Brain tumors present significant challenges in medical diagnosis and treatment,where early detection is crucial for reducing morbidity and mortality rates.This research introduces a novel deep learning model,the Progr...Brain tumors present significant challenges in medical diagnosis and treatment,where early detection is crucial for reducing morbidity and mortality rates.This research introduces a novel deep learning model,the Progressive Layered U-Net(PLU-Net),designed to improve brain tumor segmentation accuracy from Magnetic Resonance Imaging(MRI)scans.The PLU-Net extends the standard U-Net architecture by incorporating progressive layering,attention mechanisms,and multi-scale data augmentation.The progressive layering involves a cascaded structure that refines segmentation masks across multiple stages,allowing the model to capture features at different scales and resolutions.Attention gates within the convolutional layers selectively focus on relevant features while suppressing irrelevant ones,enhancing the model's ability to delineate tumor boundaries.Additionally,multi-scale data augmentation techniques increase the diversity of training data and boost the model's generalization capabilities.Evaluated on the BraTS 2021 dataset,the PLU-Net achieved state-of-the-art performance with a dice coefficient of 0.91,specificity of 0.92,sensitivity of 0.89,Hausdorff95 of 2.5,outperforming other modified U-Net architectures in segmentation accuracy.These results underscore the effectiveness of the PLU-Net in improving brain tumor segmentation from MRI scans,supporting clinicians in early diagnosis,treatment planning,and the development of new therapies.展开更多
Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response pla...Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response plays a crucial role in worsening brain injury.Neuroinflammation,a key player in the pathophysiology of stroke,has a dual role.In the acute phase of stroke,neuroinflammation exacerbates brain injury,contributing to neuronal damage and blood–brain barrier disruption.This aspect of neuroinflammation is associated with poor neurological outcomes.Conversely,in the recovery phase following stroke,neuroinflammation facilitates brain repair processes,including neurogenesis,angiogenesis,and synaptic plasticity.The transition of neuroinflammation from a harmful to a reparative role is not well understood.Therefore,this review seeks to explore the mechanisms underlying this transition,with the goal of informing the development of therapeutic interventions that are both time-and context-specific.This review aims to elucidate the complex and dual role of neuroinflammation in stroke,highlighting the main actors,biomarkers of the disease,and potential therapeutic approaches.展开更多
Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire b...Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire brain[1-4].Current commonly used approaches for such mesoscale brain mapping include two main types of three-dimensional fluorescence microscopy:the block-face methods,and the lightsheet-based methods[5,6].In general,the high imaging speed and light efficiency of light-sheet microscopy make it a suitable tool for high-throughput volumetric imaging,especially when combined with tissue-clearing techniques.However,large brain samples pose major challenges to this approach.展开更多
Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microgl...Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microglia play an important role in secondary injury and can be activated in response to traumatic brain injury.In this article,we review the origin and classification of microglia as well as the dynamic changes of microglia in traumatic brain injury.We also clarify the microglial polarization pathways and the therapeutic drugs targeting activated microglia.We found that regulating the signaling pathways involved in pro-inflammatory and anti-inflammatory microglia,such as the Toll-like receptor 4/nuclear factor-kappa B,mitogen-activated protein kinase,Janus kinase/signal transducer and activator of transcription,phosphoinositide 3-kinase/protein kinase B,Notch,and high mobility group box 1 pathways,can alleviate the inflammatory response triggered by microglia in traumatic brain injury,thereby exerting neuroprotective effects.We also reviewed the strategies developed on the basis of these pathways,such as drug and cell replacement therapies.Drugs that modulate inflammatory factors,such as rosuvastatin,have been shown to promote the polarization of antiinflammatory microglia and reduce the inflammatory response caused by traumatic brain injury.Mesenchymal stem cells possess anti-inflammatory properties,and clinical studies have confirmed their significant efficacy and safety in patients with traumatic brain injury.Additionally,advancements in mesenchymal stem cell-delivery methods—such as combinations of novel biomaterials,genetic engineering,and mesenchymal stem cell exosome therapy—have greatly enhanced the efficiency and therapeutic effects of mesenchymal stem cells in animal models.However,numerous challenges in the application of drug and mesenchymal stem cell treatment strategies remain to be addressed.In the future,new technologies,such as single-cell RNA sequencing and transcriptome analysis,can facilitate further experimental studies.Moreover,research involving non-human primates can help translate these treatment strategies to clinical practice.展开更多
It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the ...It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.展开更多
Intracerebral hemorrhage is the most dangerous subtype of stroke,characterized by high mortality and morbidity rates,and frequently leads to significant secondary white matter injury.In recent decades,studies have rev...Intracerebral hemorrhage is the most dangerous subtype of stroke,characterized by high mortality and morbidity rates,and frequently leads to significant secondary white matter injury.In recent decades,studies have revealed that gut microbiota can communicate bidirectionally with the brain through the gut microbiota–brain axis.This axis indicates that gut microbiota is closely related to the development and prognosis of intracerebral hemorrhage and its associated secondary white matter injury.The NACHT,LRR,and pyrin domain-containing protein 3(NLRP3)inflammasome plays a crucial role in this context.This review summarizes the dysbiosis of gut microbiota following intracerebral hemorrhage and explores the mechanisms by which this imbalance may promote the activation of the NLRP3 inflammasome.These mechanisms include metabolic pathways(involving short-chain fatty acids,lipopolysaccharides,lactic acid,bile acids,trimethylamine-N-oxide,and tryptophan),neural pathways(such as the vagus nerve and sympathetic nerve),and immune pathways(involving microglia and T cells).We then discuss the relationship between the activated NLRP3 inflammasome and secondary white matter injury after intracerebral hemorrhage.The activation of the NLRP3 inflammasome can exacerbate secondary white matter injury by disrupting the blood–brain barrier,inducing neuroinflammation,and interfering with nerve regeneration.Finally,we outline potential treatment strategies for intracerebral hemorrhage and its secondary white matter injury.Our review highlights the critical role of the gut microbiota–brain axis and the NLRP3 inflammasome in white matter injury following intracerebral hemorrhage,paving the way for exploring potential therapeutic approaches.展开更多
Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility...Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility of estimating brain volume through retinal fundus imaging integrated with clinical metadata,and to offer a cost-effective approach for assessing brain health.Methods:Based on clinical information,retinal fundus images,and neuroimaging data derived from a multicenter,population-based cohort study,the Kai Luan Study,we proposed a cross-modal correlation representation(CMCR)network to elucidate the intricate co-degenerative relationships between the eyes and brain for 755 subjects.Specifically,individual clinical information,which has been followed up for as long as 12 years,was encoded as a prompt to enhance the accuracy of brain volume estimation.Independent internal validation and external validation were performed to assess the robustness of the proposed model.Root mean square error(RMSE),peak signal-tonoise ratio(PSNR),and structural similarity index measure(SSIM)metrics were employed to quantitatively evaluate the quality of synthetic brain images derived from retinal imaging data.Results:The proposed framework yielded average RMSE,PSNR,and SSIM values of 98.23,35.78 d B,and 0.64,respectively,which significantly outperformed 5 other methods:multi-channel Variational Autoencoder(mcVAE),Pixelto-Pixel(Pixel2pixel),transformer-based U-Net(Trans UNet),multi-scale transformer network(MT-Net),and residual vision transformer(ResViT).The two-(2D)and three-dimensional(3D)visualization results showed that the shape and texture of the synthetic brain images generated by the proposed method most closely resembled those of actual brain images.Thus,the CMCR framework accurately captured the latent structural correlations between the fundus and the brain.The average difference between predicted and actual brain volumes was 61.36 cm~3,with a relative error of 4.54%.When all of the clinical information(including age and sex,daily habits,cardiovascular factors,metabolic factors,and inflammatory factors)was encoded,the difference was decreased to 53.89 cm~3,with a relative error of 3.98%.Based on the synthesized brain magnetic resonance images from retinal fundus images,the volumes of brain tissues could be estimated with high accuracy.Conclusion:This study provides an innovative,accurate,and cost-effective approach to characterize brain health status through readily accessible retinal fundus images.展开更多
Obese individuals who subsequently sustain a traumatic brain injury(TBI)exhibit worsened outcomes including longer periods of rehabilitation(Eagle et al.,2023).In obese individuals,prolonged symptomology is associated...Obese individuals who subsequently sustain a traumatic brain injury(TBI)exhibit worsened outcomes including longer periods of rehabilitation(Eagle et al.,2023).In obese individuals,prolonged symptomology is associated with increased levels of circulato ry pro-inflammatory marke rs up to 1 year postTBI(Eagle et al.,2023).展开更多
Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and ev...Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and evaluation systems for arbitrators in China have long faced challenges such as the vague criteria for competency and an unclear professionalization path for arbitrators. To address these issues, this study is grounded in the context of actual Chinese arbitration practice and based on the competency iceberg model. Through a methodological approach encompassing literature reviews, behavioral event interviews, expert revisions, and questionnaire surveys, a Chinese Arbitrator Competency Scale was developed and validated in this study. Examination of the findings indicated that the scale needed to consist of five dimensions—communication and coordination, cognitive skills, ethical conduct, work motivation, and personality traits—and possess a total of 28 specific indicators. Confirmatory analysis of the factors demonstrates a good fit for the five-dimensional model, with each of the dimensions exhibiting high reliability and validity. This scale is innovative in integrating the competency elements with Chinese characteristics, such as commercial acumen, crosscultural mediation skills, and adaptability to the local rule of law. This research not only enriches the competency theory in regard to the field of human resource management but also provides a scientific framework of standards and measurement tools for the selection, training, and evaluation of arbitrators. It thus has significant practical value for enhancing the professionalism and international competitiveness of China's arbitration system.展开更多
Blood-brain barrier disruption and the neuroinflammatory response are significant pathological features that critically influence disease progression and treatment outcomes.This review systematically analyzes the curr...Blood-brain barrier disruption and the neuroinflammatory response are significant pathological features that critically influence disease progression and treatment outcomes.This review systematically analyzes the current understanding of the bidirectional relationship between blood-brain barrier disruption and neuroinflammation in traumatic brain injury,along with emerging combination therapeutic strategies.Literature review indicates that blood-brain barrier disruption and neuroinflammatory responses are key pathological features following traumatic brain injury.In the acute phase after traumatic brain injury,the pathological characteristics include primary blood-brain barrier disruption and the activation of inflammatory cascades.In the subacute phase,the pathological features are characterized by repair mechanisms and inflammatory modulation.In the chronic phase,the pathological features show persistent low-grade inflammation and incomplete recovery of the blood-brain barrier.Various physiological changes,such as structural alterations of the blood-brain barrier,inflammatory cascades,and extracellular matrix remodeling,interact with each other and are influenced by genetic,age,sex,and environmental factors.The dynamic balance between blood-brain barrier permeability and neuroinflammation is regulated by hormones,particularly sex hormones and stress-related hormones.Additionally,the role of gastrointestinal hormones is receiving increasing attention.Current treatment strategies for traumatic brain injury include various methods such as conventional drug combinations,multimodality neuromonitoring,hyperbaric oxygen therapy,and non-invasive brain stimulation.Artificial intelligence also shows potential in treatment decision-making and personalized therapy.Emerging sequential combination strategies and precision medicine approaches can help improve treatment outcomes;however,challenges remain,such as inadequate research on the mechanisms of the chronic phase traumatic brain injury and difficulties with technology integration.Future research on traumatic brain injury should focus on personalized treatment strategies,the standardization of techniques,costeffectiveness evaluations,and addressing the needs of patients with comorbidities.A multidisciplinary approach should be used to enhance treatment and improve patient outcomes.展开更多
