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 construct a glioma microfluidic chip model to simulate tumor microenvironment for evaluating the medicinal efficacy of anti-glioma traditional Chinese medicines. Methods Glioblastoma cells U251 were seeded into microfluidic chips with different culture modes, and the cell viability and tumour microenvironment within the constructed model were characterized. Fluorescence staining was used to evaluate the effects of the positive drugs temozolomide （TMZ） and docetaxel （DOC） on the cell activity and apoptosis within the model, which was applied to evaluate the medicinal efficacy of the extracts of the herb Scutellaria barbata on gliomas. Results The cells in the constructed U251 microfluidic chip model displayed high viability and were able to mimic the hypoxic microenvironment of tumor to a certain extent. The viability of the U251 cells in the microfluidic chips decreased with the increasing of the concentration of the positive drug, and the viability of the 3D cultured U251 cells was higher than that in the 2D condition （P<0.05）. The intracellular mitochondrial membrane potential decreased with the increasing of the concentration of the positive drug. And the 2 mg/ml Scutellaria barbata extract killed U251 cells to a certain extent and reduced the mitochondrial membrane potential of the cells in the model. Conclusion This study successfully constructed a microfluidic chip model of glioma that could effectively simulate the tumor microenvironment and rapidly evaluate the anti-tumor medicinal efficacy, which provided a new strategy for the medicinal efficacy evaluation and active components screening of anti-glioma traditional Chinese medicines.

Objective To evaluate the efficacy of Puerariae lobatae radix （PLR） and Anemarrhenae Rhizoma （AR） in preventing and treating Alzheimer’s disease （AD） and explore its potential mechanism of action by LC-MS serum metabolomics strategy. Methods The AD rat model was established by administering aluminum chloride （AlCl₃） and D-galactose （D-gal） for 20 weeks. The traditional Chinese medicine intervention group was given the PLR, AR, and PLR-AR extracts for 8 weeks by gavage. The model effect and efficacy were evaluated by Morris water maze test and biochemical indicators including SOD, NO, and MDA; Metabolomics research based on the UHPLC-Q/TOF-MS method was conducted, and relevant metabolic pathways were analyzed through the MetaboAnalyst online website. Results The learning and memory abilities of AD model rats were significantly decreased compared with the control group, and the levels of oxidative stress and lipid peroxides were significantly increased （P<0.05）, while the SOD content was decreased considerably （P<0.01）. The learning and memory abilities of AD model rats were improved, oxidative stress and lipid peroxidation levels were reversed, and serum SOD content was increased significantly after the intervention of PLR-AR, with better effects than single drugs. Through metabolomics, 70 differential metabolites were identified between the AD model group and the control group, mainly involving 10 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and unsaturated fatty acid biosynthesis, et.al. The intervention of PLR-AR could adjust 47 metabolites, with 20 metabolites showing significant differences （P<0.05）. The significantly adjusted metabolites involve 6 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, et al. Conclusion The combination of PLR and AR could significantly improve the learning and memory abilities of AD rat models. The mechanism may be related to the improvement of oxidative stress and lipid peroxidation levels, the increase of serum SOD content, and the regulation of phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

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.

AIM To investigate the effects of Moluodan Dami Pills on chronic atrophic gastritis(CAG)rats and their mechanism.METHODS The rat models were randomly divided into the model group,the low-dose group and high-dose Moluodan Dami Pills groups(2.43 g/kg and 4.86 g/kg),and vitamin A group(0.32 g/kg),following the 16 weeks successful induction of CAG by five-factor modeling method,in contrast to another 10 normal rats of the control group.After 8 weeks corresponding administration,the rats of each group had their general physiological status and pH value of gastric juice assessed;their pathological changes of gastric mucosa observed by naked eyes combined with HE staining;their changes of gastrin-secreting cells(G cells)and somatostatin-secreting cells(D cells)in gastric mucosa observed by immunohistochemistry;and their serum levels of pepsinogen Ⅰ/pepsinogen Ⅱ(PG Ⅰ/PG Ⅱ)ratio,TNF-α and IL-6 detected by ELISA.RESULTS Compared with the model group,the groups intervened with Moluodan Damei Pills and vitamin A displayed lower pH values of gastric juice(P＜0.05),improved pathological changes of gastric mucosa,increased G and D cells counts(P＜0.05,P＜0.01),increased ratio of serum PGⅠ/PGⅡ,and decreased levels of IL-6 and TNF-α(P＜0.05,P＜0.01).CONCLUSION Moluodan Dami Pills can effectively improve the symptoms of CAG rats through its influence on the number and secretion abilityof G and D cells,the levels of serum PG Ⅰ/PG Ⅱ ratio and inflammatory factors.

