[摘 要] 目的：探讨间充质基质细胞来源细胞外囊泡（MSC-EV）对小鼠免疫检查点抑制剂相关肺炎（CIP）模型的改善作用及分子机制。方法：选取Foxp3DTR小鼠，皮下接种MC38小鼠结肠癌细胞，待肿瘤生长至可触及后，随机分为3组（每组n = 6）：①对照组；②CIP模型组[接种MC38细胞后腹腔注射白喉毒素（DT）及anti-PD-1抗体，构建Treg细胞耗竭联合anti-PD-1抗体诱导的小鼠CIP模型]；③MSC-EV干预组（CIP模型基础上，经鼻滴注MSC-EV干预，剂量109个/只，每3天1次，共2次）。体内实验采用H-E染色观察肺组织病理损伤，测定肺干湿比评估肺水肿程度，ELISA检测支气管肺泡灌洗液（BALF）中IL-1β、IL-6及TNF-α水平，流式细胞术检测BALF中Ly6G⁺粒细胞浸润比例，监测肿瘤体积评价抗肿瘤疗效。体外实验采用DiO荧光标记观察细胞外囊泡（EV）被骨髓来源巨噬细胞摄取的情况，WB法检测NOD样受体家族含Pyrin域蛋白3（NLRP3）炎症小体关键蛋白（剪切型GSDMD、成熟型IL-1β）的表达水平。结合GEO数据库miRNA测序数据（GSE69909）、Dicer敲低及miR-21/miR-125抑制剂干预揭示潜在机制。结果：MSC-EV经鼻滴注可减轻CIP模型小鼠肺部炎症损伤，降低BALF中IL-1β、IL-6、TNF-α水平及Ly6G⁺粒细胞浸润比例（P < 0.05），且不削弱anti-PD-1抗体的抗肿瘤疗效。体外DiO标记示踪显示MSC-EV可被巨噬细胞摄取，WB法检测结果显示，MSC-EV可降低NLRP3炎症小体关键活化蛋白（剪切型GSDMD、成熟型IL-1β）水平（P < 0.05）。体外实验中，Dicer敲低后制备的MSC-EV 对巨噬细胞IL-1β的下调作用减弱（P < 0.05）。miRNA测序显示miR-21、miR-125在MSC-EV中高表达，抑制miR-21或miR-125后，相应MSC-EV对巨噬细胞IL-1β剪切的抑制作用降低（P < 0.05）。结论：MSC-EV通过其携带的miR-21和miR-125等miRNA发挥抗炎效应，其机制可能与抑制巨噬细胞NLRP3炎症小体活化有关，可有效改善CIP且不影响免疫检查点抑制剂的抗肿瘤疗效。

Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

Background/Aims: Acetyl coenzyme A (acetyl-CoA) is one of the most essential metabolites in cell metabolism but its function and concentration in hepatocellular carcinoma (HCC) remain elusive and controversial. Methods: A comprehensive analysis of acetyl-CoA levels and acetyl-CoA synthetase 2 (ACSS2) expression across a range of samples, including patient specimens from both hepatitis B virus (HBV) positive and HBV negative HCC individuals, HBV-transgenic mouse HCC models, and multiple cell lines. Furthermore, to evaluate the functional significance of ACSS2 in HBV-related HCC, we implemented both genetic and pharmacological inhibition strategies targeting ACSS2. Molecular mechanism and mitophagy assessment were revealed by cleavage under target and tagmentation sequencing, RNA sequencing, bioinformatic analyses, transmission electron microscopy and JC-1 staining. Results: Our study revealed a distinct metabolic signature of HBV-related HCC, marked by elevated acetyl-CoA, which was driven by ACSS2. ACSS2 was upregulated by the carbohydrate response element-binding protein in HBV-related HCC. Furthermore, ACSS2 improved tumor cell proliferation, an effect that was dependent on its enzymatic activity. Mechanistically, ACSS2-induced acetyl-CoA accumulation activated voltage-dependent anion channels 1 transcription through increased H3K27ac occupancy, which subsequently promoted mitophagy and HBV-related HCC tumorigenesis. Notably, targeting ACSS2 by depletion or inhibition with a catalytic inhibitor significantly suppressed tumor growth. Conclusions These findings not only illustrate the interplay between metabolic reprogramming, epigenetic modification, and tumorigenesis in the context of HBV infection, but also highlight ACSS2 as a novel metabolic vulnerability in HBV-related HCC. Therefore, targeting ACSS2 could be a novel strategy against HBV-related HCC.