This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 20...This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.展开更多
Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of kn...Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.展开更多
Background:Midlife lifestyle factors,including physical activity,are associated with late-life brain health,yet the role of aerobic exercise on structural brain health in early and mid-adulthood remains poorly underst...Background:Midlife lifestyle factors,including physical activity,are associated with late-life brain health,yet the role of aerobic exercise on structural brain health in early and mid-adulthood remains poorly understood.This study aimed to examine the effect of aerobic exercise on structural brain age and to explore potential mediators.Methods:In a single-blind,12-month randomized clinical trial,130 healthy participants aged 26-58 years were randomized into a moderate-to-vigorous intensity aerobic exercise group or a usual-care control group.The exercise group attended two supervised 60-min sessions per week in a laboratory setting plus engaged in home-based exercise to achieve 150 min of exercise per week.Brain-predicted age difference(brain-PAD)and cardiorespiratory fitness(CRF)were assessed at baseline and 12 months.Both intention-to-treat(ITT)and completers analyses(including participants who completed post-intervention assessments)were performed.Results:The 130 participants(67.7%female)had an age of 41.28±9.93 years(mean±SD).At baseline,higher CRF(peak oxygen uptake,VO_(2peak))was associated with smaller brain-PAD(β=-0.309,p=0.012).After the intervention,the exercise group showed a decrease in brainPAD(estimated mean difference(EMD)=-0.60;95%confidence interval(95%CI):-1.15 to-0.04;p=0.034)compared to the control group(EMD=0.35;95%CI:-0.21 to 0.92;p=0.217);time×group interaction(between-group difference(BGD)=-0.95;95%CI:-1.72 to-0.17;p=0.019).VO2peak improved in the exercise group(EMD=1.60;95%CI:0.29-2.90;p=0.017)compared to the control group(EMD=-0.78;95%CI:-2.17 to 0.60;p=0.265);time×group interaction(BGD=2.38;95%CI:0.52-4.25;p=0.015).Body composition,blood pressure,and brain-derived neurotrophic factor levels were unaffected.None of the proposed pathways statistically mediated the effect of exercise on brain-PAD.The results from completers were similar.Conclusion:Engaging in 12 months of moderate-to-vigorous exercise reduced brain-PAD in early-to-midlife adults.The pathways by which these effects occur remain unknown.展开更多
Pericytes are multi-functional mural cells of the central nervous system that cover the capillary endothelial cells. Pericytes play a vital role in nervous system development, significantly influencing the formation, ...Pericytes are multi-functional mural cells of the central nervous system that cover the capillary endothelial cells. Pericytes play a vital role in nervous system development, significantly influencing the formation, maturation, and maintenance of the central nervous system. An expanding body of studies has revealed that pericytes establish carefully regulated interactions with oligodendrocytes, microglia, and astrocytes. These communications govern numerous critical brain processes, including angiogenesis, neurovascular unit homeostasis, blood–brain barrier integrity, cerebral blood flow regulation, and immune response initiation. Glial cells and pericytes participate in dynamic and reciprocal interactions, with each influencing and adjusting the functionality of the other. Pericytes have the ability to control astrocyte polarization, trigger differentiation of oligodendrocyte precursor cells, and initiate immunological responses in microglia. Various neurological disorders that compromise the integrity of the blood–brain barrier can disrupt these communications, impair waste clearance, and hinder cerebral blood circulation, contributing to neuroinflammation. In the context of neurodegeneration, these disruptions exacerbate pathological processes, such as neuronal damage, synaptic dysfunction, and impaired tissue repair. This article explores the complex interactions between pericytes and various glial cells in both healthy and pathological states of the central nervous system. It highlights their essential roles in neurovascular function and disease progression, providing important insights that may enhance our understanding of the molecular mechanisms underlying these interactions and guide potential therapeutic strategies for neurodegenerative disorders in future research.展开更多
BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly unders...BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly understood.AIM To examine regional abnormalities in spontaneous brain activity among patients with MDD-OB comorbidity.METHODS This study adopted a regional homogeneity(ReHo)analysis of resting-state functional magnetic resonance imaging.The study included 149 hospital patients divided into four groups:Patients experiencing their first episode of drug-naive MDD with OB,patients with MDD without OB,and age-and sex-matched healthy individuals with and without OB.Whole-brain ReHo analysis was conducted using SPM12 software and RESTplus toolkits,with group comparisons via ANOVA and post-hoc tests.Correlations between ReHo values and behavioral measures were examined.RESULTS ANOVA revealed significant whole-brain ReHo differences among the four groups in four key regions:The left middle temporal gyrus(MTG.L),right cuneus,left precuneus,and left thalamus.Post-hoc analyses confirmed pairwise differences between all groups across these regions(P<0.05).OB was associated with ReHo alterations in the MTG.L,right cuneus,and left thalamus,whereas abnormalities in the precuneus suggested synergistic pathological mechanisms between MDD and OB.Statistically significant correlations were found between the drive and fun-seeking dimensions of the behavioral activation system,as well as behavioral inhibition and the corresponding ReHo values.CONCLUSION Our findings provide novel evidence for the neuroadaptive mechanisms underlying the MDD-OB comorbidity.Further validation could lead to personalized interventions targeting MTG.L hyperactivity and targeting healthy food cues.展开更多
Background:Early detection of harmful brain activity in critically ill patients using electroencephalography(EEG)is vital for timely and effective clinical intervention.Automating EEG analysis with deep learning techn...Background:Early detection of harmful brain activity in critically ill patients using electroencephalography(EEG)is vital for timely and effective clinical intervention.Automating EEG analysis with deep learning techniques holds significant promise for enhancing diagnostic efficiency and accuracy.Methods:We implemented EfficientNetB2,which leverages convolutional neural networks with a novel Temporal Squeeze-and-Excitation module to capture temporal EEG features,and WaveNet,a sequential model designed to effectively model temporal dependencies in EEG data using dilated causal convolutions and temporal self-attention.Both models were trained and evaluated using a publicly available EEG dataset,with performance assessed via 4-fold cross-validation and a step-wise learning rate reduction strategy.Results:Our results demonstrate a significant reduction in training loss from 0.6459 to 0.3055 and validation loss from 0.9602 to 0.5719 over six epochs.Consistent improvements were observed across cross-validation folds,highlighting the robustness of the models.Additionally,ensemble learning of the two architectures further enhanced classification performance.Conclusion:This comparative analysis sheds light on the strengths and limitations of EfficientNetB2 and WaveNet for automated harmful brain activity detection in EEG signals.The findings contribute to the advancement of reliable and efficient deep learning models,paving the way for their clinical application in managing critically ill patients.展开更多
Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable ene...Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.展开更多
The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic...The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic activity across the entire brain and its numerous micro-regions remains incredibly challenging.Here,we offer a high-definition spatially resolved metabolomics technique to better understand the metabolic specialization and interconnection throughout the mouse brain using improved ambient mass spectrometry imaging.This method allows for the simultaneous mapping of thousands of metabolites at a 30 μm spatial resolution across the mouse brain,ranging from structural lipids to functional neurotransmitters.This approach effectively reveals the distribution patterns of delicate microregions and their distinctive metabolic characteristics.Using an integrated database,we annotated 259 metabolites,demonstrating that the metabolome and metabolic pathways are unique to each brain microregion.The distribution of metabolites,closely linked to functionally connected brain regions and their interactions,offers profound insights into the complexity of chemical processes and their roles in brain function.An initial dataset for future metabolomics research might be obtained from the high-definition mouse brain's spatial metabolome atlas.展开更多
In recent years,development of strategies to treat central nervous system(CNS) diseases has attracted extensive attention.A major obstacle in this field is the blood-brain barrier(BBB),which significantly limits the e...In recent years,development of strategies to treat central nervous system(CNS) diseases has attracted extensive attention.A major obstacle in this field is the blood-brain barrier(BBB),which significantly limits the efficient delivery of therapeutic agents to the brain and hinders the treatment of CNS diseases.Overcoming the restrictive nature of the BBB has thus emerged as a key objective in CNS drug development.Nanomaterials have garnered growing interest due to their unique physicochemical properties and potential to traverse the BBB,enabling targeted drug delivery to brain tissue and improving therapeutic efficacy.In this review,we present current insights into the structure and function of the BBB and highlight a range of nanomaterial-based strategies for BBB penetration,including receptor-mediated transport(RMT),adsorptive-mediated transcytosis,reversible BBB disruption,and intranasal administration.Finally,we summarize recent advances in enhancing BBB permeability for CNS therapeutics and discuss persisting challenges,offering perspectives for future research in this field.展开更多
The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.H...The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.However,recent findings revealed that some forms of neural plasticity can show a reverse trend.Although plasticity is a well-preserved,transversal feature across the animal world,a variety of cell populations and mechanisms seem to have evolved to enable structural modifications to take place in widely different brains,likely as adaptations to selective pressures.Increasing evidence now indicates that a trade-off has occurred between regenerative(mostly stem cell–driven)plasticity and developmental(mostly juvenile)remodeling,with the latter primarily aimed not at brain repair but rather at“sculpting”the neural circuits based on experience.In particular,an evolutionary trade-off has occurred between neurogenic processes intended to support the possibility of recruiting new neurons throughout life and the different ways of obtaining new neurons,and between the different brain locations in which plasticity occurs.This review first briefly surveys the different types of plasticity and the complexity of their possible outcomes and then focuses on recent findings showing that the mammalian brain has a stem cell–independent integration of new neurons into pre-existing(mature)neural circuits.This process is still largely unknown but involves neuronal cells that have been blocked in arrested maturation since their embryonic origin(also termed“immature”or“dormant”neurons).These cells can then restart maturation throughout the animal's lifespan to become functional neurons in brain regions,such as the cerebral cortex and amygdala,that are relevant to high-order cognition and emotions.Unlike stem cell–driven postnatal/adult neurogenesis,which significantly decreases from small-brained,short-living species to large-brained ones,immature neurons are particularly abundant in large-brained,long-living mammals,including humans.The immature neural cell populations hosted in these complex brains are an interesting example of an“enlarged road”in the phylogenetic trend of plastic potential decreases commonly observed in the animal world.The topic of dormant neurons that covary with brain size and gyrencephaly represents a prospective turning point in the field of neuroplasticity,with important translational outcomes.These cells can represent a reservoir of undifferentiated neurons,potentially granting plasticity within the high-order circuits subserving the most sophisticated cognitive skills that are important in the growing brains of young,healthy individuals and are frequently affected by debilitating neurodevelopmental and degenerative disorders.展开更多
文摘Brain tumors present significant challenges in medical diagnosis and treatment,where early detection is crucial for reducing morbidity and mortality rates.This research introduces a novel deep learning model,the Progressive Layered U-Net(PLU-Net),designed to improve brain tumor segmentation accuracy from Magnetic Resonance Imaging(MRI)scans.The PLU-Net extends the standard U-Net architecture by incorporating progressive layering,attention mechanisms,and multi-scale data augmentation.The progressive layering involves a cascaded structure that refines segmentation masks across multiple stages,allowing the model to capture features at different scales and resolutions.Attention gates within the convolutional layers selectively focus on relevant features while suppressing irrelevant ones,enhancing the model's ability to delineate tumor boundaries.Additionally,multi-scale data augmentation techniques increase the diversity of training data and boost the model's generalization capabilities.Evaluated on the BraTS 2021 dataset,the PLU-Net achieved state-of-the-art performance with a dice coefficient of 0.91,specificity of 0.92,sensitivity of 0.89,Hausdorff95 of 2.5,outperforming other modified U-Net architectures in segmentation accuracy.These results underscore the effectiveness of the PLU-Net in improving brain tumor segmentation from MRI scans,supporting clinicians in early diagnosis,treatment planning,and the development of new therapies.
