Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

Assessment and Visualization of Ki67 Heterogeneity in Breast Cancers through Digital Image Analysis

The Ki67 index (KI) is a standard clinical marker for tumor proliferation;however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.

Editorial:Transcriptome analysis in tumor microenvironment and tumor heterogeneity

Cancer,a disease as intricate as it is devastating,continues to challenge the medical and scientific community[1].Its complex nature is epitomized by the tumor microenvironment and tumor heterogeneity.As we delve deeper into the realms of cancer research,the advent of transcriptome analysis has emerged as a powerful torchbearer,illuminating our understanding of these enigmatic facets of cancer biology[2].

Heterogeneity of mature oligodendrocytes in the central nervous system

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.

Research status and prospects of the fractal analysis of metal material surfaces and interfaces

As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.

Multilevel analysis of the central-peripheral-target organ pathway:contributing to recovery after peripheral nerve injury

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.

Characterizing heterogeneity in vehicular traffic speed using two-step cluster analysis

In order to analyze the heterogeneity in vehicular traffic speed, a new method that integrates cluster analysis and probability distribution function fitting is presented. First, for identifying the optimal number of clusters, the two-step cluster method is applied to analyze actual speed data, which suggests that dividing speed data into two clusters can best reflect the intrinsic patterns of traffic flows. Such information is then taken as guidance in probability distribution function fitting. The normal, skew-normal and skew-t distribution functions are used to fit the probability distribution of each cluster respectively, which suggests that the skew-t distribution has the highest fitting accuracy; the second is skew-normal distribution; the worst is normal distribution. Model analysis results demonstrate that the proposed mixture model has a better fitting and generalization capability than the conventional single model. In addition, the new method is more flexible in terms of data fitting and can provide a more accurate model of speed distribution.

Heterogeneity analysis of gas-solid flow hydrodynamics in a pilot-scale fluidized bed reactor

Mesoscale drag model is of crucial significance for the reliability and accuracy in coarse-grid EulerianEulerian two-fluid model(TFM)simulations of gas-solid flow hydrodynamics in fluidized bed reactors.Although numerous mesoscale drag models have been reported in the literature,a systematic comparison of their prediction capability from the perspective of heterogeneity analysis is still lacking.In this study,in order to investigate the effect of several typical drag models on the hydrodynamic behaviors,the nonuniformity analysis and the sensitivity to material properties,extensive coarse-grid TFM simulations of a bubbling pilot-scale fluidized bed reactor are carried out.The results demonstrate that the mesoscale drag models outperform the empirical drag model in terms of nonuniformity due to the consideration of the influence of the mesoscale structures on the drag force in the bubbling region.Furthermore,the results reveal that our previously developed three-marker gradient-based drag model considering the solid concentration gradient exhibits satisfactory performance in predicting the bubbling flow hydrodynamics.Besides,the material-property-dependent drag model considering the explicit effect of material properties on drag corrections is most sensitive to the particle diameter.This work provides guideline for possible future improvements of mesoscale models to simulate gas-solid flow more accurately and universally.

Analysis of Metro Station Ridership Considering Spatial Heterogeneity

This study aims to explore the role of spatial heterogeneity in ridership analysis and examine the relationship between built environment, station attributes and urban rapid transit ridership at the station level.Although spatial heterogeneity has been widely acknowledged in spatial data analysis, it has been rarely considered in travel behavior studies.Four models(three global models-ordinary least squares(OLS), spatial lag model(SLM), spatial error model(SEM) and one local model-geographically weighted regression(GWR) model) are estimated separately to explore the relationship between various independent variables and station ridership, and identify the influence of spatial heterogeneity.Using the data of built environment and station characteristics, the results of diagnostic identify evidence the existence of spatial heterogeneity in station ridership for the metro network in Nanjing, China.Results of comparing the various goodness-of-fit indicators show that, the GWR model yields the best fit of the data, performance followed by the SEM, SLM and OLS model.The results also demonstrate that population, number of lines, number of feeder buses, number of exits, road density and proportion residential area have a significant impact on station ridership.Moreover, the study pays special attention to the spatial variation in the coefficients of the independent variables and their statistical significance.It underlines the importance of taking spatial heterogeneity into account in the station ridership analysis and the decision-making in urban planning.

