Objective:To explore the RNA expression and alterations in brain structure in individuals who have experienced stressful life events (SLE), as well as the correlation patterns between them and their association with the occurrence of depression.Methods:Prospectively, a total of 80 SLE subjects were recruited from the psychiatry and psychology clinic of the Jiangsu University Affiliated Yixing Hospital between January 2021 and December 2022, with 16 normal controls (NC) enrolled concurrently. The 17 items Hamilton depression scale (HAMD-17) and social readjustment rating scale (SRRS) were used to assess depressive symptoms and stress levels. RNA sequencing information of peripheral blood and imaging data at baseline were collected. Based on whether depression occurred during the 2-year follow-up period, SLE subjects were divided into the SLE-depression group ( n=15) and the SLE-non-depression group ( n=65). Differentially expressed genes (DEGs) were screened using differential analysis and protein-protein interaction (PPI) networks. Fractional anisotropy (FA) of white matter tracts and gray matter volume (GMV) were extracted using tract-based spatial statistics and voxel-based morphometry.Using analysis of variance compared inter-group differences in gene expression, GMV and white matter FA values. Partial correlation analysis was used to explore correlations between DEGs, altered GMV and white matter microstructure. Gene set enrichment analysis (GSEA) was performed on key genes to identify potential biological pathways. Propensity score matching constructed sensitivity subgroups to verify result robustness. Results:The SLE-depression group showed significantly higher SRRS and HAMD-17 scores at baseline and at the end of follow-up compared to the SLE-non-depression group and the NC group ( H=47.773, 35.427, 41.114, all P<0.05). Expression levels of IL-10 (2.12±0.28, 2.43±0.44), EZH2 (2.11±0.43, 2.45±0.51), NCAM1 (3.60±0.30, 3.03±0.39), CD3E (4.95±0.37, 4.57±0.48), CCK (3.29±0.28, 3.02±0.42), and CX3CR1 (5.55±0.40, 5.91±0.34) were significantly different between the SLE-depression group and SLE-non-depression group( F=5.549~28.371, all P<0.05). Compared with the SLE-non-depression group, the SLE-depression group exhibited significantly lower FA values in the genu of the corpus callosum (0.29±0.04, 0.31±0.04) and the left uncinate fasciculus (0.31±0.02, 0.33±0.02), as well as significantly smaller GMV in the right hippocampus (0.29±0.07, 0.33±0.06), bilateral middle frontal gyrus (left: 0.27±0.05, 0.31±0.05; right: 0.28±0.06, 0.32±0.06), right insula (0.36±0.03, 0.38±0.04), and left precentral gyrus (0.19±0.04, 0.24±0.05) ( F=4.593-12.064, all P<0.05, FDR correction). GMV in the right anterior cingulate and paracingulate gyri was significantly larger than that in the SLE-non-depression group (0.34±0.05, 0.29±0.06) ( F=6.704, P=0.034, FDR correction). Partial correlation analysis revealed significantly stronger correlations between hub DEGs and altered brain regions in the SLE-depression group ( r=0.017-0.801) compared to the SLE-non-depression group ( r=0.002-0.382), with a statistically significant difference ( U=629, P<0.001; Cliff's Delta=0.454). GSEA indicated that the aforementioned genes were primarily involved in pathways including the ribosome, spliceosome, ribosome biogenesis in eukaryotes, and neuroactive ligand-receptor interaction. Sensitivity analysis confirmed that the above results remained statistically significant after balancing sample sizes (all P<0.05). Conclusion:The SLE-depression group showed specific RNA expression and brain structure alterations compared to the SLE-non-depression group, and the correlation between RNA and brain structure was significantly enhanced in the SLE-depression group. This suggests that the correlation between genes and brain structure in the SLE population may be related to their susceptibility to depression.