Objective To study the ability of radial basis function neural network(RBFNN)with different implementations for electrical impedance tomography(EIT)under real brain shapes,to evaluate the advantages and disadvantages of different approaches,and to provide a reference for the selection of practical imaging methods.Methods COMSOL Multiphysics was used to establish a multilayer 2D model with real structure based on brain CT and an EIT simulation dataset.The effects of the exact RBFNN,the orthogonal least squares-based RBFNN(OLS RBFNN)and the K-Means-based BRFNN(K-Means RBFNN)on the image reconstruction result were explored with the dataset constructed.The root mean square error(RMSE)and image correlation coefficient(ICC)were adopted to evaluate the imaging results.Results EIT could be completed with all the three RBFNNs without noise,and the exact RBFNN had the best results with average ICC and RMSE of 0.784 and 0.467,respectively,in the test set.The OLS RBFNN had the best imaging results at a hidden node of 50,with an average ICC and RMSE of 0.788 and 0.462,respectively.The K-Means RBFNN achieved the best imaging results at noise levels of 30,40,50,60,70 and 80 dB with stable ICC and RMSE and high robustness.Conclusion All the three RBFNNs can be used for brain EIT image reconstruction with their own advantages and disadvantages,and the RBFNN has to be selected for EIT reconstruc-tion based on considerations on actual conditions.[Chinese Medical Equipment Journal,2024,45(10):1-6]

Objective To develop a prediction tool for post-endoscopic retrograde cholangiopancreatography(ER-CP)early biliary tract infection(PEEBI)in patients with choledocholithiasis,and assist clinical decision-making be-fore ERCP and early personalized intervention after ERCP.Methods An observational bidirectional cohort study was adopted to select inpatients with choledocholithiasis who underwent ERCP in a hospital.Directed acyclic graph(DAGs)and the least absolute shrinkage and selection operator(LASSO)were used to predict PEEBI based on lo-gistic regression,and the models were compared and validated internally and externally.Results From January 1,2020 to September 30,2023,a total of 2 121 patients with choledocholithiasis underwent ERCP were enrolled,of whom 77(3.6％)developed PEEBI,mostly in the first 2 days after surgery(66.2％).The major influencing fac-tors for PEEBI were non-iatrogenic patient-related factors,namely diabetes mellitus(OR=2.43,95％CI:1.14-4.85),bile duct malignancy(OR=3.95,95％CI:1.74-8.31)and duodenal papillary diverticulum(OR=4.39,95％CI:1.86-9.52).Compared with the LASSO model,the DAGs model showed higher ability(3.0％)in com-prehensive discrimination(P=0.007),as well as good differentiation performance(D=0.133,P=0.894)and cal-ibration performance(x2=5.499,P=0.703)in external validation.Conclusion The DAGs model constructed in this study has good predictive performance.With the help of this tool,targeted early preventive measures in clinical practice can be taken to reduce the occurrence of PEEBI.

Ziziphi spinosae semen mainly contains contents of saponins,flavonoids,alkaloids and aliphatic acids.Meanwhile,it has a variety of activities such as sedative-hypnotic,anti-anxiety,anti-depression,nerve protection,cardiovascular and cerebrovascular protection,liver protection,and antioxidant,which is widely used in medicine,food,health food and other fields.The chemical constituents,pharmacological action and clinical application of Ziziphi spinosae semen were systematically summarized in this paper by reviewing the literature,in order to provide theoretical guidance for the sustainable development of the resources and the rational use of Ziziphi spinosae semen.

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.