposed model is tested separately for unique solutions and existence on bi intervals.The numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons Polynomial.The proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler Law.The cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said disease.This study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered 1000.The obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

Is it possible to foot reflexology for infants with sensorineural hearing loss?

Foot reflexology is a non-invasive and safe complementary therapy that works by massaging the reflex zones of the feet and exerts systemic or whole-body regulation through meridian nerve conduction.This therapy is commonly used in the treatment of various conditions such as autism and Parkinson's disease.However,there is limited reporting on the use of foot reflexology therapy for infants with sensorineural hearing loss(SNHL).Currently,there is no definitive conclusion on how foot reflexology therapy can influence hearing.This editorial holds some guiding significance regarding this clinical issue.The aim is to present physiological evidence of how foot reflexology therapy can impact infants with SNHL,thereby enhancing clinician’s awareness of foot reflexology in treating infants with SNHL.

Induced neural stem cells regulate microglial activation through Akt-mediated upregulation of CXCR4 and Crry in a mouse model of closed head injury

Microglial activation that occurs rapidly after closed head injury may play important and complex roles in neuroinflammation-associated neuronal damage and repair.We previously reported that induced neural stem cells can modulate the behavior of activated microglia via CXCL12/CXCR4 signaling,influencing their activation such that they can promote neurological recovery.However,the mechanism of CXCR4 upregulation in induced neural stem cells remains unclear.In this study,we found that nuclear factor-κB activation induced by closed head injury mouse serum in microglia promoted CXCL12 and tumor necrosis factor-αexpression but suppressed insulin-like growth factor-1 expression.However,recombinant complement receptor 2-conjugated Crry(CR2-Crry)reduced the effects of closed head injury mouse serum-induced nuclear factor-κB activation in microglia and the levels of activated microglia,CXCL12,and tumor necrosis factor-α.Additionally,we observed that,in response to stimulation(including stimulation by CXCL12 secreted by activated microglia),CXCR4 and Crry levels can be upregulated in induced neural stem cells via the interplay among CXCL12/CXCR4,Crry,and Akt signaling to modulate microglial activation.In agreement with these in vitro experimental results,we found that Akt activation enhanced the immunoregulatory effects of induced neural stem cell grafts on microglial activation,leading to the promotion of neurological recovery via insulin-like growth factor-1 secretion and the neuroprotective effects of induced neural stem cell grafts through CXCR4 and Crry upregulation in the injured cortices of closed head injury mice.Notably,these beneficial effects of Akt activation in induced neural stem cells were positively correlated with the therapeutic effects of induced neural stem cells on neuronal injury,cerebral edema,and neurological disorders post–closed head injury.In conclusion,our findings reveal that Akt activation may enhance the immunoregulatory effects of induced neural stem cells on microglial activation via upregulation of CXCR4 and Crry,thereby promoting induced neural stem cell–mediated improvement of neuronal injury,cerebral edema,and neurological disorders following closed head injury.

Learning the parameters of a class of stochastic Lotka-Volterra systems with neural networks

In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.

Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.

Repetitive transcranial magnetic stimulation in Alzheimer’s disease:effects on neural and synaptic rehabilitation

Alzheimer’s disease is a neurodegenerative disease resulting from deficits in synaptic transmission and homeostasis.The Alzheimer’s disease brain tends to be hyperexcitable and hypersynchronized,thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life,leaving patients incapacitated.Repetitive transcranial magnetic stimulation is a cost-effective,neuro-modulatory technique used for multiple neurological conditions.Over the past two decades,it has been widely used to predict cognitive decline;identify pathophysiological markers;promote neuroplasticity;and assess brain excitability,plasticity,and connectivity.It has also been applied to patients with dementia,because it can yield facilitatory effects on cognition and promote brain recovery after a neurological insult.However,its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of studies.This study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment,evaluate its effects on synaptic plasticity,and identify the associated mechanisms.This review essentially focuses on changes in the pathology,amyloidogenesis,and clearance pathways,given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer’s disease.Apoptotic mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription,which are closely related to the neural regeneration process,are also highlighted.Finally,we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation,with the aim to highlight future directions for better clinical translations.

