In this article,the authors explore the online updating estimation for general estimating equations(EEs)in heterogeneous streaming data settings.The framework is based on more conservative model assumptions,leading to...In this article,the authors explore the online updating estimation for general estimating equations(EEs)in heterogeneous streaming data settings.The framework is based on more conservative model assumptions,leading to more robust estimations and preventing misspecification.The authors establish the standard renewable estimation under blockwise heterogeneity assumption,which can correctly specify model in some sense.To mitigate heterogeneity and enhance estimation accuracy,the authors propose two novel online detection and fusion strategies,with corresponding algorithms provided.Theoretical properties of the proposed methods are demonstrated in the context of small block sizes.Extensive numerical experiments validate the theoretical findings.Real data analysis of the Ford Gobike docked bike-sharing dataset verifies the feasibility and robustness of the proposed methods.展开更多
Promoting the synergistic governance of pollution control(PC)and carbon reduction(CR)in the agricultural sector was an important way for the Chinese government to implement the“dual carbon”initiative and respond to ...Promoting the synergistic governance of pollution control(PC)and carbon reduction(CR)in the agricultural sector was an important way for the Chinese government to implement the“dual carbon”initiative and respond to climate change.Based on the data of China’s crop production from 31 provincial-level regions from 1997 to 2022,this paper constructs a framework consisting of spatiotemporal evolution,synergy effect measurement,differences in contributions across regions,and influencing factors analysis to reveal the relationship between agricultural PC and CR.The results showed that the annual growth rates of pollutant emissions and carbon emissions were 1.85%and 0.79%,respectively.However,the annual decline rates of their emission intensities were 3.14%and 4.32%,respectively.This indicated that China’s actions to reduce pollution and carbon emissions in agriculture have achieved good results,that the effect of PC was weaker than that of CR and had an obvious“policy node effect.”Simultaneously,the synergy between PC and CR evolved from“basic coordination”to“basic imbalance.”The contribution of inter-regional differences was relatively large,while intra-regional differences were smaller,highlighting the importance of reducing regional disparities in promoting the synergistic governance of PC and CR.The basic conditions,industrial structure,input intensity,and development potential of agricultural development were key factors in widening the coupling coordination gap between PC and CR,and the influence of these significant factors exhibited clear spatiotemporal heterogeneity.These findings have provided important evidence for understanding China’s agricultural environmental governance strategies and could offer experiential insights for developing countries in advancing the coordinated governance of agricultural PC and CR.展开更多
Traditional clinical subtype classifications(such as amnestic and non-amnestic mild cognitive impairment)rely on subjective interpretations of overlapping patterns of performance on cognitive tests,which may lead to u...Traditional clinical subtype classifications(such as amnestic and non-amnestic mild cognitive impairment)rely on subjective interpretations of overlapping patterns of performance on cognitive tests,which may lead to unreliable categorization.A more precise and objective classification of mild cognitive impairment subtypes can be achieved through data-driven clustering techniques.However,because previous studies have not restricted their cohorts to patients who have mild cognitive impairment with the pathology of Alzheimer’s disease,the nature of cognitive variability and its impact on disease progression in a strictly defined biomarker-positive preclinical Alzheimer’s disease cohort remains unknown.We examined cognitive heterogeneity among participants with mild cognitive impairment due to Alzheimer’s disease and evaluated its prognostic utility.Neuropsychological test data from 389 patients with mild cognitive impairment in whom the cerebrospinal fluid biomarker confirmed Alzheimer’s disease were obtained from the Alzheimer’s Disease Neuroimaging Initiative cohorts.Principal component analysis and model-based clustering were used to identify cognitive profiles,which were then validated through a 100-time bootstrap analysis.Pairwise comparisons tested for differences between the identified subgroups in participant characteristics,scores on cognitive and clinical outcomes,levels of cerebrospinal fluid biomarkers,and magnetic resonance imaging-derived brain volumes.Longitudinal analyses evaluated differences in rate of change of magnetic resonance imaging volumetric measurements and clinical outcomes over 48 months.Survival analysis assessed risk for conversion to dementia.Alpha-synuclein levels and white matter hyperintensity volumes were considered for sensitivity analysis.Two distinct cognitive profiles were identified:a“typical”group(56.04%of the sample)that demonstrated relatively poorer scores on memory testing than non-memory tests,and an“atypical”group(43.96%of the sample)with smaller differences between memory and non-memory measures,indicating a more uniform pattern of impairment across cognitive domains.While