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.

Objective:To explore the independent risk factors for uremic encephalopathy(UE)in maintenance hemodialysis(MHD)patients and provide evidence for early clinical warning and intervention.Methods:A case-control study was conducted,enrolling 67 MHD patients diagnosed with UE(UE group)at Laibin People's Hospital from January 2010 to December 2024,and 67 non-UE patients during the same period(control group).Demographic characteristics,dialysis parameters,laboratory indicators,and infection events were collected.Univariate and multivariate logistic regression analyses were used to identify independent risk factors for UE.Results:The UE group had significantly higher rates of infection(58.2％vs.29.9％),serum creatinine(789 vs.702 μmol/L),and iPTH levels(568 vs.385 pg/mL)compared to the control group(P＜0.05).Multivariate analysis revealed that concurrent infection(OR=3.022,95％CI:1.312-6.958),elevated serum creatinine(OR=1.004,95％CI:1.000-1.008),and elevated iPTH(OR=1.002,95％CI:1.001-1.003)were independent risk factors for UE(P＜0.05).The combined prediction model achieved an AUC of 0.878(95％CI:0.822-0.934),with 82.1％sensitivity and 80.6％specificity.Conclusion:Infection,elevated serum creatinine,and elevated iPTH significantly increase the risk of UE in MHD patients.Clinical management should emphasize infection prevention,toxin clearance optimization,and parathyroid function regulation to reduce UE incidence.

Fibroblast growth factor,as a critical protein regulating cell growth and differentiation,exhibits aberrant signaling closely associated with various pathological pathologies,including cancer.Among the members of the fibroblast growth factor family,fibroblast growth factor 9(FGF9)has been identified as a critical player in cancer initiation and progression.While numerous studies have investigated the molecular mechanisms of FGF9 individually,comprehensive reviews addressing its impact in cancer remain scarce.This article systematically reviews the functional mechanisms and regulatory networks of FGF9 in cancer,with a focus on its roles in common malignancies such as lung cancer,liver cancer,gastric cancer,colorectal cancer,breast cancer,and ovarian cancer.The aim is to facilitate translational research on FGF9 for targeted cancer diagnosis and therapy.

Objective To investigate the relationship between deep medullary vein(DMV)score and enlarged perivascular space(EPVS)score with cranial MRI to explore the mechanisms of EPVS occurrence and development.Methods Totally 118 patients with cerebral small vessel disease in some hospital had their clinical and imaging data analyzed retrospectively.On T2-weighted images,EPVS scores ranging from 0 to 4 were assigned to the basal ganglia and centrum semiovale regions based on the number of EPVS.For DMV scoring on magnetic susceptibility weighted images,the brain lobes were divided into six regions,including bilateral frontal,parietal and occipital lobes,and scored according to the significance and continuity of the DMV signals(0 to 3 points),and the scores of the regions were summed up as the total DMV score(0 to 18 points).Spearman correlation analysis was employed to investigate the correlation between DMV and EPVS scores.Kruskal-Wallis test was used to analyze the differences among groups with different EPVS scores.Additionally,multinomial ordinal regression analysis was conducted to explore the factors influencing EPVS.Results No significant correlation was found between EPVS scores in centrum semiovale and DMV scores(r2=0.015,P=0.191),while DMV scores and EPVS scores in basal ganglia showed a significant positive correlation(r2=0.558,P<0.000 1).Univariate analysis revealed statisti-cally significant differences in age,hypertension and DMV scores when different scoring groups of EPVS in the basal ganglia region were compared(P<0.05);multinomial ordinal regression analysis showed that age,hypertension and DMV scores were independently correlated with EPVS scores in the basal ganglia region.Conclusion There is a positive correlation between DMV scores and EPVS scores in the basal ganglia.Age,hypertension,and DMV score are independent influe-ncing factors for EPVS in the basal ganglia region.[Chinese Medical Equipment Journal,2025,46(4):52-56]

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 evaluate the effects of transcatheter aortic valve replacement(TAVR)on left ventricular reverse remodeling(LVRR)and outcomes in patients with mixed aortic valve disease(MAVD)and predominant aortic stenosis(AS).Methods Patients undergoing TAVR at our center between January 2020 and December 2022 were enrolled consecutively.Propensity score matching(PSM)(1∶1 ratio)was used to reduce selection bias.Transthoracic echocardiography(TTE)was used to monitor left ventricular ejection fraction(LVEF)and other structural parameters over time.The study outcome was a composite of cardiovascular death and rehospitalization due to cardiovascular causes.Linear mixed-effects models and logistic regression were utilized for comparing echocardiographic changes across groups and identifying independent risk factors for no-LVRR,respectively.Results After PSM,126 patients were included.MAVD group exhibited larger structural parameters(left ventricular end-systolic/end-diastolic diameter and volume,left ventricular mass index)and a lower left ventricular ejection fraction(LVEF)(all P＜0.05).However,more pronounced improvements in left ventricular structure and hemodynamics were observed during follow-up.Multivariate logistic regression analysis indicated that the left ventricular mass index(LVMI)was an independent predictor of left ventricular reverse remodeling(LVRR)after TAVR,whereas persistent moderate or greater mitral regurgitation(MR)and paravalvular leak(PVL)significantly reduced the incidence of LVRR.During a median follow-up period of 23 months,a total of 31 endpoint events occurred,and there was no statistically significant difference in long-term prognosis between the two groups(Log-rank P=0.330).Conclusions Compared to patients in the AS group,those in the MAVD group exhibited more severe left ventricular remodeling before TAVR.However,more significant LVRR was observed during postoperative follow-up.Additionally,the long-term prognosis was comparable between the two groups.