This study investigated the full-genome molecular characteristics of a rotavirus vaccine-derived strain,G1P[8]geno-type A group rotavirus RVA/Human-wt/CHN/HN1140/2021/G1P[8](referred to as HN1140).The gene fragments of the HN1140 strain were amplified with reverse transcription-polymerase chain reaction(RT-PCR)combined with whole-genome primers to obtain the full genome sequence.Genotyping was performed with the online genotyping tool RotaC 2.0,and similarity and genetic evolution analyses for each gene segment were conducted in DNAstar5.1 and MEGA11.0 software.The genotype of the HN1140 strain was deter-mined to be G1-P[8]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis demonstrated that all 11 genomic segments clus-tered closely with the RotaTeq vaccine strains,sharing 99.7%-100%nucleotide sequence similarity.Notably,VP1,VP2,VP6,and NSP2-NSP5 segments showed 100%nucleotide identity with RotaTeq strains.Comparative genomic analysis identified 13 nucleotide and 8 amino acid substitutions between HN1140 and RotaTeq strains,localized within the VP7,VP4,VP1,VP2,VP3,and NSP1 segments.The HN1140 strain exhibited the genotype G1-P[8]-A3-T6-H3,which was consistent with the typical profile of a vaccine-derived reassortant.This strain demonstrated high genetic similarity to RotaTeq vaccine strains,with nucleotide sequence identity ranging from 99.7%to 100%.These findings suggested that HN1140 evolved from RotaTeq vaccine strains through genetic reassortment.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Depression is a prevalent mental and emotional disor-der that often results in significant emotional disturbances,cog-nitive dysfunction,and memory impairments.It is characterized by a high incidence rate,a substantial disability burden,and limited therapeutic efficacy.Currently,the long-term use of medications for the treatment of depression can result in a range of adverse reactions,highlighting the urgent need to explore no-vel approaches that can effectively alleviate depressive symptoms while minimizing side effects.Curcumin,a natural polyphenolic compound derived from the rhizome of turmeric,demonstrates considerable potential in the prevention and treatment of depres-sion,owing to its diverse array of biological activities.In recent years,numerous studies have investigated the use of curcumin for the treatment of depression.This article aims to provide a comprehensive review of the mechanisms of action underlying curcumin's efficacy in treating depression.Specifically,it focu-ses on its ability to improve neurotransmitter imbalances,restore neural plasticity,alleviate neural damage,mitigate dysfunction of the hypothalamic-pituitary-adrenal(HPA)axis,regulate in-flammatory factors and neuroinflammatory signaling pathways,and inhibit oxidative stress.This review is intended to offer in-sights and methodological references for basic research on curcu-min,as well as for the development of novel therapeutic agents for the treatment of depression.

This study investigated the full-genome molecular characteristics of a rotavirus vaccine-derived strain,G1P[8]geno-type A group rotavirus RVA/Human-wt/CHN/HN1140/2021/G1P[8](referred to as HN1140).The gene fragments of the HN1140 strain were amplified with reverse transcription-polymerase chain reaction(RT-PCR)combined with whole-genome primers to obtain the full genome sequence.Genotyping was performed with the online genotyping tool RotaC 2.0,and similarity and genetic evolution analyses for each gene segment were conducted in DNAstar5.1 and MEGA11.0 software.The genotype of the HN1140 strain was deter-mined to be G1-P[8]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis demonstrated that all 11 genomic segments clus-tered closely with the RotaTeq vaccine strains,sharing 99.7%-100%nucleotide sequence similarity.Notably,VP1,VP2,VP6,and NSP2-NSP5 segments showed 100%nucleotide identity with RotaTeq strains.Comparative genomic analysis identified 13 nucleotide and 8 amino acid substitutions between HN1140 and RotaTeq strains,localized within the VP7,VP4,VP1,VP2,VP3,and NSP1 segments.The HN1140 strain exhibited the genotype G1-P[8]-A3-T6-H3,which was consistent with the typical profile of a vaccine-derived reassortant.This strain demonstrated high genetic similarity to RotaTeq vaccine strains,with nucleotide sequence identity ranging from 99.7%to 100%.These findings suggested that HN1140 evolved from RotaTeq vaccine strains through genetic reassortment.

Objective:To analyze the short-term hospital-based transmission characteristics and gene variation of Carbapenem-Resistant Klebsiella pneumoniae (CRKP) by genome-wide technique to provide evidence for transmission control. Methods:The experimental strain was derived from all the CRKP isolated in Affiliated Hospital of North China University of Science and Technology from October 2022 to December 2023. Strain identification and drug susceptibility were tested with VITEK 2-Compact automatic bacterial identification drug susceptibility analyzer or disk method, and the results were interpreted through whole genome sequencing. The ST type, carbapenem resistance gene, virulence factor, and O serotype of the collected strains were analyzed.Results:Among the 115 strains of CRKP, 94 strains were isolated from the intensive care unit (ICU), accounting for 81.7%, and 21 strains were isolated from the non-intensive care unit (NICU), accounting for 18.3%. The 115 strains of CRKP can be divided into 11 ST types, of which ST11 type was the most (54.8%, 63/115), followed by ST15 type (22.6%, 26/115) and ST5492 type (15.7%, 18/115). Type ST5492 was a new clonal group in the region. The 115 strains of CRKP could be divided into 7 O serotypes, most of which were O2a type(32.2%,37/115), followed by O5 type(30.4%,35/115) and O1 type(27.8%,32/115). The resistance genes of carbapenem antibiotics showed that there were 107 strains carrying the blaKPC-2 gene, one strain with the blaNDM-1 gene, and one strain with both the blaKPC-2 and blaNDM-13 genes. Virulence genes were detected in 55 CRKP strains (47.8%, 55/115), among which six strains detected peg-344, iucA, iroB, rmpA, and rmpA2 virulence genes (5.2%, 6/115). Four virulence genes ( peg-344, iucA, rmpA, and rmpA2) were detected in 34 strains (29.6%, 34/115). Three virulence genes ( iucA, iroB and rmpA) were detected in two strains (1.7%, 2/115). Three virulence genes ( peg-344, iucA and rmpA) were detected in one strain (0.8%, 1/115). IucA and rmpA virulence genes were detected in 12 strains (10.4%, 12/115). KPC-2_ST11_O2a, KPC-2_ST15_O1 and KPC-2_ST5492_O5 were dominant clones, and their distribution was mainly in the intensive care unit. The whole genome sequence analysis showed that there were three dominant clones, among which ST11 clones were subdivided into three dominant O serotypes, all of which were mainly in the intensive care unit. Conclusion:The popular strain in the hospital of CRKP is a KPC-2_ST11 clone group carrying iucA, rmpA/rmpA2, with cross-department transmission and mutation. ST5492 is a newly-launched clone type. The intensive care unit of hvKP carrying five virulence genes, including peg-344, should be alert to the epidemic risk of CR-hvKP outbreak.

