New insights into astrocyte diversity from the lens of transcriptional regulation and their implications for neurodegenerative disease treatments

Astrocytes are a major glial cell type in the central nervous system,and they provide trophic and metabolic support to neurons.In addition to these roles,they play crucial roles in modulating synaptic functions,development,and pruning(Brandebura et al.,2023).Astrocytes become reactive(activated)by undergoing morphological,molecular,and functional alterations in response to neuropathology such as in injuries and neurodegenerative diseases(NDs)(Escartin et al.,2021).

SMART/ASTC dynamic soft reduction technology and its application on the bloom continuous caster at Pangang

The SMART/ASTC dynamic soft reduction technology of VAI and its application on the 6-strand bloom continuous caster at Pangang, China are presented. The operation results show that soft reduction technology is effective to improve the inner quality of continuously cast blooms. At Pangang, both the central porosity and the central segregation ratings are no more than 1.0, the central shrinkage cavity rating is no more than 0.5, and the central segregation index of carbon is no more than 1.05. Rails made from the blooms have excellent quality and are used for high-speed tracks.

Hybrid stacking ensemble algorithm and simulated annealing optimization for stability evaluation of underground entry-type excavations

The stability of underground entry-type excavations(UETEs)is of paramount importance for ensuring the safety of mining operations.As more engineering cases are accumulated,machine learning(ML)has demonstrated great potential for the stability evaluation of UETEs.In this study,a hybrid stacking ensemble method aggregating support vector machine(SVM),k-nearest neighbor(KNN),decision tree(DT),random forest(RF),multilayer perceptron neural network(MLPNN)and extreme gradient boosting(XGBoost)algorithms was proposed to assess the stability of UETEs.Firstly,a total of 399 historical cases with two indicators were collected from seven mines.Subsequently,to pursue better evaluation performance,the hyperparameters of base learners(SVM,KNN,DT,RF,MLPNN and XGBoost)and meta learner(MLPNN)were tuned by combining a five-fold cross validation(CV)and simulated annealing(SA)approach.Based on the optimal hyperparameters configuration,the stacking ensemble models were constructed using the training set(75%of the data).Finally,the performance of the proposed approach was evaluated by two global metrics(accuracy and Cohen’s Kappa)and three within-class metrics(macro average of the precision,recall and F1-score)on the test set(25%of the data).In addition,the evaluation results were compared with six base learners optimized by SA.The hybrid stacking ensemble algorithm achieved better comprehensive performance with the accuracy,Kappa coefficient,macro average of the precision,recall and F1-score were 0.92,0.851,0.885,0.88 and 0.883,respectively.The rock mass rating(RMR)had the most important influence on evaluation results.Moreover,the critical span graph(CSG)was updated based on the proposed model,representing a significant improvement compared with the previous studies.This study can provide valuable guidance for stability analysis and risk management of UETEs.However,it is necessary to consider more indicators and collect more extensive and balanced dataset to validate the model in future.

Review and Evaluate the Bioinformatics Analysis Strategies of ATAC-seq and CUT&Tag Data

Efficient and reliable profiling methods are essential to study epigenetics.Tn5,one of the first identified prokaryotic transposases with high DNA-binding and tagmentation efficiency,is widely adopted in different genomic and epigenomic protocols for high-throughputly exploring the genome and epigenome.Based on Tn5,the Assay for Transposase-Accessible Chromatin using sequencing(ATAC-seq)and the Cleavage Under Targets and Tagmentation(CUT&Tag)were developed to measure chromatin accessibility and detect DNA–protein interactions.These methodologies can be applied to large amounts of biological samples with low-input levels,such as rare tissues,embryos,and sorted single cells.However,fast and proper processing of these epigenomic data has become a bottleneck because massive data production continues to increase quickly.Furthermore,inappropriate data analysis can generate biased or misleading conclusions.Therefore,it is essential to evaluate the performance of Tn5-based ATAC-seq and CUT&Tag data processing bioinformatics tools,many of which were developed mostly for analyzing chromatin immunoprecipitation followed by sequencing(ChIP-seq)data.Here,we conducted a comprehensive benchmarking analysis to evaluate the performance of eight popular software for processing ATAC-seq and CUT&Tag data.We compared the sensitivity,specificity,and peak width distribution for both narrow-type and broad-type peak calling.We also tested the influence of the availability of control IgG input in CUT&Tag data analysis.Finally,we evaluated the differential analysis strategies commonly used for analyzing the CUT&Tag data.Our study provided comprehensive guidance for selecting bioinformatics tools and recommended analysis strategies,which were implemented into Docker/Singularity images for streamlined data analysis.

Novel stacking models based on SMOTE for the prediction of rockburst grades at four deep gold mines

Rockburst is a frequently encountered hazard during the production of deep gold mines.Accurate prediction of rockburst is an important measure to prevent rockburst in gold mines.This study considers seven indicators to evaluate rockburst at four deep gold mines.Field research and rock tests were performed at two gold mines in China to collect these seven indicators and rockburst cases.The collected database was oversampled by the synthetic minority oversampling technique(SMOTE)to balance the categories of rockburst datasets.Stacking models combining tree-based models and logistic regression(LR)were established by the balanced database.Rockburst datasets from another two deep gold mines were implemented to verify the applicability of the predictive models.The stacking model combining extremely randomized trees and LR based on SMOTE(SMOTE-ERT-LR)was the best model,and it obtained a training accuracy of 100%and an evaluation accuracy of 100%.Moreover,model evaluation suggested that SMOTE can enhance the prediction performance for weak rockburst,thereby improving the overall performance.Finally,sensitivity analysis was performed for SMOTE-ERT-LR.The results indicated that the SMOTE-ERT-LR model can achieve satisfactory performance when only depth,maximum tangential stress index,and linear elastic energy index were available.