基金supported by European Union-NextGeneration EU under the Italian University and Research(MUR)National Innovation Ecosystem grant ECS00000041-VITALITY-CUP E13C22001060006(to MdA)。
文摘Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response plays a crucial role in worsening brain injury.Neuroinflammation,a key player in the pathophysiology of stroke,has a dual role.In the acute phase of stroke,neuroinflammation exacerbates brain injury,contributing to neuronal damage and blood–brain barrier disruption.This aspect of neuroinflammation is associated with poor neurological outcomes.Conversely,in the recovery phase following stroke,neuroinflammation facilitates brain repair processes,including neurogenesis,angiogenesis,and synaptic plasticity.The transition of neuroinflammation from a harmful to a reparative role is not well understood.Therefore,this review seeks to explore the mechanisms underlying this transition,with the goal of informing the development of therapeutic interventions that are both time-and context-specific.This review aims to elucidate the complex and dual role of neuroinflammation in stroke,highlighting the main actors,biomarkers of the disease,and potential therapeutic approaches.
基金supported by the STI 2030-Major Project(2021ZD0204400,2022ZD0205203,2021ZD0200104,2022ZD0211900)the Shenzhen Science and Technology Program(RCYX20210706092100003,RCBS20221008093311027)+3 种基金the Shenzhen Medical Research Funds(A2303005)the Youth Innovation Promotion Association CAS(2022367)the National Natural Science Foundation of China(32100896)NSFC-Guangdong Joint Fund(U20A6005).
文摘Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire brain[1-4].Current commonly used approaches for such mesoscale brain mapping include two main types of three-dimensional fluorescence microscopy:the block-face methods,and the lightsheet-based methods[5,6].In general,the high imaging speed and light efficiency of light-sheet microscopy make it a suitable tool for high-throughput volumetric imaging,especially when combined with tissue-clearing techniques.However,large brain samples pose major challenges to this approach.
基金supported by the Natural Science Foundation of Yunnan Province,No.202401AS070086(to ZW)the National Key Research and Development Program of China,No.2018YFA0801403(to ZW)+1 种基金Yunnan Science and Technology Talent and Platform Plan,No.202105AC160041(to ZW)the Natural Science Foundation of China,No.31960120(to ZW)。
文摘Traumatic brain injury can be categorized into primary and secondary injuries.Secondary injuries are the main cause of disability following traumatic brain injury,which involves a complex multicellular cascade.Microglia play an important role in secondary injury and can be activated in response to traumatic brain injury.In this article,we review the origin and classification of microglia as well as the dynamic changes of microglia in traumatic brain injury.We also clarify the microglial polarization pathways and the therapeutic drugs targeting activated microglia.We found that regulating the signaling pathways involved in pro-inflammatory and anti-inflammatory microglia,such as the Toll-like receptor 4/nuclear factor-kappa B,mitogen-activated protein kinase,Janus kinase/signal transducer and activator of transcription,phosphoinositide 3-kinase/protein kinase B,Notch,and high mobility group box 1 pathways,can alleviate the inflammatory response triggered by microglia in traumatic brain injury,thereby exerting neuroprotective effects.We also reviewed the strategies developed on the basis of these pathways,such as drug and cell replacement therapies.Drugs that modulate inflammatory factors,such as rosuvastatin,have been shown to promote the polarization of antiinflammatory microglia and reduce the inflammatory response caused by traumatic brain injury.Mesenchymal stem cells possess anti-inflammatory properties,and clinical studies have confirmed their significant efficacy and safety in patients with traumatic brain injury.Additionally,advancements in mesenchymal stem cell-delivery methods—such as combinations of novel biomaterials,genetic engineering,and mesenchymal stem cell exosome therapy—have greatly enhanced the efficiency and therapeutic effects of mesenchymal stem cells in animal models.However,numerous challenges in the application of drug and mesenchymal stem cell treatment strategies remain to be addressed.In the future,new technologies,such as single-cell RNA sequencing and transcriptome analysis,can facilitate further experimental studies.Moreover,research involving non-human primates can help translate these treatment strategies to clinical practice.
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-62 and lzujbky-2024-jdzx06)the National Natural Science Foundation of China(Grant No.12247101)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant Nos.22JR5RA389 and 23JRRA1740)the‘111 Center’Fund(Grant No.B20063).
文摘It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.
基金supported by the Guangdong Basic and Applied Basic Research Foundation,No.2023A1515030045(to HS)Presidential Foundation of Zhujiang Hospital of Southern Medical University,No.yzjj2022ms4(to HS)。
文摘Intracerebral hemorrhage is the most dangerous subtype of stroke,characterized by high mortality and morbidity rates,and frequently leads to significant secondary white matter injury.In recent decades,studies have revealed that gut microbiota can communicate bidirectionally with the brain through the gut microbiota–brain axis.This axis indicates that gut microbiota is closely related to the development and prognosis of intracerebral hemorrhage and its associated secondary white matter injury.The NACHT,LRR,and pyrin domain-containing protein 3(NLRP3)inflammasome plays a crucial role in this context.This review summarizes the dysbiosis of gut microbiota following intracerebral hemorrhage and explores the mechanisms by which this imbalance may promote the activation of the NLRP3 inflammasome.These mechanisms include metabolic pathways(involving short-chain fatty acids,lipopolysaccharides,lactic acid,bile acids,trimethylamine-N-oxide,and tryptophan),neural pathways(such as the vagus nerve and sympathetic nerve),and immune pathways(involving microglia and T cells).We then discuss the relationship between the activated NLRP3 inflammasome and secondary white matter injury after intracerebral hemorrhage.The activation of the NLRP3 inflammasome can exacerbate secondary white matter injury by disrupting the blood–brain barrier,inducing neuroinflammation,and interfering with nerve regeneration.Finally,we outline potential treatment strategies for intracerebral hemorrhage and its secondary white matter injury.Our review highlights the critical role of the gut microbiota–brain axis and the NLRP3 inflammasome in white matter injury following intracerebral hemorrhage,paving the way for exploring potential therapeutic approaches.