Heterogeneity Analysis of Cucumber Canopy in the Solar Greenhouse

Detailed analysis of canopy structural heterogeneity is an essential step in conducting parameters for a canopy structural model. This paper aims to analyze the structural heterogeneity of a cucumber （Cucumis sativus L.） canopy by means of analyzing leaf distribution in a greenhouse environment with natural sunlight and also to assess the effect of structural canopy heterogeneity on light interception and photosynthesis. Two experiments and four measurements were carried out in autumn 2011 and spring 2012. A static virtual three-dimensional （3D） canopy structure was reconstructed using a 3D digitizing method. The diurnal variation of photosynthesis rate was measured using CIRAS-2 photosynthesis system. The results showed that, leaf azimuth as tested with the Rayleigh-test was homogeneous at vine tip over stage but turned heterogeneous at fruit harvest stage. After eliminating the inlfuence of the environment on the azimuth using the von Mises-Fisher method, the angle between two successive leaves was 144°;at the same time, a rule for the azimuth distribution in the canopy was established, stating that the azimuth distribution in cucumber followed a law which was positive spin and anti-spin. Leaf elevation angle of south-oriented leaves was on average 13.8° higher than that of north-oriented leaves. The horizontal distribution of light interception and photosynthesis differed signiifcantly between differently oriented leaves. East-and west-oriented leaves exhibited the highest photosynthetic rate. In conclusion, detailed analysis of canopy structural heterogeneity in this study indicated that leaf azimuth and elevation angle were heterogeneous in cucumber canopy and they should be explicitly described as they have a great impact both on light distribution and photosynthesis.

A semi-analytical rate-transient analysis model for light oil reservoirs exhibiting reservoir heterogeneity and multiphase flow

Rate-transient analysis(RTA)has been widely applied to extract estimates of reservoir/hydraulic fracture properties.However,the majority of RTA techniques can lead to misdiagnosis of reservoir/fracture information when the reservoir exhibits reservoir heterogeneity and multiphase flow simultaneously.This work proposes a practical-yet-rigorous method to decouple the effects of reservoir heterogeneity and multiphase flow during TLF,and improve the evaluation of reservoir/fracture properties.A new,general,semi-analytical model is proposed that explicitly accounts for multiphase flow,fractalbased reservoir heterogeneity,anomalous diffusion,and pressure-dependent fluid properties.This is achieved by introducing a new Boltzmann-type transformation,the exponent of which includes reservoir heterogeneity and anomalous diffusion.In order to decouple the effects of reservoir heterogeneity and multiphase flow during TLF,the modified Boltzmann variable allows the conversion of three partial differential equations(PDE's)(i.e.,oil,gas and water diffusion equations)into ordinary differential equations(ODE's)that are easily solved using the Runge-Kutta(RK)method.A modified time-power-law plot is also proposed to estimate the reservoir and fracture properties,recognizing that the classical square-root-of-time-plot is no longer valid when various reservoir complexities are exhibited simultaneously.Using the slope of the straight line on the modified time-power-law plot,the linear flow parameter can be estimated with more confidence.Moreover,because of the new Boltzmann-type transformation,reservoir and fracture properties can be derived more efficiently without the need for defining complex pseudo-variable transformations.Using the new semi-analytical model,the effects of multiphase flow,reservoir heterogeneity and anomalous diffusion on rate-decline behavior are evaluated.For the case of approximately constant flowing pressure,multiphase flow impacts initial oil rate,which is a function of oil relative permeability and well flowing pressure.However,multiphase flow has a minor effect on the oil production decline exponent.Reservoir heterogeneity/anomalous diffusion affect both the initial oil production rate and production decline exponent.The production decline exponent constant is a function of reservoir heterogeneity/anomalous diffusion only.The practical significance of this work is the advancement of RTA techniques to allow for more complex reservoir scenarios,leading to more accurate production forecasting and better-informed capital planning.

