Objective·To investigate the differential gene expression of microglia in the gray and white matter of multiple sclerosis(MS)using single-nucleus transcriptomic analysis,aiming to explore their roles in disease progression,and identify key transcriptional regulatory networks associated with the disease.Methods·snRNA-seq data of frozen human brain tissue samples from MS patients and control individuals were obtained from the Gene Expression Omnibus(GEO)database.R language,along with R packages such as Seurat,was employed to identify cell types based on specific cell markers.Microglia were extracted from the identified cell populations and classified based on their anatomical origin,either gray matter or white matter.Dimensionality reduction and clustering techniques were utilized to identify distinct microglial subpopulations with differential characteristics.Differentially expressed genes(DEGs)between the MS and control groups at the subpopulation level were analyzed by using the Seurat package.Gene set enrichment analysis of Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)was conducted on the DEGs to further explore the biological significance of these differences.Monocle3 was used for pseudotime analysis to study dynamic changes in microglia subpopulations during disease progression.Single cell regulatory network inference and clustering(SCENIC)method was applied to analyze transcription factor(TF)regulatory networks,aiming to identify key transcription factors potentially involved in MS regulation.Results·After quality control,a total of 149 062 nuclei were retained for analysis.Following dimensional reduction and clustering,12 238 microglia were identified by using key markers,including DOCK8,CSF1R,P2RY12,and CD74.The results of GO and KEGG pathway analysis showed that in gray matter microglia,functions such as endocytosis,ion homeostasis,and lipid localization were downregulated during disease progression,while in white matter microglia,functions such as protein folding,cytoplasmic translation,and response to thermal stimuli were upregulated.SCENIC analysis revealed that the expression of transcription factors such as FLI1,MITF,and FOXP1 was upregulated in MS.Conclusion·Microglia play a critical role in MS,with white matter microglia being more significantly impacted by MS than their gray matter counterparts.Transcription factors such as FLI1,MITF,and FOXP1 are identified as key regulators involved in disease modulation,with their associated transcriptional regulatory networks playing a central role in disease modulation.

Objective·To investigate the differential gene expression of microglia in the gray and white matter of multiple sclerosis(MS)using single-nucleus transcriptomic analysis,aiming to explore their roles in disease progression,and identify key transcriptional regulatory networks associated with the disease.Methods·snRNA-seq data of frozen human brain tissue samples from MS patients and control individuals were obtained from the Gene Expression Omnibus(GEO)database.R language,along with R packages such as Seurat,was employed to identify cell types based on specific cell markers.Microglia were extracted from the identified cell populations and classified based on their anatomical origin,either gray matter or white matter.Dimensionality reduction and clustering techniques were utilized to identify distinct microglial subpopulations with differential characteristics.Differentially expressed genes(DEGs)between the MS and control groups at the subpopulation level were analyzed by using the Seurat package.Gene set enrichment analysis of Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)was conducted on the DEGs to further explore the biological significance of these differences.Monocle3 was used for pseudotime analysis to study dynamic changes in microglia subpopulations during disease progression.Single cell regulatory network inference and clustering(SCENIC)method was applied to analyze transcription factor(TF)regulatory networks,aiming to identify key transcription factors potentially involved in MS regulation.Results·After quality control,a total of 149 062 nuclei were retained for analysis.Following dimensional reduction and clustering,12 238 microglia were identified by using key markers,including DOCK8,CSF1R,P2RY12,and CD74.The results of GO and KEGG pathway analysis showed that in gray matter microglia,functions such as endocytosis,ion homeostasis,and lipid localization were downregulated during disease progression,while in white matter microglia,functions such as protein folding,cytoplasmic translation,and response to thermal stimuli were upregulated.SCENIC analysis revealed that the expression of transcription factors such as FLI1,MITF,and FOXP1 was upregulated in MS.Conclusion·Microglia play a critical role in MS,with white matter microglia being more significantly impacted by MS than their gray matter counterparts.Transcription factors such as FLI1,MITF,and FOXP1 are identified as key regulators involved in disease modulation,with their associated transcriptional regulatory networks playing a central role in disease modulation.

Objective To compare the pain management effects between painless wards with quality control circle mode and conventional pain management mode.Methods A retrospective case control study was conducted on the clinical data of 233 patients with lower limb fracture admitted from August 2015 to August 2016.There were 124 males and 109 females,aged 18-74 years [(48.3 ±3.3)years].The patients were divided into observation group (n =117) and control group (n =116) according to the pain management mode.The observation group followed the standard continuous quality improvement program and combined with professional team and patients Wechat group to implement pain management,and further measures were taken in accordance with the feedbacks.The control group adopted routine painless ward nursing model for perioperative analgesia nursing intervention.The pain score VAS,the start time of functional exercise,the compliance of rehabilitation activities,the length of hospital stay,and the healing time of fracture were compared between the two groups.Results There was no significant difference in VAS scores between the two groups at 12 hours before operation and 6 hours after operation (P ＞ 0.05).The observation group had lower VAS scores at 12 hours (3.2± 1.4),24 hours (2.8 ±0.9),48 hours (1.6 ± 0.7),and 72 hours (1.5 ± 0.8) after operation than the control group (P ＜0.05).The observation group started functional exercises earlier [(18.9 ± 0.4) hours after operation]than the control group earlier [(48.1 ± 1.7) hours after operation] (P ＜ 0.01).The observation group had a rehabilitation compliance rate of 62.6％,higher than that of the control group (17.6％) (P ＜0.05).The hospital stay [(12.18 ± 0.14) days] and fracture healing time [(97.86 ± 0.83) days] of the observation group were shorter than those of the control group (P ＜ 0.05).Conclusion The pain management model of standardized continuous quality improvement can significantly relieve pain in patients with lower limb fracture,shorten hospitalization time,bring forward the start time of functional exercise,improve the compliance of rehabilitation activities,and promote fracture healing.

ObjectTo develop the reliable RP-HPLC methods for the determination of salidroside, tyrosol, rosavin, rosin, and rosarin in the plants of Rhodiola L. and to evaluate their species from different habitats. Methods Method Ⅰ: methanol-water (0.5 mmol/L SDS in 1% acetic acid aqueous solution) system for the analysis of salidroside; method Ⅱ: acetonitrile-water system for rosavin; method Ⅲ: aqueous acetonitrile-phosphoric gradient system for salidroside, tyrosol, rosavin, rosin, and rosarin. Results The contents of salidroside in different species range from 0.021% to 1.420%, and those of rosavin in all species are very limited or undetected except in Rhodiola rosea L. and R. sachalinensis. The contents of the five marker ingredients are significantly species- and habitat-dependent. Conclusion Three RP-HPLC methods are established for quantitative analysis of the above five marker ingredients in the meantime, respectively. Evaluation of the quality of varied species of Rhodiola L. shows that R. rosea growing in Xinjiang Uygur Autonomous Region and R. sachalinensis growing in Jilin province are the two better species contained with abundant above-mentioned ingredients in China.