基金supported by the National Natural Science Foundation of China(62522119 and 62372358)the Beijing Natural Science Foundation(7242267)+2 种基金the Beijing Scholars Program([2015]160)the Natural Science Basic Research Program of Shaanxi(2023-JC-QN-0719)the Guangdong Basic and Applied Basic Research Foundation(2022A1515110453)。
文摘Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility of estimating brain volume through retinal fundus imaging integrated with clinical metadata,and to offer a cost-effective approach for assessing brain health.Methods:Based on clinical information,retinal fundus images,and neuroimaging data derived from a multicenter,population-based cohort study,the Kai Luan Study,we proposed a cross-modal correlation representation(CMCR)network to elucidate the intricate co-degenerative relationships between the eyes and brain for 755 subjects.Specifically,individual clinical information,which has been followed up for as long as 12 years,was encoded as a prompt to enhance the accuracy of brain volume estimation.Independent internal validation and external validation were performed to assess the robustness of the proposed model.Root mean square error(RMSE),peak signal-tonoise ratio(PSNR),and structural similarity index measure(SSIM)metrics were employed to quantitatively evaluate the quality of synthetic brain images derived from retinal imaging data.Results:The proposed framework yielded average RMSE,PSNR,and SSIM values of 98.23,35.78 d B,and 0.64,respectively,which significantly outperformed 5 other methods:multi-channel Variational Autoencoder(mcVAE),Pixelto-Pixel(Pixel2pixel),transformer-based U-Net(Trans UNet),multi-scale transformer network(MT-Net),and residual vision transformer(ResViT).The two-(2D)and three-dimensional(3D)visualization results showed that the shape and texture of the synthetic brain images generated by the proposed method most closely resembled those of actual brain images.Thus,the CMCR framework accurately captured the latent structural correlations between the fundus and the brain.The average difference between predicted and actual brain volumes was 61.36 cm~3,with a relative error of 4.54%.When all of the clinical information(including age and sex,daily habits,cardiovascular factors,metabolic factors,and inflammatory factors)was encoded,the difference was decreased to 53.89 cm~3,with a relative error of 3.98%.Based on the synthesized brain magnetic resonance images from retinal fundus images,the volumes of brain tissues could be estimated with high accuracy.Conclusion:This study provides an innovative,accurate,and cost-effective approach to characterize brain health status through readily accessible retinal fundus images.
文摘Obese individuals who subsequently sustain a traumatic brain injury(TBI)exhibit worsened outcomes including longer periods of rehabilitation(Eagle et al.,2023).In obese individuals,prolonged symptomology is associated with increased levels of circulato ry pro-inflammatory marke rs up to 1 year postTBI(Eagle et al.,2023).
基金Research on Problems and Countermeasures in Building the Capacity of the Grassroots International Chambers of Commerce in the Context of High-Quality Development (W2024H03841)a key research project of the China Council for the Promotion of International Trade in 2025。
文摘Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and evaluation systems for arbitrators in China have long faced challenges such as the vague criteria for competency and an unclear professionalization path for arbitrators. To address these issues, this study is grounded in the context of actual Chinese arbitration practice and based on the competency iceberg model. Through a methodological approach encompassing literature reviews, behavioral event interviews, expert revisions, and questionnaire surveys, a Chinese Arbitrator Competency Scale was developed and validated in this study. Examination of the findings indicated that the scale needed to consist of five dimensions—communication and coordination, cognitive skills, ethical conduct, work motivation, and personality traits—and possess a total of 28 specific indicators. Confirmatory analysis of the factors demonstrates a good fit for the five-dimensional model, with each of the dimensions exhibiting high reliability and validity. This scale is innovative in integrating the competency elements with Chinese characteristics, such as commercial acumen, crosscultural mediation skills, and adaptability to the local rule of law. This research not only enriches the competency theory in regard to the field of human resource management but also provides a scientific framework of standards and measurement tools for the selection, training, and evaluation of arbitrators. It thus has significant practical value for enhancing the professionalism and international competitiveness of China's arbitration system.
基金supported by Open Scientific Research Program of Military Logistics,No.BLB20J009(to YZhao).
文摘Blood-brain barrier disruption and the neuroinflammatory response are significant pathological features that critically influence disease progression and treatment outcomes.This review systematically analyzes the current understanding of the bidirectional relationship between blood-brain barrier disruption and neuroinflammation in traumatic brain injury,along with emerging combination therapeutic strategies.Literature review indicates that blood-brain barrier disruption and neuroinflammatory responses are key pathological features following traumatic brain injury.In the acute phase after traumatic brain injury,the pathological characteristics include primary blood-brain barrier disruption and the activation of inflammatory cascades.In the subacute phase,the pathological features are characterized by repair mechanisms and inflammatory modulation.In the chronic phase,the pathological features show persistent low-grade inflammation and incomplete recovery of the blood-brain barrier.Various physiological changes,such as structural alterations of the blood-brain barrier,inflammatory cascades,and extracellular matrix remodeling,interact with each other and are influenced by genetic,age,sex,and environmental factors.The dynamic balance between blood-brain barrier permeability and neuroinflammation is regulated by hormones,particularly sex hormones and stress-related hormones.Additionally,the role of gastrointestinal hormones is receiving increasing attention.Current treatment strategies for traumatic brain injury include various methods such as conventional drug combinations,multimodality neuromonitoring,hyperbaric oxygen therapy,and non-invasive brain stimulation.Artificial intelligence also shows potential in treatment decision-making and personalized therapy.Emerging sequential combination strategies and precision medicine approaches can help improve treatment outcomes;however,challenges remain,such as inadequate research on the mechanisms of the chronic phase traumatic brain injury and difficulties with technology integration.Future research on traumatic brain injury should focus on personalized treatment strategies,the standardization of techniques,costeffectiveness evaluations,and addressing the needs of patients with comorbidities.A multidisciplinary approach should be used to enhance treatment and improve patient outcomes.