Heterogeneity and Secondary Structure Analysis of 3' Untranslated Region in Classical Swine Fever Viruses

The attenuated vaccine strains of CSFV have a 12-nucleotides （nt） insertion in the 3＇-UTR of genome as compared to that of CSFV virulent strains. In this study, we found a distinct heterogeneity in the 3＇-UTR of attenuated Thiverval and HCLV strains. The longest 3＇-UTR of Thiverval strain was 259 base pairs （bp） with a 32-nt insertion, the shortest 3＇-UTR had only 233 bp with a 6-nt insertion. The longest 3＇-UTR of HCLV strain was 244 bp with a 17-nt insertion and the shortest 3＇ UTR was 235 bp with a 8-nt insertion. Compared with the published sequences of 3＇-UTR of vaccine and virulent strains, the 3＇-UTR of CSFV vaccine strains have two variable regions where insertion among the different vaccine strains were frequently found. The first is located between the second conservative TALk codon and the start of T-rich region where we found the variable length insertion in the same vaccine strain Thiveral or HCLV and the second is located between the end of T-rich region and the front of GAA eodon, however, a 4-nt deletion was found in this region in the virulent Shimen strain. These two regions may represent the ＂hot spot＂ for mutation. Modeling the secondary structures of the 3＇-UTR suggests that the T-rich insertion could result in the change of structure and free energy, thus affecting the stability of the 3＇-UTR structure. These findings will help to understand the mechanism of attenuated vaccines and improve vaccine safety, stability, and efficacy.

Effects of Normalized Difference Vegetation Index and Related Wavebands′ Characteristics on Detecting Spatial Heterogeneity Using Variogram-based Analysis

Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables. How these variables affect their corresponding spatial heterogeneities, however, have received little attention. In this paper, we examined the effects of characteristics of normalized difference vegetation index （NDVI） and its related bands variable images, namely red and near infrared （NIR）, on their corresponding spatial heterogeneity detection based on variogram models. In a coastal wetland region, two groups of study sites with distinct fractal vegetation cover were tested and analyzed. The results show that： l） in high fractal vegetation cover （H-FVC） area, NDV! and NIR variables display a similar ability in detecting the spatial he- terogeneity caused by vegetation growing status structure; 2） in low fractal vegetation cover （L-FVC） area, the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3） generally, NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers. Moreover, as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account, the proposed variogram analysis method can make the variable selection objectively and scientifically, especially in studies related to spatial heterogeneity using remotely sensed data.

Single-cell analysis of cellular heterogeneity and interactions in the ischemia-reperfusion injured mouse intestine

Nine major cell populations among 46,716 cells were identified in mouse intestinal ischemia‒reperfusion(II/R)injury by single-cell RNA sequencing.For enterocyte cells,11 subclusters were found,in which enterocyte cluster 1(EC1),enterocyte cluster 3(EC3),and enterocyte cluster 8(EC8)were newly discovered cells in ischemia 45 min/reperfusion 720 min(I 45 min/R 720 min)group.EC1 and EC3 played roles in digestion and absorption,and EC8 played a role in cell junctions.For TA cells,after ischemia 45 min/reperfusion 90 min(I 45 min/R 90 min),many TA cells at the stage of proliferation were identified.For Paneth cells,Paneth cluster 3 was observed in the resting state of normal jejunum.After I 45 min/R 90 min,three new subsets were found,in which Paneth cluster 1 had good antigen presentation activity.The main functions of goblet cells were to synthesize and secrete mucus,and a novel subcluster(goblet cluster 5)with highly proliferative ability was discovered in I 45 min/R 90 min group.As a major part of immune system,the changes in T cells with important roles were clarified.Notably,enterocyte cells secreted Guca2b to interact with Gucy2c receptor on the membranes of stem cells,TA cells,Paneth cells,and goblet cells to elicit intercellular communication.One marker known as glutathione S-transferase mu 3(GSTM3)affected intestinal mucosal barrier function by adjusting mitogen-activated protein kinases(MAPK)signaling during II/R injury.The data on the heterogeneity of intestinal cells,cellular communication and the mechanism of GSTM3 provide a cellular basis for treating II/R injury.

