Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Objective:To characterize the epidemiology, antimicrobial susceptibility, and molecular mechanisms of carbapenem-resistant Enterobacterales (CRE) carrying multiple carbapenemase genes in China, and to provide evidence for infection control and antibiotic stewardship.Methods:From 2016 to 2023, 115 CRE isolates harboring at least two carbapenemase genes were collected from 41 hospitals in 18 provinces across China. Species identification, antimicrobial susceptibility testing, and whole-genome sequencing were performed. Multilocus sequence typing (MLST) and capsular typing were conducted using Kleborate, plasmid replicon types were identified with PlasmidFinder, and a core genome phylogenetic tree was constructed.Results:The majority of isolates belonged to Klebsiella spp. (80.0%, 92/115), followed by E. cloacae (8.7%, 10/115) and E. coli (6.1%, 7/115). The isolates were mainly from Hebei, Beijing, Shandong, and Hunan (60.9%, 70/115), and sputum was the predominant specimen (43.5%, 50/115). The most common genotype was bla KPC+bla NDM (73.0%, 84/115), primarily in Klebsiella spp. (79.8%, 67/84), followed by bla NDM+bla IMP (15.7%, 18/115). The prevalent plasmid replicon types were IncFII (77.5%, 86/111), IncFIB (68.5%, 76/111), IncR (51.4%, 57/111), and IncX3 (20.7%, 23/111). Notably, 88.6% (31/35) of ST11-KL64 K. pneumoniae strains co-harbored IncFII, IncFIB, and IncR plasmids simultaneously. Between 2016 and 2022, the dominant subtype among Klebsiella spp. isolates was bla KPC-2+bla NDM-1 (56.2%, 36/64). In 2023, the bla KPC-2+bla NDM-13 subtype (29.5%, 19/64) emerged and exhibited clonal transmission (single nucleotide polymorphism 2?74 bp) in Hebei, Beijing, and Jilin. Susceptibility testing showed widespread resistance to β-lactams (90.2%-100%). Aztreonam-avibactam, tigecycline, and colistin retained high activity, with susceptibility rates of 90.16%-98.36%. Conclusions:In China, the majority of clinical Enterobacteriaceae strains that harbor multiple carbapenemases are Klebsiella spp. co-producing KPC and NDM enzymes. Dissemination is driven by both clonal expansion of ST11-KL64 and horizontal transfer of IncFII, IncFIB, and IncR plasmids. The recent emergence and regional clonal spread of the bla KPC-2+bla NDM-13 genotype underscore the urgent need for strengthened surveillance and containment measures.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

Cancer is the main cause of death,and drug therapy has greatly improved the effectiveness of anti-tumor treatment.However,there are problems such as high adverse reactions and the risk of developing drug resistance after long-term use.There is an urgent need to seek new drug targets.Human antigen R(HuR),as an RNA binding protein,promotes the whole process of tumor occurrence,development and metastasis through post transcriptional regulation of mRNA stability,and HuR is general-ly highly expressed in tumor tissue,making it a new target for an-ti-tumor therapy and a standard for prognosis evaluation.Tradi-tional Chinese medicine formulas and their various chemical components can inhibit tumor proliferation,induce tumor cell ap-optosis,inhibit angiogenesis,suppress immune escape,and re-verse tumor drug resistance by regulating HuR activity.This re-view summarizes the importance of HuR in regulation of tumor progression,as well as analyzes the mechanisms of the antitumor effects through active ingredients of Chinese medicine with the regulation of HuR.It is expected to provide new ideas for tumor therapy and guidance for the development of HuR-targeted anti-tumor drugs.

Objective:To explore the moderating and mediating roles of psychological resilience in the relationship between job satisfaction and depressive symptoms among petrochemical workers.Methods:In April 2022, a cluster sampling method was used to conduct a questionnaire survey among 1087 in-service employees of a petrochemical enterprise in Henan Province. A total of 861 questionnaires were recovered, including 857 valid ones, with an effective rate of 99.54%. Data on job satisfaction, psychological resilience, and depressive symptoms were collected using the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), Job Satisfaction Questionnaire, and Patient Health Questionnaire-9 (PHQ-9). Spearman rank correlation analysis was applied to analyze the relationships among the scores of job satisfaction, psychological resilience, and depressive symptoms. Hierarchical linear regression analysis was used to test the moderating effect of psychological resilience, and the Bootstrap method was employed to verify the mediating effect of psychological resilience.Results:The scores of job satisfaction, psychological resilience, and depressive symptoms among petrochemical workers were 36.00 (31.00, 36.00) points, 36.00 (30.00, 41.00) points, and 7.00 (3.00, 9.00) points. The detection rate of depressive symptoms was 65.7% (563/857). Results of Spearman rank correlation analysis showed that job satisfaction of petrochemical workers was positively correlated with psychological resilience ( rs=0.270, P<0.01) and negatively correlated with depressive symptoms ( rs=-0.386, P<0.01), psychological resilience was negatively correlated with depressive symptoms ( rs=-0.515, P<0.01). Results of hierarchical linear regression analysis indicated that psychological resilience had no moderating effect on the relationship between job satisfaction and depressive symptoms of petrochemical workers ( b=0.001, P>0.05). Results of the mediating effect test showed that psychological resilience played a partial mediating effect in the relationship between job satisfaction and depressive symptoms ( P<0.01), with a mediating effect value of -0.071 (95% CI: -0.125, -0.045), accounting for 20.16% of the total effect. Conclusion:Psychological resilience exerts a partial mediating effect rather than a moderating effect in the relationship between job satisfaction and depressive symptoms among petrochemical workers.

Objective:To evaluate the epidemiological protective effect of a booster dose of acellular DTP vaccine (DTaP) against pertussis in 6-year-old children.Methods:A retrospective cohort study was conducted to compare the incidence of pertussis in 6-year-old children who received DTaP versus DT vaccine boosters in 2023 over a two-year period from May 2023 to May 2025. The protective effect of the fifth dose of DTaP against pertussis in 6-year-old children was evaluated.Results:A total of 960 participants were enrolled in this study, including 480 children in the experimental group who received the fifth dose of DTaP vaccine and 480 children in the control group who received the DT vaccine booster. Baseline characteristics were balanced between the two groups. There were six confirmed cases of pertussis in the experimental group, with a reported incidence rate of 1.25%. In the control group, 14 pertussis cases were reported, with a reported incidence rate of 2.92%. The protective effectiveness(VE) of the DTaP vaccine against pertussis was 57.14% (95% CI:-10.59%-83.39%). For 6-year-old children who completed the booster immunization, the incidence data of pertussis were collected from the 14 th day after vaccination (i.e., the study day 0). Based on the annual cumulative incidence rate, the VE of DTaP against pertussis at 6, 12, 18, and 24 months after vaccination was 100%, 63.80% (95% CI:-14.49%-88.55%), 64.59% (95% CI: 1.17%-87.31%), and 57.60% (95% CI:-10.80%-83.78%), respectively. In the DTaP group, the annual cumulative incidence rate of 12 to 24 months did not show a significant upward or downward trend ( Z=-0.995, P=0.320). Conclusion:Boosting 6-year-old children with the DTaP vaccine provides measurable protection against pertussis. The protective efficacy is significant in the early stage (0 to 6 months) after vaccination, and it still remains effective at 12 to 24 months.