Small extracellular vesicles derived from human induced pluripotent stem cell-differentiated neural progenitor cells mitigate retinal ganglion cell degeneration in a mouse model of optic nerve injury

Several studies have found that transplantation of neural progenitor cells(NPCs)promotes the survival of injured neurons.However,a poor integration rate and high risk of tumorigenicity after cell transplantation limits their clinical application.Small extracellular vesicles(sEVs)contain bioactive molecules for neuronal protection and regeneration.Previous studies have shown that stem/progenitor cell-derived sEVs can promote neuronal survival and recovery of neurological function in neurodegenerative eye diseases and other eye diseases.In this study,we intravitreally transplanted sEVs derived from human induced pluripotent stem cells(hiPSCs)and hiPSCs-differentiated NPCs(hiPSC-NPC)in a mouse model of optic nerve crush.Our results show that these intravitreally injected sEVs were ingested by retinal cells,especially those localized in the ganglion cell layer.Treatment with hiPSC-NPC-derived sEVs mitigated optic nerve crush-induced retinal ganglion cell degeneration,and regulated the retinal microenvironment by inhibiting excessive activation of microglia.Component analysis further revealed that hiPSC-NPC derived sEVs transported neuroprotective and anti-inflammatory miRNA cargos to target cells,which had protective effects on RGCs after optic nerve injury.These findings suggest that sEVs derived from hiPSC-NPC are a promising cell-free therapeutic strategy for optic neuropathy.

Human-induced pluripotent stem cell-derived neural stem cell exosomes improve blood-brain barrier function after intracerebral hemorrhage by activating astrocytes via PI3K/AKT/MCP-1 axis

Cerebral edema caused by blood-brain barrier injury after intracerebral hemorrhage is an important factor leading to poor prognosis.Human-induced pluripotent stem cell-derived neural stem cell exosomes(hiPSC-NSC-Exos)have shown potential for brain injury repair in central nervous system diseases.In this study,we explored the impact of hiPSC-NSC-Exos on blood-brain barrier preservation and the underlying mechanism.Our results indicated that intranasal delivery of hiPSC-NSC-Exos mitigated neurological deficits,enhanced blood-brain barrier integrity,and reduced leukocyte infiltration in a mouse model of intracerebral hemorrhage.Additionally,hiPSC-NSC-Exos decreased immune cell infiltration,activated astrocytes,and decreased the secretion of inflammatory cytokines like monocyte chemoattractant protein-1,macrophage inflammatory protein-1α,and tumor necrosis factor-αpost-intracerebral hemorrhage,thereby improving the inflammatory microenvironment.RNA sequencing indicated that hiPSC-NSC-Exo activated the PI3K/AKT signaling pathway in astrocytes and decreased monocyte chemoattractant protein-1 secretion,thereby improving blood-brain barrier integrity.Treatment with the PI3K/AKT inhibitor LY294002 or the monocyte chemoattractant protein-1 neutralizing agent C1142 abolished these effects.In summary,our findings suggest that hiPSC-NSC-Exos maintains blood-brain barrier integrity,in part by downregulating monocyte chemoattractant protein-1 secretion through activation of the PI3K/AKT signaling pathway in astrocytes.

Maintaining moderate levels of hypochlorous acid promotes neural stem cell proliferation and differentiation in the recovery phase of stroke

It has been shown clinically that continuous removal of ischemia/reperfusion-induced reactive oxygen species is not conducive to the recovery of late stroke.Indeed,previous studies have shown that excessive increases in hypochlorous acid after stroke can cause severe damage to brain tissue.Our previous studies have found that a small amount of hypochlorous acid still exists in the later stage of stroke,but its specific role and mechanism are currently unclear.To simulate stroke in vivo,a middle cerebral artery occlusion rat model was established,with an oxygen-glucose deprivation/reoxygenation model established in vitro to mimic stroke.We found that in the early stage(within 24 hours)of ischemic stroke,neutrophils produced a large amount of hypochlorous acid,while in the recovery phase(10 days after stroke),microglia were activated and produced a small amount of hypochlorous acid.Further,in acute stroke in rats,hypochlorous acid production was prevented using a hypochlorous acid scavenger,taurine,or myeloperoxidase inhibitor,4-aminobenzoic acid hydrazide.Our results showed that high levels of hypochlorous acid(200μM)induced neuronal apoptosis after oxygen/glucose deprivation/reoxygenation.However,in the recovery phase of the middle cerebral artery occlusion model,a moderate level of hypochlorous acid promoted the proliferation and differentiation of neural stem cells into neurons and astrocytes.This suggests that hypochlorous acid plays different roles at different phases of cerebral ischemia/reperfusion injury.Lower levels of hypochlorous acid(5 and 100μM)promoted nuclear translocation ofβ-catenin.By transfection of single-site mutation plasmids,we found that hypochlorous acid induced chlorination of theβ-catenin tyrosine 30 residue,which promoted nuclear translocation.Altogether,our study indicates that maintaining low levels of hypochlorous acid plays a key role in the recovery of neurological function.