Objective:To explore the RNA expression and alterations in brain structure in individuals who have experienced stressful life events (SLE), as well as the correlation patterns between them and their association with the occurrence of depression.Methods:Prospectively, a total of 80 SLE subjects were recruited from the psychiatry and psychology clinic of the Jiangsu University Affiliated Yixing Hospital between January 2021 and December 2022, with 16 normal controls (NC) enrolled concurrently. The 17 items Hamilton depression scale (HAMD-17) and social readjustment rating scale (SRRS) were used to assess depressive symptoms and stress levels. RNA sequencing information of peripheral blood and imaging data at baseline were collected. Based on whether depression occurred during the 2-year follow-up period, SLE subjects were divided into the SLE-depression group ( n=15) and the SLE-non-depression group ( n=65). Differentially expressed genes (DEGs) were screened using differential analysis and protein-protein interaction (PPI) networks. Fractional anisotropy (FA) of white matter tracts and gray matter volume (GMV) were extracted using tract-based spatial statistics and voxel-based morphometry.Using analysis of variance compared inter-group differences in gene expression, GMV and white matter FA values. Partial correlation analysis was used to explore correlations between DEGs, altered GMV and white matter microstructure. Gene set enrichment analysis (GSEA) was performed on key genes to identify potential biological pathways. Propensity score matching constructed sensitivity subgroups to verify result robustness. Results:The SLE-depression group showed significantly higher SRRS and HAMD-17 scores at baseline and at the end of follow-up compared to the SLE-non-depression group and the NC group ( H=47.773, 35.427, 41.114, all P<0.05). Expression levels of IL-10 (2.12±0.28, 2.43±0.44), EZH2 (2.11±0.43, 2.45±0.51), NCAM1 (3.60±0.30, 3.03±0.39), CD3E (4.95±0.37, 4.57±0.48), CCK (3.29±0.28, 3.02±0.42), and CX3CR1 (5.55±0.40, 5.91±0.34) were significantly different between the SLE-depression group and SLE-non-depression group( F=5.549~28.371, all P<0.05). Compared with the SLE-non-depression group, the SLE-depression group exhibited significantly lower FA values in the genu of the corpus callosum (0.29±0.04, 0.31±0.04) and the left uncinate fasciculus (0.31±0.02, 0.33±0.02), as well as significantly smaller GMV in the right hippocampus (0.29±0.07, 0.33±0.06), bilateral middle frontal gyrus (left: 0.27±0.05, 0.31±0.05; right: 0.28±0.06, 0.32±0.06), right insula (0.36±0.03, 0.38±0.04), and left precentral gyrus (0.19±0.04, 0.24±0.05) ( F=4.593-12.064, all P<0.05, FDR correction). GMV in the right anterior cingulate and paracingulate gyri was significantly larger than that in the SLE-non-depression group (0.34±0.05, 0.29±0.06) ( F=6.704, P=0.034, FDR correction). Partial correlation analysis revealed significantly stronger correlations between hub DEGs and altered brain regions in the SLE-depression group ( r=0.017-0.801) compared to the SLE-non-depression group ( r=0.002-0.382), with a statistically significant difference ( U=629, P<0.001; Cliff's Delta=0.454). GSEA indicated that the aforementioned genes were primarily involved in pathways including the ribosome, spliceosome, ribosome biogenesis in eukaryotes, and neuroactive ligand-receptor interaction. Sensitivity analysis confirmed that the above results remained statistically significant after balancing sample sizes (all P<0.05). Conclusion:The SLE-depression group showed specific RNA expression and brain structure alterations compared to the SLE-non-depression group, and the correlation between RNA and brain structure was significantly enhanced in the SLE-depression group. This suggests that the correlation between genes and brain structure in the SLE population may be related to their susceptibility to depression.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

Objective:To evaluate the accuracy of airborne pollen concentrations monitored by a novel volumetric suction pollen monitor.Methods:During the peak period of autumn pollen concentration in Beijing from September 1st to 27th, the pollen concentration was collected using gravitational and volumetric pollen monitor, and the correlation of pollen concentration between two kind of pollen monitor was analyzed. The effects of daily mean temperature, relative humidity and wind speed on the real-time pollen concentration of the volumetric suction pollen monitor were also analyzed. SPSS 25.0 software was used for statistical analysis.Results:There was significant correlation between the pollen concentration obtained by the two collectors ( r s value was 0.85 and 0.86, respectively, both P<0.001). Using a volumetric suction monitor, the pollen concentration in the horizontal 3 lines of the pollen sample (12.5%) under a 200×microscope was significantly correlated with the pollen concentration in the whole sample ( r s=0.97, P<0.001). The real-time pollen concentration collected by the volumetric suction monitor within 24 hours was greatly affected by the daily average temperature (all P<0.05), and the pollen concentration increased with the daytime temperature, which was not affected by the relative humidity and the average wind speed (all P>0.05). Conclusion:The airborne pollen concentration monitored by new volumetric pollen monitor has high accuracy and can accurately achieve real-time.