Insight into the spoilage heterogeneity of meat-borne bacteria isolates with high-producing collagenase

Chilled chicken is inevitably contaminated by microorganisms during slaughtering and processing,resulting in spoilage.Cutting parts of chilled chicken,especially wings,feet,and other skin-on products,are abundant in collagen,which may be the primary target for degradation by spoilage microorganisms.In this work,a total of 17 isolates of spoilage bacteria that could secrete both collagenase and lipase were determined by raw-chicken juice agar(RJA)method,and the results showed that 7 strains of Serratia,Aeromonas,and Pseudomonas could significantly decompose the collagen ingredients.The gelatin zymography showed that Serratia liquefaciens(F5)and(G7)had apparent degradation bands around 50 kDa,and Aeromonas veronii(G8)and Aeromonas salmonicida(H8)had a band around.65 and 95 kDa,respectively.The lipase and collagenase activities were detected isolate-by-isolate,with F5 showing the highest collagenase activity.For spoilage ability on meat in situ,F5 performed strongest in spoilage ability,indicated by the total viable counts,total volatile basic nitrogen content,sensory scores,lipase,and collagenase activity.This study provides a theoretical basis for spoilage heterogeneity of strains with high-producing collagenase in meat.

Spatial Heterogeneity Analysis of PM2.5 Concentration in Central Plains Economic Region

The research of the spatial heterogeneity of PM2.5 concentration in an area, is of great significance for understanding its regional spatial distribution structure, exploring the transmission relationship between regions, in order to formulate joint prevention and control measures within the entire area. Based on the daily monitoring data of PM2.5 concentration in the Central Plains Economic Region in 2019, this paper utilizes cluster analysis to divide the regional PM2.5 concentration into 5 classes, builds their spatial semi-variogram model, and then utilizes interpolation analysis method to study the regional overall distribution characteristics and transmission law. The results show that the PM2.5 concentration in the Central Plains Economic Region has a medium or higher spatial autocorrelation. The critical value of the overall PM2.5 concentration in the area is 150 μg/m3, as the overall PM2.5 concentration less than the value, the PM2.5 in a region mainly comes from local emissions, as the overall PM2.5 concentration higher than the value, the influence of spatial structure on the distribution of PM2.5 concentration is gradually obvious. PM2.5 has a certain degree of spatial transmission, which mainly includes two routes as Puyang-Xingtai and Puyang-Zhengzhou, and the transmission intensity of the former is greater than the latter.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China:a network analysis

Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.

Spatial Heterogeneity and Risk Factors of Dental Caries in 12-Year-Old Children in Shanxi Province,China

Objective This study aimed to explore the spatial heterogeneity and risk factors for dental caries in 12-year-old children in Shanxi province,China.Methods The data encompassed 3,721 participants from the two most recent oral health surveys conducted across 16 districts in Shanxi Province in 2015 and 2018.Eighteen specific variables were analyzed to examine the interplay between socioeconomic factors,medical resources and environmental conditions.The Geo-detector model was employed to assess the impacts and interactions of these ecological factors.Results Socioeconomic factors(Q=0.30,P<0.05)exhibited a more substantial impact compared to environmental(Q=0.19,P<0.05)and medical resource factors(Q=0.25,P<0.05).Notably,the urban population percentage(UPP)demonstrated the most significant explanatory power for the spatial heterogeneity in caries prevalence,as denoted by its highest q-value(q=0.51,P<0.05).Additionally,the spatial distribution’s heterogeneity of caries was significantly affected by SO2 concentration(q=0.39,P<0.05)and water fluoride levels(q=0.27,P<0.05)among environmental factors.Conclusion The prevalence of caries exhibited spatial heterogeneity,escalating from North to South in Shanxi Province,China,influenced by socioeconomic factors,medical resources,and environmental conditions to varying extents.

Advances in microfluidic-based DNA methylation analysis

DNA methylation has been extensively investigated in recent years,not least because of its known relationship with various diseases.Progress in analytical methods can greatly increase the relevance of DNA methylation studies to both clinical medicine and scientific research.Microflu-idic chips are excellent carriers for molecular analysis,and their use can provide improvements from multiple aspects.On-chip molecular analysis has received extensive attention owing to its advantages of portability,high throughput,low cost,and high efficiency.In recent years,the use of novel microfluidic chips for DNA methylation analysis has been widely reported and has shown obvious superiority to conventional methods.In this review,wefirst focus on DNA methylation and its applications.Then,we discuss advanced microfluidic-based methods for DNA methylation analysis and describe the great progress that has been made in recent years.Finally,we summarize the advantages that microfluidic technology brings to DNA methylation analysis and describe several challenges and perspectives for on-chip DNA methylation analysis.This review should help researchers improve their understanding and make progress in developing microfluidic-based methods for DNA methylation analysis.