Exosomes originating from neural stem cells undergoing necroptosis participate in cellular communication by inducing TSC2 upregulation of recipient cells following spinal cord injury

We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function,their precise function in spinal cord injury remains unclear.To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury,we conducted singlecell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury.Subsequently,we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes.The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes.Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs,104 long non-coding RNAs,720 circular RNAs,and 14 microRNAs compared with the control group.Construction of a competing endogenous RNA network identified the following hub genes:tuberous sclerosis 2(Tsc2),solute carrier family 16 member 3(Slc16a3),and forkhead box protein P1(Foxp1).Notably,a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury.TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone.Furthermore,in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells.Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways.In addition,Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways.Collectively,these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.

Interference Cancellation Based Neural Receiver for Superimposed Pilot in Multi-Layer Transmission

In this paper,an interference cancellation based neural receiver for superimposed pilot(SIP)in multi-layer transmission is proposed,where the data and pilot are non-orthogonally superimposed in the same time-frequency resource.Specifically,to deal with the intra-layer and inter-layer interference of SIP under multi-layer transmission,the interference cancellation with superimposed symbol aided channel estimation is leveraged in the neural receiver,accompanied by the pre-design of pilot code-division orthogonal mechanism at transmitter.In addition,to address the complexity issue for inter-vendor collaboration and the generalization problem in practical deployments,respectively,this paper also provides a fixed SIP(F-SIP)design based on constant pilot power ratio and scalable mechanisms for different modulation and coding schemes(MCSs)and transmission layers.Simulation results demonstrate the superiority of the proposed schemes on the performance of block error rate and throughput compared with existing counterparts.

Convolutional Graph Neural Network with Novel Loss Strategies for Daily Temperature and Precipitation Statistical Downscaling over South China

Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.

Predicting outcomes using neural networks in the intensive care unit

Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich data for prognostication and clinical care.They can handle complex nonlinear relation-ships in medical data and have advantages over traditional predictive methods.A number of models are used:(1)Feedforward networks;and(2)Recurrent NN and convolutional NN to predict key outcomes such as mortality,length of stay in the ICU and the likelihood of complications.Current NN models exist in silos;their integration into clinical workflow requires greater transparency on data that are analyzed.Most models that are accurate enough for use in clinical care operate as‘black-boxes’in which the logic behind their decision making is opaque.Advan-ces have occurred to see through the opacity and peer into the processing of the black-box.In the near future ML is positioned to help in clinical decision making far beyond what is currently possible.Transparency is the first step toward vali-dation which is followed by clinical trust and adoption.In summary,NNs have the transformative ability to enhance predictive accuracy and improve patient management in ICUs.The concept should soon be turning into reality.

Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model

Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.

Human neural stem cell-derived extracellular vesicles protect against ischemic stroke by activating the PI3K/AKT/mTOR pathway

Human neural stem cell-derived extracellular vesicles exhibit analogous functions to their parental cells,and can thus be used as substitutes for stem cells in stem cell therapy,thereby mitigating the risks of stem cell therapy and advancing the frontiers of stem cell-derived treatments.This lays a foundation for the development of potentially potent new treatment modalities for ischemic stroke.However,the precise mechanisms underlying the efficacy and safety of human neural stem cell-derived extracellular vesicles remain unclear,presenting challenges for clinical translation.To promote the translation of therapy based on human neural stem cell-derived extracellular vesicles from the bench to the bedside,we conducted a comprehensive preclinical study to evaluate the efficacy and safety of human neural stem cell-derived extracellular vesicles in the treatment of ischemic stroke.We found that administration of human neural stem cell-derived extracellular vesicles to an ischemic stroke rat model reduced the volume of cerebral infarction and promoted functional recovery by alleviating neuronal apoptosis.The human neural stem cell-derived extracellular vesicles reduced neuronal apoptosis by enhancing phosphorylation of phosphoinositide 3-kinase,mammalian target of rapamycin,and protein kinase B,and these effects were reversed by treatment with a phosphoinositide 3-kinase inhibitor.These findings suggest that human neural stem cell-derived extracellular vesicles play a neuroprotective role in ischemic stroke through activation of phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin signaling pathway.Finally,we showed that human neural stem cell-derived extracellular vesicles have a good in vivo safety profile.Therefore,human neural stem cell-derived extracellular vesicles are a promising potential agent for the treatment of ischemic stroke.