Objective:To establish graded forecast models of pollen concentration in spring and summer-autumn in northern China, based on long-term data of pollen and allergic rhinitis (AR) medical visits in 8 cities of northern China.Methods:Pollen concentration and the characteristics of AR patients from 8 cities of northern China, including Beijing, Baotou, Hohhot, Xi′an, Xining, Cangzhou, Liaocheng and Zibo, were analyzed. Spearman′s correlation was used to examine the relationship between pollen concentration and daily AR patient visits. A pollen concentration grading was establish, and a pollen forecast model was created using the eXtreme gradient boosting (XGBoost) algorithm. The model incorporated meteorological factors and the 3-day moving average of pollen concentrations.Results:The spring pollen period started early and lasted long in Beijing and Xi ′an, while the summer-autumn pollen period started earlier and persisted longer in Xining, Baotou and Hohhot. During summer-autumn pollen period, and the spring period in most cities (except Baotou and Cangzhou), average daily patient visits were significantly higher than those in non-pollen periods. A strong correlation was observed between daily AR patient visits and the 3-day moving average of pollen concentrations in both the spring and summer-autumn periods across all cities. Based on the correlation, a pollen concentration grading standard of northern China was established. The accuracy evaluation of pollen concentration prediction model showed that the percentage of forecasts with either completely accurate or within one level difference exceeded 91% in spring and 95% in summer-autumn. The most important predictive variable in the model was the pollen level from previous day, followed by the temperature and humidity.Conclusion:The grading prediction model for pollen concentration provides guidance for AR patients in term of travel, early defense and treatment, as well as the determining medication schedules for clinical drug research and specific immunotherapy.

Objective To analyze the composition characteristics and biological functions of tumor cell subpopulations in glioblastoma(GBM)through multi-transcriptomics sequencing technology,and explore the hypoxia characteristics and spatial localization features of the mesenchymal-like(MES-like)tumor cell subpopulation in GBM and the influence on malignant biological behaviors.Methods Multi-transcriptomics sequencing data,including single-cell RNA sequencing(scRNA-seq)data(18 patients),bulk RNA sequencing(bulk RNA-seq)and spatial transcriptomics(ST)data of GBM,were employed to define cell subpopulations in GBM,and Gene Ontology(GO)and Gene Set Enrichment Analysis(GSEA)were utilized to analyze their functions.The proportions and locations of cell subpopulations in bulk RNA-seq data were evaluated with BayesPrism deconvolution.Immunofluorescence assay was conducted for verification on 12 paraffin samples of GBM from patients who visited the neurosurgical department of our hospital from 2015 to 2023 and met the pathological diagnostic criteria for GBM(10 males and 2 females,at an average age of 53.50 years and a median age of 54.50 years).pySCENIC was applied to predict specific transcription factors of tumor cell subpopulations.Results Tumor cells in GBM were highly heterogeneous,and could be mainly divided into 4 subpopulations:astrocyte-like(AC-like),neural progenitor-like(NPC-like),oligodendrocyte progenitor-like(OPC-like)and MES-like.Differential gene analysis found that the MES-like tumor cells highly expressed vascular endothelial growth factor A(VEGFA),adrenomedullin(ADM),N-myc downstream regulated 1(NDRG1),insulin like growth factor binding protein 5(IGFBP5),and A-kinase anchoring protein 12(AKAP12)(P<0.001).pySCENIC