the groups had comparable levels of overall cognitive impairment and cerebrospinal fluid biomarkers of Alzheimer’s disease,the typical group displayed accelerated atrophy rates every 6 months across multiple brain regions(hippocampus:29.02 mm^(3),standard error[SE]=10.13,P=0.005;whole brain:1799.85 mm^(3),SE=781.57,P=0.023;entorhinal cortex:22.26 mm^(3),SE=11.15,P=0.048;fusiform gyrus:66.24 mm^(3),SE=28.53,P=0.021).Survival analysis revealed markedly higher dementia conversion risk(hazard ratio:1.70,95%confidence interval:1.27,2.27,P<0.001)and shorter progression time in the typical group.These findings persisted after controlling for comorbid pathologies.In conclusion,this data-driven approach identified two distinct cognitive subtypes of mild cognitive impairment due to Alzheimer’s disease that differed in their rates of clinical decline and neurodegeneration.These findings could be used to improve prognostic models and inform clinical trial stratification.展开更多
The presence or absence of adult neural stem cells in the mammalian forebrain ependyma has been debated for two decades.In this study,we performed single-cell RNA sequencing to investigate the cellular composition of ...The presence or absence of adult neural stem cells in the mammalian forebrain ependyma has been debated for two decades.In this study,we performed single-cell RNA sequencing to investigate the cellular composition of the ependymal surface of the adult mouse forebrain using whole mounts of lateral walls of lateral ventricles.We identified 12 different cell subtypes in the ependymal surface.Immunocytochemical analyses revealed that CD133^(+)multi-ciliated cells comprised 67.6%of ependymal cells,while the remaining 32.4%were CD133^(-).CD133^(+)ependymal cells can be further classified into FOXJ1^(+)/SOX2^(+)/ACTA2^(+)cells,FLT1^(+)/CD31^(+)/CLDN5^(+)endothelial-like cells,and PDGFRB^(+)/VTN^(+)/NG2^(+)pericyte-like cells,as well as endothelial-pericyte-like cells and Foxj1^(+)endothelial-like cells.CD133^(-)ependymal cells can be further divided into endothelial-like cells,Foxj1^(+)ependymal cells,Foxj1^(+)endothelial-like cells,pericyte-like cells,endothelial-pericyte-like cells,VIM^(+)cells,and cells negative for all of these markers.This comprehensive profiling confirms the heterogeneity of the ependymal surface in the adult mouse forebrain.Debate regarding whether adult ependymal cells contain neural stem cells has arisen because different researchers have examined different populations of ependymal cells.Our study provides a new perspective for investigation of clinical endogenous neural stem cells,ultimately paving the way for stem cell therapies in neurological diseases.展开更多
The Internet of Vehicles(IoV)is an emerging technology that aims to connect vehicles,infrastructure,and other devices to enable intelligent transportation systems.One of the key challenges in IoV is to ensure safe and...The Internet of Vehicles(IoV)is an emerging technology that aims to connect vehicles,infrastructure,and other devices to enable intelligent transportation systems.One of the key challenges in IoV is to ensure safe and efficient communication among vehicles of different types and capabilities.This paper proposes a data-driven vehicular heterogeneity-based intelligent collision avoidance system for IoV.The system leverages Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication to collect real-time data about the environment and the vehicles.The data is collected to acknowledge the heterogeneity of vehicles and human behavior.The data is analyzed using machine learning algorithms to identify potential collision risks and recommend appropriate actions to avoid collisions.The system takes into account the heterogeneity of vehicles,such as their size,speed,and maneuverability,to optimize collision avoidance strategies.The proposed system is experimented with real-time datasets and compared with existing collision avoidance systems.The results are shown using the evaluation metrics that show the proposed system can significantly reduce the number of collisions and improve the overall safety and efficiency of IoV with an accuracy of 96.5%using the SVM algorithm.The trial outcomes demonstrated that the new system,incorporating vehicular,weather,and human behavior factors,outperformed previous systems that only considered vehicular and weather aspects.This innovative approach is poised to lead transportation efforts,reducing accident rates and improving the quality of transportation systems in smart cities.By offering predictive capabilities,the proposed model not only helps control accident rates but also prevents them in advance,ensuring road safety.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
In the fast-paced living environment, changes in dietary patterns have led to a continuous increase in the incidence and mortality rates of colorectal cancer (CRC), making it a prevalent malignant tumor of the digesti...In the fast-paced living environment, changes in dietary patterns have led to a continuous increase in the incidence and mortality rates of colorectal cancer (CRC), making it a prevalent malignant tumor of the digestive system worldwide. Currently, CRC clinical diagnosis and treatment face challenges such as high costs and persistently high recurrence rates. Traditional quantification of tumor-infiltrating lymphocytes (TILs) relies on manual analysis and judgment, resulting in low diagnostic efficiency and susceptibility to subjective factors, leading to missed or misdiagnosed cases. To enhance the efficiency and quality of CRC clinical diagnosis and treatment, this study explores domestic and international research on the automatic identification of CRC cells using machine learning strategies. It analyzes the morphological heterogeneity and prognostic value in the application of this strategy, aiming to deepen the understanding of intelligent tool applications in precise diagnosis, treatment, and prognostic evaluation of colorectal cancer, comprehend the current research status and development trends, and provide references for addressing and addressing the gaps in related research.展开更多
Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More r...Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.展开更多
Quantifying spatial heterogeneity in soil water retention properties(SWRP)is crucial for enhancing the accuracy of hydrogeological simulations.However,studies on the spatial heterogeneity of SWRP in the Chinese Loess ...Quantifying spatial heterogeneity in soil water retention properties(SWRP)is crucial for enhancing the accuracy of hydrogeological simulations.However,studies on the spatial heterogeneity of SWRP in the Chinese Loess Plateau(CLP)remain scarce,especially at the vertical scale.We conducted laboratory tests on undisturbed loess cores collected from boreholes in CLP to analyze soil physical parameters(SPPs)and SWRP.Measured soil water characteristic curves(SWCCs)were fitted to the Brooks-Corey(BC),Fredlund-Xing(FX),and van Genuchten(vG)models.It was revealed that the FX and vG models outperformed the BC model.The geostatistical analysis identified the Gaussian model as optimal for describing the semivariograms of both SPPs and SWCC fitting parameters(FPs).Strikingly,over 90%of these parameters exhibited strong vertical spatial dependence,with an average autocorrelation length of 213.878 cm for SPPs and 320.678 cm for FPs.Moreover,SWRP was found to be significantly influenced by both SPPs and the vertical position relative to the loess ridge slope surface.Parameters near the ridge slope surface showed significantly degraded spatial dependence.These findings provide valuable insights for parameterizing the spatial heterogeneity of soil water retention properties,which are beneficial for hydrogeological modelling in shallow CLP loess strata.展开更多
Objective:Leucine-rich alpha-2 glycoprotein 1(Lrg1)could regulate diverse cells in cerebral ischemiareperfusion.Our study seeks to uncover Lrg1’s impact on endothelial cell heterogeneity via differentiation pathways ...Objective:Leucine-rich alpha-2 glycoprotein 1(Lrg1)could regulate diverse cells in cerebral ischemiareperfusion.Our study seeks to uncover Lrg1’s impact on endothelial cell heterogeneity via differentiation pathways and transcription factors.Method:The CSOmap model measured cell-to-brain-center distances using single-cell RNA sequencing(scRNA-seq)data in middle cerebral artery occlusion reperfusion(MCAO/R).Monocle2 mapped endothelial differentiation paths.Gene set enrichment analysis(GSEA)analyzed endothelial subcluster variations.Database searches revealed a zinc finger MIZ-type containing 1 protein-frizzled 3(Zmiz1-Fzd3)promoter interaction.Endothelial cells were transfected with a Fzd3 promoter-luciferase plasmid.Polymerase chain reaction(PCR)and western blotting assessed MCAO/R or Zmiz1 overexpression effects on Fzd3-related mRNA and proteins.A retroviral vector carrying Zmiz1 was injected into the brains of mice to study its effect on Fzd3.Result:Lrg1−/−mice exhibited elevated cell adhesion proteins and decreased microvascular leakage after MCAO/R.CSOmap showed widened astrocyte spacing in thesemice.RSS revealed Zmiz1 overexpression inMCAO/R+Lrg1−/−mice.MCAO/R and pcDNA3-Zmiz1 transfection both enhanced luciferase activity with Fzd3,indicating Zmiz1 binding to Fzd3.Retroviral Zmiz1 injection or knockdown disrupted ischemic brain tight junctions,highlighting Zmiz1’s key role in blood-brain barrier protection,likely through Fzd3 pathway modulation.Conclusion:The findings indicate Lrg1 knockout induces endothelial differentiation by activating Zmiz1,which is crucial for maintaining blood-brain barrier function,possibly via modulating the Fzd3 pathway.展开更多
Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between th...Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.展开更多
Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce t...Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design...Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.展开更多
The spatial distribution of overburden layer thickness(OLT)is crucial for landslide susceptibility prediction and slope stability analysis.Due to OLT spatial heterogeneity in hillslope regions,combined with the diffic...The spatial distribution of overburden layer thickness(OLT)is crucial for landslide susceptibility prediction and slope stability analysis.Due to OLT spatial heterogeneity in hillslope regions,combined with the difficulty and time consumption of OLT sample collection,accurately predicting OLT distribution remains a challenging.To address this,a novel framework has been developed.First,OLT samples are collected through field surveys,remote sensing,and geological drilling.Next,the heterogeneity of OLT’s spatial distribution is analyzed using the probability distribution of OLT samples and their horizontal and vertical distributions.The OLT samples are categorized and the small sample categories are expanded using the synthetic minority over-sampling technique(SMOTE).The slope position is selected as a key conditioning factor.Subsequently,16 conditioning factors are applied to construct OLT prediction model using the random forest regression algorithm.Weights are assigned to each OLT sample category to balance the uneven distribution of sample sizes.Finally,the Pearson correlation coefficient,mean absolute error(MAE),root mean square error(RMSE),and Lin’s concordance correlation coefficient(Lin’s CCC)are employed to validate the OLT prediction results.The Huangtan town serves as the case study.Results show:(1)heterogeneity analysis,SMOTE-based OLT sample expansion strategy and slope position selection can significantly mitigate the effect of spatial heterogeneity on OLT prediction.