Objective:It is of great significance to analyze the expression characteristics of immune-related genes in pancreatic cancer and their relationship with prognosis,construct and verify a reliable prognostic model,and explore prognostic methods of pancreatic cancer from the perspective of immune microenvironment.Methods:GSEA enrich-ment analysis of differentially expressed genes in pancreatic cancer was performed to identify key immune-related pathways and genes.The genes involved in the immune pathway were screened through the STRING database and combined with univariate Cox regression and LASSO regression analysis.Three key genes,RIPK2,IRAK2 and CXCL11,were finally identified to construct the prognostic model.The accuracy of the model was evaluated using ROC curves and calibration curves,and verified in an independent verification set(GSE57495).At the same time,the expression pat-terns of key genes in the immune microenvironment were analyzed by single-cell RNA sequencing,and the expression levels of these genes were verified in pancreatic cancer cell lines by RT-qPCR.Results:The expressions of RIPK2,IRAK2 and CXCL11 in pancreatic cancer cell lines were higher than those in normal pancreatic cancer cells(P<0.05).The model based on these three genes divided the patients into a high-risk group(n=87)and a low-risk group(n=89),and the difference in survival time between the high-risk group and the low-risk group was statistically significant(P<0.001).Risk score was correlated with G stage,N stage and tumor residue(P<0.01).Single-cell analysis showed that the ex-pression of these genes was highest in tumor-associated macrophages(mean>0.5)and correlated with regulatory T cells and macrophage infiltration(P<0.05).Multivariate analysis showed that risk score was correlated with overall sur-vival after adjusting for clinical factors(P=0.0014).Conclusion:Based on three key immune-related genes(RIPK2,IRAK2 and CXCL11),we successfully constructed a model to accurately predict the prognosis of pancreatic cancer pa-tients,revealing the important role of these genes in the tumor immune microenvironment,and providing new insights and theoretical basis for pancreatic cancer prognosis assessment and immunotherapy research.

Objective:It is of great significance to analyze the expression characteristics of immune-related genes in pancreatic cancer and their relationship with prognosis,construct and verify a reliable prognostic model,and explore prognostic methods of pancreatic cancer from the perspective of immune microenvironment.Methods:GSEA enrich-ment analysis of differentially expressed genes in pancreatic cancer was performed to identify key immune-related pathways and genes.The genes involved in the immune pathway were screened through the STRING database and combined with univariate Cox regression and LASSO regression analysis.Three key genes,RIPK2,IRAK2 and CXCL11,were finally identified to construct the prognostic model.The accuracy of the model was evaluated using ROC curves and calibration curves,and verified in an independent verification set(GSE57495).At the same time,the expression pat-terns of key genes in the immune microenvironment were analyzed by single-cell RNA sequencing,and the expression levels of these genes were verified in pancreatic cancer cell lines by RT-qPCR.Results:The expressions of RIPK2,IRAK2 and CXCL11 in pancreatic cancer cell lines were higher than those in normal pancreatic cancer cells(P<0.05).The model based on these three genes divided the patients into a high-risk group(n=87)and a low-risk group(n=89),and the difference in survival time between the high-risk group and the low-risk group was statistically significant(P<0.001).Risk score was correlated with G stage,N stage and tumor residue(P<0.01).Single-cell analysis showed that the ex-pression of these genes was highest in tumor-associated macrophages(mean>0.5)and correlated with regulatory T cells and macrophage infiltration(P<0.05).Multivariate analysis showed that risk score was correlated with overall sur-vival after adjusting for clinical factors(P=0.0014).Conclusion:Based on three key immune-related genes(RIPK2,IRAK2 and CXCL11),we successfully constructed a model to accurately predict the prognosis of pancreatic cancer pa-tients,revealing the important role of these genes in the tumor immune microenvironment,and providing new insights and theoretical basis for pancreatic cancer prognosis assessment and immunotherapy research.