transcription factor prediction found that the high-active transcription factors of the MES-like tumor cells were AT-rich interaction domain 3A(ARID3A),FOS like 2,AP-1 transcription factor subunit(FOSL2),endothelial PAS domain protein 1(EPAS1),CCAAT enhancer binding protein delta(CEBPD),and CCAAT enhancer binding protein beta(CEBPB)(P<0.05).GO and GSEA enrichment analyses found that the MES-like tumor cells were enriched in hypoxia-related pathways,especially the pathway of cell responses to hypoxia levels(NES=2.437,P<0.001).BayesPrism deconvolution showed that the MES-like tumor cells mainly existed in PAN(Pseudopalisading cells around necrosis)and perinecrotic zone.Immunofluorescence assay confirmed CD44+(CD44 antigen)MES-like tumor cells were mainly located in hypoxia areas with highly expression of hypoxia inducible factor 1 subunit alpha(HIF1α)(P<0.01).Multivariate Cox regression analysis indicated that the MES-like tumor cells were significantly correlated with the adverse prognosis of GBM patients(HR=1.71,95%CI:1.38～2.11,P<0.001).Conclusion Tumor cells in GBM are of highly heterogeneity.They could be mainly divided into 4 subpopulations:AC-like,NPC-like,OPC-like and MES-like.MES-like tumor cells,mainly locating in PAN and perinecrotic zone,are characterized by hypoxia,which can promote the malignant progression of GBM.

PURPOSE: To methodically assess the effectiveness of augmentative plating (AP) and exchange nailing (EN) in managing nonunion following intramedullary nailing for long bone fractures of the lower extremity. METHODS: PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to gather clinical studies regarding the use of AP and EN techniques in the treatment of nonunion following intramedullary nailing of lower extremity long bones. The search was conducted up until May 2023. The original studies underwent an independent assessment of their quality, a process conducted utilizing the Newcastle-Ottawa scale. Data were retrieved from these studies, and meta-analysis was executed utilizing Review Manager 5.3. RESULTS: This meta-analysis included 8 studies involving 661 participants, with 305 in the AP group and 356 in the EN group. The results of the meta-analysis demonstrated that the AP group exhibited a higher rate of union (odds ratio: 8.61, 95% confidence intervals (CI): 4.12 - 17.99, p < 0.001), shorter union time (standardized mean difference (SMD): -1.08, 95% CI: -1.79 - -0.37, p = 0.003), reduced duration of the surgical procedure (SMD: -0.56, 95% CI: -0.93 - -0.19, p = 0.003), less bleeding (SMD: -1.5, 95% CI: -2.81 - -0.18, p = 0.03), and a lower incidence of complications (relative risk: -0.17, 95% CI: -0.27 - -0.06, p = 0.001). In the subgroup analysis, the time for union in the AP group in nonisthmal and isthmal nonunion of lower extremity long bones was shorter compared to the EN group (nonisthmal SMD: -1.94, 95% CI: -3.28 - -0.61, p < 0.001; isthmal SMD: -1.08, 95% CI: -1.64 - -0.52, p = 0.002). CONCLUSION In the treatment of nonunion in diaphyseal fractures of the long bones in the lower extremity, the AP approach is superior to EN, both intraoperatively (with reduced duration of the surgical procedure and diminished blood loss) and postoperatively (with an elevated union rate, shorter union time, and lower incidence of complications). Specifically, in the management of nonunion of lower extremity long bones with non-isthmal and isthmal intramedullary nails, AP demonstrated shorter union time in comparison to EN.
Humans ; Bone Nails/adverse effects* ; Bone Plates/adverse effects* ; Femoral Fractures/surgery* ; Fracture Fixation, Intramedullary/methods* ; Fractures, Ununited/surgery* ; Lower Extremity/injuries*

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count