(2)The Pearson correlation coefficient,RMSE,MAE and Lin’s CCC values are 0.84,1.173,1.378 and 0.804,respectively,indicating excellent prediction performance.This research provides an effective solution for predicting OLT distribution in hillslope regions.展开更多
In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics...In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.展开更多
Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functio...Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.展开更多
Objective:Practice related to the traditional postpartum confinement custom“Zuo Yuezi”vary among individuals,and its relationship with postpartum depression(PPD)remains unclear.This study aims to explore the current...Objective:Practice related to the traditional postpartum confinement custom“Zuo Yuezi”vary among individuals,and its relationship with postpartum depression(PPD)remains unclear.This study aims to explore the current practice and heterogeneity of“Zuo Yuezi”among Chinese women and to analyze its association with PPD.Methods:A cross-sectional study was conducted among 542 women from 3 hospitals between January and February 2016.Data were collected on whether participants practiced“Zuo Yuezi”,their willingness and attitudes toward“Zuo Yuezi”,demographic characteristics,adherence to specific“Zuo Yuezi”practices,emotional experiences during the“Zuo Yuezi”period,and PPD symptoms.Latent profile analysis(LPA)was used to identify heterogeneity in“Zuo Yuezi”practices,and multivariate logistic regression was used to analyze the association between practice patterns and PPD.Results:A total of 542 postpartum women completed the survey.About 98%(531/542)of participants reported practicing“Zuo Yuezi”,among whom 41.2%followed traditional customs and 29.5%followed parental advice.Approximately 95%of women practiced“Zuo Yuezi”for≥30 days,and nearly half strictly followed a 30-day“Zuo Yuezi”period.Significant heterogeneity was observed in practice components and adherence levels,with the greatest heterogeneity in dietary practices and the lowest in hygiene practices.Latent profile analysis identified 4 levels of adherence to“Zuo Yuezi”practices:low,mediumlow,medium,and high.Higher adherence was associated with belief in disease prevention,home-based“Zuo Yuezi”practices,and longer“Zuo Yuezi”duration.Lower adherence was associated with an increased risk of PPD(χ^(2)=16.103,P<0.05).Conclusion:The practice of“Zuo Yuezi”is widespread but heterogeneous.Lower adherence to“Zuo Yuezi”practices may increase the risk of postpartum depression,highlighting the need for culturally sensitive and individualized perinatal care.展开更多
Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its ability to stimulate antitumor immune responses while minimizing damage to healthy tissues.However,the significant het...Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its ability to stimulate antitumor immune responses while minimizing damage to healthy tissues.However,the significant heterogeneity in immune responses among patients complicates its clinical application,hindering outcome prediction and treatment personalization.Artificial intelligence(AI)offers a transformative solution by integrating multidimensional data such as immunomics,radiomics,and clinical features to decode complex immune pa-tterns and predict individual therapeutic outcomes.This editorial explored the potential of AI to address immune response heterogeneity in low-dose radiation therapy and proposed an AI-driven framework for precision immunotherapy.While promising,challenges,including data standardization,model interpre-tability,and clinical validation,must be overcome to ensure successful integration into oncological practice.展开更多
Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in signific...Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.12471281in part by the National Statistical Science Research Project under Grant No.2022LD03。
文摘In this article,the authors explore the online updating estimation for general estimating equations(EEs)in heterogeneous streaming data settings.The framework is based on more conservative model assumptions,leading to more robust estimations and preventing misspecification.The authors establish the standard renewable estimation under blockwise heterogeneity assumption,which can correctly specify model in some sense.To mitigate heterogeneity and enhance estimation accuracy,the authors propose two novel online detection and fusion strategies,with corresponding algorithms provided.Theoretical properties of the proposed methods are demonstrated in the context of small block sizes.Extensive numerical experiments validate the theoretical findings.Real data analysis of the Ford Gobike docked bike-sharing dataset verifies the feasibility and robustness of the proposed methods.