Objective:To investigate the impact of fibroblast growth factor(FGF)on recurrence following segmen-tal mastectomy in patients with plasma cell mastitis.Methods:A total of 162 female patients diagnosed with plasma cell mastitis(PCM)were selected from our hospital from October 2021 to May 2023.All patients underwent segmental mastectomy.They were divided into recurrence group(n=28)and non-recurrence group(n=134)according to the follow-up survey on recurrence.Conduct a univariate analysis on the factors influencing recurrence in patients with PCM who undergo segmental mastectomy.After correcting for confounding factors,conduct a multiple linear regression analysis.Using a multivariate logistic regression model to explore the independent risk factors for recurrence in patients undergo-ing segmental mastectomy for PCM.Utilizing logistic regression analysis to explore the independent,multiplicative,or additive interaction between FGF and angiogenic factor in the management of recurrence in PCM patients undergoing segmental mastectomy.The Local Weighted Regression Scatter Method(LOWESS)is used to analyze the two-dimensional curve relationship of continuous variables.Evaluate the predictive efficacy of FGF for PCM recurrence fol-lowing segmental mastectomy using Receiver Operating Characteristic(ROC)curves.Results:The results of univariate analysis showed that the body mass index(BMI),estradiol,prolactin levels,nipple depression,and sinus phase propor-tion of patients in the recurrent group were significantly higher than those in the non recurrent group,and the differ-ences were statistically significant(P＜0.05).Before surgery and 1 and 3 months after surgery,the levels of FGF,vascu-lar endothelial growth factor(VEGF),endostatin(ES),and VEGF/ES in the recurrent group were higher than those in the non recurrent group,with statistically significant differences between the groups(P＜0.05).The intra group comparison results showed that compared with before surgery,all indicators in both groups of patients were significantly reduced at 1 month after surgery(P＜0.05),while in the recurrent group,all indicators were significantly increased at 3 months after surgery(P＜0.001).Logistic regression analysis showed that patients with elevated FGF had a higher risk of recurrence in PCM(P＜0.05).LOWESS analysis found that there is a certain non-linear relationship between PCM recurrence rate and FGF.FGF has good predictive performance for PCM recurrence.After further adjusting for various confounding fac-tors such as BMI,it was found that the angiogenic factor is related to FGF.The interaction results show that there is an additive or multiplicative interaction between FGF and VEGF/ES.Conclusion:FGF elevation increases the risk of re-currence after segmental mastectomy for PCM.FGF and VEGF/ES exhibit additive or multiplicative interactions.FGF has good predictive performance for PCM recurrence.

Objective:To investigate the mechanism of natural antigen B(nAgB)to protect Immune thrombocytopenia(ITP)mouse model by influencing autophagy.Methods:Twenty-eight female BALB/c mice aged 8-10 weeks were randomly divided into four groups.7 mice of each group were immunized intraperitoneally,the control group was treated with PBS as the control group;ITP group was treated with anti-CD41 monoclonal antibody(anti-CD41Ab)only;nAgB group was treated with nAgB intraperitoneal injection for 5d;nAgB+ITP group was treated with nAgB intraperitoneal injection for 5d,then treated with anti-CD41 Ab.The peripheral blood platelet count in each group was tested;and the spleen and liver should be isolated and weighed,the organ index was calculated;qRT-PCR was used to detect spleen microtubule-associated protein 1 light chain 3(LC3),p62,Beclin-1 mRNA expression levels.Western blot was used to detect the protein expression level of spleen LC3 Ⅱ/LC3 Ⅰ,p62,Beclin-1.Results:Compared with the control group,mice in the ITP group showed a significant decrease in blood PLT count[(102.1±17.9)× 109/L vs(485.4±185.2)×109/L,P＜0.01],a significant increase in spleen index(P＜0.01),mice in the nAgB group showed a significant increase in blood PLT count,rising to(1051±127.6)× 109/L on the 3 day after modeling.Compared with the ITP group,mice in the nAgB+ITP group showed a significant increase in PLT count on the 1 day of anti-CD41 Ab administration[(428.6±131.6)× 109/L vs(102.1±17.9)×109/L,P＜0.05],however,the spleen index was significantly decreased(P＜0.05).qRT-PCR and Western blot results showed that compared with the control group,the mRNA and protein expression levels of spleen LC3,p62 and Beclin-1 were increased in the ITP group of mice(P＜0.05,P＜0.01).Compared with the ITP group,the nAgB+ITP group could significantly decrease mRNA levels of spleen LC3,p62 and Beclin-1(P＜0.05,P＜0.01),and also significantly decrease the protein expression levels of LC3 Ⅱ/LC3 Ⅰ,p62 and Beclin-1(P＜0.05,P＜0.01).Conclusion:nAgB inhibits the transcription and expression levels of autophagy-related genes and regulates immune intolerance,thereby protecting ITP mouse models.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.