文摘This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.
基金funded by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation):project ID 431549029-SFB 1451the Marga-und-Walter-Boll-Stiftung(#210-10-15)(to MAR)a stipend from the'Gerok Program'(Faculty of Medicine,University of Cologne,Germany)。
文摘Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.
基金funded by the National Institutes of Health and the National Heart,Lung,and Blood Institute(P01HL040962)。
文摘Background:Midlife lifestyle factors,including physical activity,are associated with late-life brain health,yet the role of aerobic exercise on structural brain health in early and mid-adulthood remains poorly understood.This study aimed to examine the effect of aerobic exercise on structural brain age and to explore potential mediators.Methods:In a single-blind,12-month randomized clinical trial,130 healthy participants aged 26-58 years were randomized into a moderate-to-vigorous intensity aerobic exercise group or a usual-care control group.The exercise group attended two supervised 60-min sessions per week in a laboratory setting plus engaged in home-based exercise to achieve 150 min of exercise per week.Brain-predicted age difference(brain-PAD)and cardiorespiratory fitness(CRF)were assessed at baseline and 12 months.Both intention-to-treat(ITT)and completers analyses(including participants who completed post-intervention assessments)were performed.Results:The 130 participants(67.7%female)had an age of 41.28±9.93 years(mean±SD).At baseline,higher CRF(peak oxygen uptake,VO_(2peak))was associated with smaller brain-PAD(β=-0.309,p=0.012).After the intervention,the exercise group showed a decrease in brainPAD(estimated mean difference(EMD)=-0.60;95%confidence interval(95%CI):-1.15 to-0.04;p=0.034)compared to the control group(EMD=0.35;95%CI:-0.21 to 0.92;p=0.217);time×group interaction(between-group difference(BGD)=-0.95;95%CI:-1.72 to-0.17;p=0.019).VO2peak improved in the exercise group(EMD=1.60;95%CI:0.29-2.90;p=0.017)compared to the control group(EMD=-0.78;95%CI:-2.17 to 0.60;p=0.265);time×group interaction(BGD=2.38;95%CI:0.52-4.25;p=0.015).Body composition,blood pressure,and brain-derived neurotrophic factor levels were unaffected.None of the proposed pathways statistically mediated the effect of exercise on brain-PAD.The results from completers were similar.Conclusion:Engaging in 12 months of moderate-to-vigorous exercise reduced brain-PAD in early-to-midlife adults.The pathways by which these effects occur remain unknown.
文摘Pericytes are multi-functional mural cells of the central nervous system that cover the capillary endothelial cells. Pericytes play a vital role in nervous system development, significantly influencing the formation, maturation, and maintenance of the central nervous system. An expanding body of studies has revealed that pericytes establish carefully regulated interactions with oligodendrocytes, microglia, and astrocytes. These communications govern numerous critical brain processes, including angiogenesis, neurovascular unit homeostasis, blood–brain barrier integrity, cerebral blood flow regulation, and immune response initiation. Glial cells and pericytes participate in dynamic and reciprocal interactions, with each influencing and adjusting the functionality of the other. Pericytes have the ability to control astrocyte polarization, trigger differentiation of oligodendrocyte precursor cells, and initiate immunological responses in microglia. Various neurological disorders that compromise the integrity of the blood–brain barrier can disrupt these communications, impair waste clearance, and hinder cerebral blood circulation, contributing to neuroinflammation. In the context of neurodegeneration, these disruptions exacerbate pathological processes, such as neuronal damage, synaptic dysfunction, and impaired tissue repair. This article explores the complex interactions between pericytes and various glial cells in both healthy and pathological states of the central nervous system. It highlights their essential roles in neurovascular function and disease progression, providing important insights that may enhance our understanding of the molecular mechanisms underlying these interactions and guide potential therapeutic strategies for neurodegenerative disorders in future research.
基金Supported by Provincial Key Research Project of Henan Province,No.232102310081.
文摘BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly understood.AIM To examine regional abnormalities in spontaneous brain activity among patients with MDD-OB comorbidity.METHODS This study adopted a regional homogeneity(ReHo)analysis of resting-state functional magnetic resonance imaging.The study included 149 hospital patients divided into four groups:Patients experiencing their first episode of drug-naive MDD with OB,patients with MDD without OB,and age-and sex-matched healthy individuals with and without OB.Whole-brain ReHo analysis was conducted using SPM12 software and RESTplus toolkits,with group comparisons via ANOVA and post-hoc tests.Correlations between ReHo values and behavioral measures were examined.RESULTS ANOVA revealed significant whole-brain ReHo differences among the four groups in four key regions:The left middle temporal gyrus(MTG.L),right cuneus,left precuneus,and left thalamus.Post-hoc analyses confirmed pairwise differences between all groups across these regions(P<0.05).OB was associated with ReHo alterations in the MTG.L,right cuneus,and left thalamus,whereas abnormalities in the precuneus suggested synergistic pathological mechanisms between MDD and OB.Statistically significant correlations were found between the drive and fun-seeking dimensions of the behavioral activation system,as well as behavioral inhibition and the corresponding ReHo values.CONCLUSION Our findings provide novel evidence for the neuroadaptive mechanisms underlying the MDD-OB comorbidity.Further validation could lead to personalized interventions targeting MTG.L hyperactivity and targeting healthy food cues.