基金National Social Science Fund of China,No.22BGL182。
文摘Promoting the synergistic governance of pollution control(PC)and carbon reduction(CR)in the agricultural sector was an important way for the Chinese government to implement the“dual carbon”initiative and respond to climate change.Based on the data of China’s crop production from 31 provincial-level regions from 1997 to 2022,this paper constructs a framework consisting of spatiotemporal evolution,synergy effect measurement,differences in contributions across regions,and influencing factors analysis to reveal the relationship between agricultural PC and CR.The results showed that the annual growth rates of pollutant emissions and carbon emissions were 1.85%and 0.79%,respectively.However,the annual decline rates of their emission intensities were 3.14%and 4.32%,respectively.This indicated that China’s actions to reduce pollution and carbon emissions in agriculture have achieved good results,that the effect of PC was weaker than that of CR and had an obvious“policy node effect.”Simultaneously,the synergy between PC and CR evolved from“basic coordination”to“basic imbalance.”The contribution of inter-regional differences was relatively large,while intra-regional differences were smaller,highlighting the importance of reducing regional disparities in promoting the synergistic governance of PC and CR.The basic conditions,industrial structure,input intensity,and development potential of agricultural development were key factors in widening the coupling coordination gap between PC and CR,and the influence of these significant factors exhibited clear spatiotemporal heterogeneity.These findings have provided important evidence for understanding China’s agricultural environmental governance strategies and could offer experiential insights for developing countries in advancing the coordinated governance of agricultural PC and CR.
基金funded by Shanghai Baiyulan Pujiang Project(No.24PJD087)funded by the National Natural Science Foundation of China(No.12401347)+5 种基金Shanghai“Science and Technology Innovation Action Plan”Computational Biology Key Project(Nos.23JS1400500 and 23JS1400800)Chinese MOE Foundation on Humanities and Social Sciences(No.23YJC910006)the Natural Science Foundation of Shanghai(No.24ZR1420400)MWB was funded by NIH/NIA(Nos.R01AG082073,R01AG079280,and P30AG062429)HHF was funded by NIH/NIA(Nos.U19AG079774-01,R01AG061146,P30AG062429,R01AG076634-01,CIHR 137794)funded by NIH/NIA R01AG064002,P30AG062429,R01AG076634,and the Epstein Family Alzheimer’s Research Collaboration.
文摘Traditional clinical subtype classifications(such as amnestic and non-amnestic mild cognitive impairment)rely on subjective interpretations of overlapping patterns of performance on cognitive tests,which may lead to unreliable categorization.A more precise and objective classification of mild cognitive impairment subtypes can be achieved through data-driven clustering techniques.However,because previous studies have not restricted their cohorts to patients who have mild cognitive impairment with the pathology of Alzheimer’s disease,the nature of cognitive variability and its impact on disease progression in a strictly defined biomarker-positive preclinical Alzheimer’s disease cohort remains unknown.We examined cognitive heterogeneity among participants with mild cognitive impairment due to Alzheimer’s disease and evaluated its prognostic utility.Neuropsychological test data from 389 patients with mild cognitive impairment in whom the cerebrospinal fluid biomarker confirmed Alzheimer’s disease were obtained from the Alzheimer’s Disease Neuroimaging Initiative cohorts.Principal component analysis and model-based clustering were used to identify cognitive profiles,which were then validated through a 100-time bootstrap analysis.Pairwise comparisons tested for differences between the identified subgroups in participant characteristics,scores on cognitive and clinical outcomes,levels of cerebrospinal fluid biomarkers,and magnetic resonance imaging-derived brain volumes.Longitudinal analyses evaluated differences in rate of change of magnetic resonance imaging volumetric measurements and clinical outcomes over 48 months.Survival analysis assessed risk for conversion to dementia.Alpha-synuclein levels and white matter hyperintensity volumes were considered for sensitivity analysis.Two distinct cognitive profiles were identified:a“typical”group(56.04%of the sample)that demonstrated relatively poorer scores on memory testing than non-memory tests,and an“atypical”group(43.96%of the sample)with smaller differences between memory and non-memory measures,indicating a more uniform pattern of impairment across cognitive domains.While the groups had comparable levels of overall cognitive impairment and cerebrospinal fluid biomarkers of Alzheimer’s disease,the typical group displayed accelerated atrophy rates every 6 months across multiple brain regions(hippocampus:29.02 mm^(3),standard error[SE]=10.13,P=0.005;whole brain:1799.85 mm^(3),SE=781.57,P=0.023;entorhinal cortex:22.26 mm^(3),SE=11.15,P=0.048;fusiform gyrus:66.24 mm^(3),SE=28.53,P=0.021).Survival analysis revealed markedly higher dementia conversion risk(hazard ratio:1.70,95%confidence interval:1.27,2.27,P<0.001)and shorter progression time in the typical group.These findings persisted after controlling for comorbid pathologies.In conclusion,this data-driven approach identified two distinct cognitive subtypes of mild cognitive impairment due to Alzheimer’s disease that differed in their rates of clinical decline and neurodegeneration.These findings could be used to improve prognostic models and inform clinical trial stratification.