Effect of injection scheme on asymmetric phenomenon in rectangular and circular scramjets

The asymmetric separation has a crucial effect on the performance of the scramjet.In this study,the asymmetric separation and combustion in both rectangular and circular scramjets are investigated numerically,and the effect of injection scheme is analyzed.The characteristics of the flow field are analyzed based on sufficient code verification.In the rectangular scramjet,the separation tends to occur in the corner due to the corner boundary-layer effect.The separation is asym-metric and only two corners have serious separation.The fuel penetration depth in the separation zone increases and the combustion is intensified.When the injection scheme is uniform,both the combustion and separation become weak.In the circular scramjet,the separation and combustion are basically axisymmetric in the scramjet with one-row injection scheme.The asymmetric combustion becomes obvious in cases with multi-row injection scheme.When the injection orifices distribute intensively on the top and bottom sides,the strongest and weakest separations occur near these two sides respectively.When the distribution of orifices becomes uniform,the direction of separation cannot be predicted.For multi-row cases,the nonuniform injection scheme could result in violent combustion and asymmetric flow structures compared with the uniform injection scheme.

Mixing and combustion characteristics in a scramjet combustor with different distances between cavity and backward-facing step

The mixing and combustion characteristics in a cavity flameholding combustor under inlet Mach number 2.92 are numerically investigated with ethylene injection.Dimensionless distance is defined as the ratio of the actual distance to the height of the combustor entrance.The cavity shear-layer mode,the lifted cavity shear-layer mode,and jet wake mode with upstream separation are observed respectively with dimensionless distance equals to 1.5,4.5,and 7.5.In both non-reacting and reacting flow fields,the numerical results are essentially in agreement with the schlieren photography,flame chemiluminescence images,and wall pressure,which verify the reliability of the numerical method.The results of non-reacting flow fields show that the BackwardFacing Step(BFS)can promote the flow separation downstream at a fixed distance.The more forward the separation position is,the larger the separation zone is in the non-reacting flow field.Furthermore,the larger the separation zone is,the higher the intensity of combustion in the reacting flow field is.A reasonable distance can reduce the total pressure loss generated by the shock waves in the combustor.The flame presents remarkable three-dimensional characteristics in the reacting flow fields.When dimensionless distance equals to 4.5,there are flames near the side wall above the cavity and it is difficult for the flame stabilization in the center of the combustor,while the combustion intensity in the center of the combustor is higher than that near the side wall when dimensionless distance equals to 7.5.In the cavity flameholding combustors with a backward-facing step,the higher combustion intensity may bring much total pressure loss to the combustor.Thus,it is a good choice to achieve better thrust performance when dimensionless distance equals to 4.5 compared to the other two combustors.

Flamelet-like models applied in scramjet combustors:A state of art and prospect

Developing supersonic combustion models with efficiency,accuracy and practicality is important foundation to deeply understand the complex combustion processes in scramjet engines.Characterized by efficiency and intuition,the flamelet-like models are widely used models in computational combustion methods.However,the supersonic combustion flow field has the nature of strong compressibility,multiple modality,and multiple scales,which poses a great challenge to the traditional flamelet-like models with fixed boundary conditions,and then the complex chemical reaction mechanisms that may face will impose additional computational burden.In this context,this paper reviews the flamelet-like models used in scramjet engines,and summarizes prominent issues in the application practice,including modeling partially premixed combustion,defining progress variable,solving temperature efficiently,evaluating assumed Probability Density Function(PDF)models,and treating mixture fraction variance.Furthermore,possible prospects and directions of improvements are proposed and highlighted for the flamelet-like models.To fully describe the physicochemical scenario and address the raised challenges,these improvements are dedicated to dealing with the compressibility,temperature rise,time-scales,species of interest,multi-inlet combustion,the progress variable definition,and the higher Mach number flight condition.

A novel Lactococcus lactis L-arabinose isomerase for D-tagatose production from lactose

A new strain of Lactococcus lactis producing D-tagatose was isolated and identified.Its L-arabinose isomerase coding gene was cloned and expressed in Escherichia coli BL21(DE3).The optimal temperature and pH of the purified enzyme were 50◦C and 8.0.To produce D-tagatose from lactose,β-D-galactosidases from Lc.Lactis,Lactiplantibacillus plantarum,and Streptococcus thermophilus were further incorporated into E.coli by two strategies.Theseβ-D-galactosidases were fused to L-arabinose isomerase coupled with a peptide linker(GGGGS)3.Meanwhile,they were co-expressed with L-arabinose isomerase using pETDuet-1 vector.Among these recombinant strains,the cell co-expressing L-arabinose isomerase and S.thermophilusβ-D-galactosidase showed maximal activity.SDS-PAGE results confirmed that exogenous enzymes had the maximum soluble expression level in this strain.At the optimal condition,the conversion rate of D-tagatose from 300 g/L lactose achieved to 42.4%,and the volumetric productivity reached 4.28 g/L/h at 15 h.This research established a highly efficient biotransformation system to produce D-tagatose from lactose.