文摘Background:Early detection of harmful brain activity in critically ill patients using electroencephalography(EEG)is vital for timely and effective clinical intervention.Automating EEG analysis with deep learning techniques holds significant promise for enhancing diagnostic efficiency and accuracy.Methods:We implemented EfficientNetB2,which leverages convolutional neural networks with a novel Temporal Squeeze-and-Excitation module to capture temporal EEG features,and WaveNet,a sequential model designed to effectively model temporal dependencies in EEG data using dilated causal convolutions and temporal self-attention.Both models were trained and evaluated using a publicly available EEG dataset,with performance assessed via 4-fold cross-validation and a step-wise learning rate reduction strategy.Results:Our results demonstrate a significant reduction in training loss from 0.6459 to 0.3055 and validation loss from 0.9602 to 0.5719 over six epochs.Consistent improvements were observed across cross-validation folds,highlighting the robustness of the models.Additionally,ensemble learning of the two architectures further enhanced classification performance.Conclusion:This comparative analysis sheds light on the strengths and limitations of EfficientNetB2 and WaveNet for automated harmful brain activity detection in EEG signals.The findings contribute to the advancement of reliable and efficient deep learning models,paving the way for their clinical application in managing critically ill patients.
基金supported by Science and Technology Standard Project of Guangdong Electric Power Design Institute(ER11301W,ER11811W).
文摘Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.
基金financial support from the National Natural Science Foundation of China (Nos.82473887 and 21927808)the Scientific and Technological Innovation Program of Shanghai (No.23DZ2202500)the CAMS Innovation Fund for Medical Sciences (No.2021-1-I2M-026)。
文摘The brain's functions are governed by molecular metabolic networks.However,due to the sophisticated spatial organization and diverse activities of the brain,characterizing both the minute and large-scale metabolic activity across the entire brain and its numerous micro-regions remains incredibly challenging.Here,we offer a high-definition spatially resolved metabolomics technique to better understand the metabolic specialization and interconnection throughout the mouse brain using improved ambient mass spectrometry imaging.This method allows for the simultaneous mapping of thousands of metabolites at a 30 μm spatial resolution across the mouse brain,ranging from structural lipids to functional neurotransmitters.This approach effectively reveals the distribution patterns of delicate microregions and their distinctive metabolic characteristics.Using an integrated database,we annotated 259 metabolites,demonstrating that the metabolome and metabolic pathways are unique to each brain microregion.The distribution of metabolites,closely linked to functionally connected brain regions and their interactions,offers profound insights into the complexity of chemical processes and their roles in brain function.An initial dataset for future metabolomics research might be obtained from the high-definition mouse brain's spatial metabolome atlas.
基金funded by the Fundamental Research Funds for the Central Universities (No.2242022R42012)。
文摘In recent years,development of strategies to treat central nervous system(CNS) diseases has attracted extensive attention.A major obstacle in this field is the blood-brain barrier(BBB),which significantly limits the efficient delivery of therapeutic agents to the brain and hinders the treatment of CNS diseases.Overcoming the restrictive nature of the BBB has thus emerged as a key objective in CNS drug development.Nanomaterials have garnered growing interest due to their unique physicochemical properties and potential to traverse the BBB,enabling targeted drug delivery to brain tissue and improving therapeutic efficacy.In this review,we present current insights into the structure and function of the BBB and highlight a range of nanomaterial-based strategies for BBB penetration,including receptor-mediated transport(RMT),adsorptive-mediated transcytosis,reversible BBB disruption,and intranasal administration.Finally,we summarize recent advances in enhancing BBB permeability for CNS therapeutics and discuss persisting challenges,offering perspectives for future research in this field.
基金supported by Progetto Trapezio,Compagnia di San Paolo(67935-2021.2174),to LBFondazione CRT(Cassa di Risparmio di Torino,RF=2022.0618),to LBPRIN2022(grant 2022LB4X3N),to LB。
文摘The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.However,recent findings revealed that some forms of neural plasticity can show a reverse trend.Although plasticity is a well-preserved,transversal feature across the animal world,a variety of cell populations and mechanisms seem to have evolved to enable structural modifications to take place in widely different brains,likely as adaptations to selective pressures.Increasing evidence now indicates that a trade-off has occurred between regenerative(mostly stem cell–driven)plasticity and developmental(mostly juvenile)remodeling,with the latter primarily aimed not at brain repair but rather at“sculpting”the neural circuits based on experience.In particular,an evolutionary trade-off has occurred between neurogenic processes intended to support the possibility of recruiting new neurons throughout life and the different ways of obtaining new neurons,and between the different brain locations in which plasticity occurs.This review first briefly surveys the different types of plasticity and the complexity of their possible outcomes and then focuses on recent findings showing that the mammalian brain has a stem cell–independent integration of new neurons into pre-existing(mature)neural circuits.This process is still largely unknown but involves neuronal cells that have been blocked in arrested maturation since their embryonic origin(also termed“immature”or“dormant”neurons).These cells can then restart maturation throughout the animal's lifespan to become functional neurons in brain regions,such as the cerebral cortex and amygdala,that are relevant to high-order cognition and emotions.Unlike stem cell–driven postnatal/adult neurogenesis,which significantly decreases from small-brained,short-living species to large-brained ones,immature neurons are particularly abundant in large-brained,long-living mammals,including humans.The immature neural cell populations hosted in these complex brains are an interesting example of an“enlarged road”in the phylogenetic trend of plastic potential decreases commonly observed in the animal world.The topic of dormant neurons that covary with brain size and gyrencephaly represents a prospective turning point in the field of neuroplasticity,with important translational outcomes.These cells can represent a reservoir of undifferentiated neurons,potentially granting plasticity within the high-order circuits subserving the most sophisticated cognitive skills that are important in the growing brains of young,healthy individuals and are frequently affected by debilitating neurodevelopmental and degenerative disorders.