基金supported by the State Key Program of the National Natural Science Foundation of China,No.82030035(to YES)Peak Disciplines(Type IV)of Institutions of Higher Learning in Shanghai(to LZ).
文摘The presence or absence of adult neural stem cells in the mammalian forebrain ependyma has been debated for two decades.In this study,we performed single-cell RNA sequencing to investigate the cellular composition of the ependymal surface of the adult mouse forebrain using whole mounts of lateral walls of lateral ventricles.We identified 12 different cell subtypes in the ependymal surface.Immunocytochemical analyses revealed that CD133^(+)multi-ciliated cells comprised 67.6%of ependymal cells,while the remaining 32.4%were CD133^(-).CD133^(+)ependymal cells can be further classified into FOXJ1^(+)/SOX2^(+)/ACTA2^(+)cells,FLT1^(+)/CD31^(+)/CLDN5^(+)endothelial-like cells,and PDGFRB^(+)/VTN^(+)/NG2^(+)pericyte-like cells,as well as endothelial-pericyte-like cells and Foxj1^(+)endothelial-like cells.CD133^(-)ependymal cells can be further divided into endothelial-like cells,Foxj1^(+)ependymal cells,Foxj1^(+)endothelial-like cells,pericyte-like cells,endothelial-pericyte-like cells,VIM^(+)cells,and cells negative for all of these markers.This comprehensive profiling confirms the heterogeneity of the ependymal surface in the adult mouse forebrain.Debate regarding whether adult ependymal cells contain neural stem cells has arisen because different researchers have examined different populations of ependymal cells.Our study provides a new perspective for investigation of clinical endogenous neural stem cells,ultimately paving the way for stem cell therapies in neurological diseases.
文摘The Internet of Vehicles(IoV)is an emerging technology that aims to connect vehicles,infrastructure,and other devices to enable intelligent transportation systems.One of the key challenges in IoV is to ensure safe and efficient communication among vehicles of different types and capabilities.This paper proposes a data-driven vehicular heterogeneity-based intelligent collision avoidance system for IoV.The system leverages Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication to collect real-time data about the environment and the vehicles.The data is collected to acknowledge the heterogeneity of vehicles and human behavior.The data is analyzed using machine learning algorithms to identify potential collision risks and recommend appropriate actions to avoid collisions.The system takes into account the heterogeneity of vehicles,such as their size,speed,and maneuverability,to optimize collision avoidance strategies.The proposed system is experimented with real-time datasets and compared with existing collision avoidance systems.The results are shown using the evaluation metrics that show the proposed system can significantly reduce the number of collisions and improve the overall safety and efficiency of IoV with an accuracy of 96.5%using the SVM algorithm.The trial outcomes demonstrated that the new system,incorporating vehicular,weather,and human behavior factors,outperformed previous systems that only considered vehicular and weather aspects.This innovative approach is poised to lead transportation efforts,reducing accident rates and improving the quality of transportation systems in smart cities.By offering predictive capabilities,the proposed model not only helps control accident rates but also prevents them in advance,ensuring road safety.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
文摘In the fast-paced living environment, changes in dietary patterns have led to a continuous increase in the incidence and mortality rates of colorectal cancer (CRC), making it a prevalent malignant tumor of the digestive system worldwide. Currently, CRC clinical diagnosis and treatment face challenges such as high costs and persistently high recurrence rates. Traditional quantification of tumor-infiltrating lymphocytes (TILs) relies on manual analysis and judgment, resulting in low diagnostic efficiency and susceptibility to subjective factors, leading to missed or misdiagnosed cases. To enhance the efficiency and quality of CRC clinical diagnosis and treatment, this study explores domestic and international research on the automatic identification of CRC cells using machine learning strategies. It analyzes the morphological heterogeneity and prognostic value in the application of this strategy, aiming to deepen the understanding of intelligent tool applications in precise diagnosis, treatment, and prognostic evaluation of colorectal cancer, comprehend the current research status and development trends, and provide references for addressing and addressing the gaps in related research.
基金supported by the National Natural Science Foundation of China,Nos.82404892(to QY),82061160374(to ZZ)the Science and Technology Development Fund,Macao Special Administrative Region,China,Nos.0023/2020/AFJ,0035/2020/AGJ+2 种基金the University of Macao Research Grant,Nos.MYRG2022-00248-ICMS,MYRG-CRG2022-00010-ICMS(to MPMH)the Natural Science Foundation of Guangdong Province,No.2024A1515012818(to ZZ)the Fundamental Research Funds for the Central Universities,No.21623114(to ZZ).
文摘Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.
基金supported by the National Natural Science Foundation of China(Grant No.52379097)the National Natural Science Foundation of China(No.52509138)+2 种基金the Water Conservancy Science and Technology Project of Jiangxi Province(Grant No.202426ZDKT27)Chongqing Natural Science Foundation Doctoral Program(CSTB2025NSCQ-BSX0020)the Research and Innovation Program for Graduate Students of Chongqing Municipality(Grant No.CYB23251).
文摘Quantifying spatial heterogeneity in soil water retention properties(SWRP)is crucial for enhancing the accuracy of hydrogeological simulations.However,studies on the spatial heterogeneity of SWRP in the Chinese Loess Plateau(CLP)remain scarce,especially at the vertical scale.We conducted laboratory tests on undisturbed loess cores collected from boreholes in CLP to analyze soil physical parameters(SPPs)and SWRP.Measured soil water characteristic curves(SWCCs)were fitted to the Brooks-Corey(BC),Fredlund-Xing(FX),and van Genuchten(vG)models.It was revealed that the FX and vG models outperformed the BC model.The geostatistical analysis identified the Gaussian model as optimal for describing the semivariograms of both SPPs and SWCC fitting parameters(FPs).Strikingly,over 90%of these parameters exhibited strong vertical spatial dependence,with an average autocorrelation length of 213.878 cm for SPPs and 320.678 cm for FPs.Moreover,SWRP was found to be significantly influenced by both SPPs and the vertical position relative to the loess ridge slope surface.Parameters near the ridge slope surface showed significantly degraded spatial dependence.These findings provide valuable insights for parameterizing the spatial heterogeneity of soil water retention properties,which are beneficial for hydrogeological modelling in shallow CLP loess strata.
基金supported by the Foundation Project:National Natural Science.Foundation of China(Nos.:82460249,82100417,81760094)The Foundation of Jiangxi Provincial Department of Science and Technology Outstanding Youth Fund Project(20212BAB206022,20242BAB23080).
文摘Objective:Leucine-rich alpha-2 glycoprotein 1(Lrg1)could regulate diverse cells in cerebral ischemiareperfusion.Our study seeks to uncover Lrg1’s impact on endothelial cell heterogeneity via differentiation pathways and transcription factors.Method:The CSOmap model measured cell-to-brain-center distances using single-cell RNA sequencing(scRNA-seq)data in middle cerebral artery occlusion reperfusion(MCAO/R).Monocle2 mapped endothelial differentiation paths.Gene set enrichment analysis(GSEA)analyzed endothelial subcluster variations.Database searches revealed a zinc finger MIZ-type containing 1 protein-frizzled 3(Zmiz1-Fzd3)promoter interaction.Endothelial cells were transfected with a Fzd3 promoter-luciferase plasmid.Polymerase chain reaction(PCR)and western blotting assessed MCAO/R or Zmiz1 overexpression effects on Fzd3-related mRNA and proteins.A retroviral vector carrying Zmiz1 was injected into the brains of mice to study its effect on Fzd3.Result:Lrg1−/−mice exhibited elevated cell adhesion proteins and decreased microvascular leakage after MCAO/R.CSOmap showed widened astrocyte spacing in thesemice.RSS revealed Zmiz1 overexpression inMCAO/R+Lrg1−/−mice.MCAO/R and pcDNA3-Zmiz1 transfection both enhanced luciferase activity with Fzd3,indicating Zmiz1 binding to Fzd3.Retroviral Zmiz1 injection or knockdown disrupted ischemic brain tight junctions,highlighting Zmiz1’s key role in blood-brain barrier protection,likely through Fzd3 pathway modulation.Conclusion:The findings indicate Lrg1 knockout induces endothelial differentiation by activating Zmiz1,which is crucial for maintaining blood-brain barrier function,possibly via modulating the Fzd3 pathway.
基金financially supported by the National Natural Science Foundation of China(Nos.52173020 and 52573023)。
文摘Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01B187).
文摘Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金supported by the Sapienza Universitàdi Roma Sapienza Awards no.6H15XNFS.
文摘Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.
基金funded by the Natural Science Foundation of China(No.42407241,42272326 and 52222905)Jiangxi Provincial Natural Science Foundation(Nos.20242BAB20241,20242BAB23052 and 20242BAB24001).
文摘The spatial distribution of overburden layer thickness(OLT)is crucial for landslide susceptibility prediction and slope stability analysis.Due to OLT spatial heterogeneity in hillslope regions,combined with the difficulty and time consumption of OLT sample collection,accurately predicting OLT distribution remains a challenging.To address this,a novel framework has been developed.First,OLT samples are collected through field surveys,remote sensing,and geological drilling.Next,the heterogeneity of OLT’s spatial distribution is analyzed using the probability distribution of OLT samples and their horizontal and vertical distributions.The OLT samples are categorized and the small sample categories are expanded using the synthetic minority over-sampling technique(SMOTE).The slope position is selected as a key conditioning factor.Subsequently,16 conditioning factors are applied to construct OLT prediction model using the random forest regression algorithm.Weights are assigned to each OLT sample category to balance the uneven distribution of sample sizes.Finally,the Pearson correlation coefficient,mean absolute error(MAE),root mean square error(RMSE),and Lin’s concordance correlation coefficient(Lin’s CCC)are employed to validate the OLT prediction results.The Huangtan town serves as the case study.Results show:(1)heterogeneity analysis,SMOTE-based OLT sample expansion strategy and slope position selection can significantly mitigate the effect of spatial heterogeneity on OLT prediction.(2)The Pearson correlation coefficient,RMSE,MAE and Lin’s CCC values are 0.84,1.173,1.378 and 0.804,respectively,indicating excellent prediction performance.This research provides an effective solution for predicting OLT distribution in hillslope regions.
基金Chinese Scholarship Council(202206240086)National Natural Science Foundation of China(81974099,82170785,81974098,82170784)+4 种基金National Key Research and Development Program of China(2021YFC2009303)programs from Science and Technology Department of Sichuan Province(2021YFH0172)Young Investigator Award of Sichuan University 2017(2017SCU04A17)Technology Innovation Research and Development Project of Chengdu Science and Technology Bureau(2019-YF05-00296-SN)Sichuan University-Panzhihua science and technology cooperation special fund(2020CDPZH-4).
文摘In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.
基金supported by a grant from the Progressive MS Alliance(BRAVE in MS)Le Grand Portage Fund。
文摘Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.
基金supported by the National Natural Science Foundation(82273643 and 81973059)the Hunan Provincial Natural Science Foundation(2023JJ30712)+1 种基金the Youth Science Foundation of Hunan Provincial Natural Science Foundation Committee Class A Project(2025JJ20095)the Nutrition and Care of Maternal&Child Research Fund Project of Biostime Institute of Nutrition&Care(2018BINCMCF31),China.
文摘Objective:Practice related to the traditional postpartum confinement custom“Zuo Yuezi”vary among individuals,and its relationship with postpartum depression(PPD)remains unclear.This study aims to explore the current practice and heterogeneity of“Zuo Yuezi”among Chinese women and to analyze its association with PPD.Methods:A cross-sectional study was conducted among 542 women from 3 hospitals between January and February 2016.Data were collected on whether participants practiced“Zuo Yuezi”,their willingness and attitudes toward“Zuo Yuezi”,demographic characteristics,adherence to specific“Zuo Yuezi”practices,emotional experiences during the“Zuo Yuezi”period,and PPD symptoms.Latent profile analysis(LPA)was used to identify heterogeneity in“Zuo Yuezi”practices,and multivariate logistic regression was used to analyze the association between practice patterns and PPD.Results:A total of 542 postpartum women completed the survey.About 98%(531/542)of participants reported practicing“Zuo Yuezi”,among whom 41.2%followed traditional customs and 29.5%followed parental advice.Approximately 95%of women practiced“Zuo Yuezi”for≥30 days,and nearly half strictly followed a 30-day“Zuo Yuezi”period.Significant heterogeneity was observed in practice components and adherence levels,with the greatest heterogeneity in dietary practices and the lowest in hygiene practices.Latent profile analysis identified 4 levels of adherence to“Zuo Yuezi”practices:low,mediumlow,medium,and high.Higher adherence was associated with belief in disease prevention,home-based“Zuo Yuezi”practices,and longer“Zuo Yuezi”duration.Lower adherence was associated with an increased risk of PPD(χ^(2)=16.103,P<0.05).Conclusion:The practice of“Zuo Yuezi”is widespread but heterogeneous.Lower adherence to“Zuo Yuezi”practices may increase the risk of postpartum depression,highlighting the need for culturally sensitive and individualized perinatal care.
文摘Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its ability to stimulate antitumor immune responses while minimizing damage to healthy tissues.However,the significant heterogeneity in immune responses among patients complicates its clinical application,hindering outcome prediction and treatment personalization.Artificial intelligence(AI)offers a transformative solution by integrating multidimensional data such as immunomics,radiomics,and clinical features to decode complex immune pa-tterns and predict individual therapeutic outcomes.This editorial explored the potential of AI to address immune response heterogeneity in low-dose radiation therapy and proposed an AI-driven framework for precision immunotherapy.While promising,challenges,including data standardization,model interpre-tability,and clinical validation,must be overcome to ensure successful integration into oncological practice.
基金funded by the National Key Research and Development Program of China(grant number 2023YFC3009204)the National Natural Science Foundation of China(grant number 52174015).
文摘Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.
