ObjectiveTo investigate the efficacy and safety of Babaodan Capsule （BBD） in the treatment of patients with chronic hepatitis B virus （HBV） infection with damp-heat in the liver and gallbladder comorbid with gallbladder polyps. MethodsA randomized， double-blinded， placebo-controlled single-center trial was conducted among 120 patients with chronic HBV infection who were admitted to Beijing YouAn Hospital， Capital Medical University， from August 2020 to April 2023， and they were divided into treatment group （BBD） and control group （placebo）， with 60 patients in each group. The course of treatment was 24 weeks， and follow-up assessments were conducted every 4 weeks. The primary outcome measures were the number and maximum diameter of gallbladder polyps （assessed by ultrasound）， and the secondary outcome measures included traditional Chinese medicine （TCM） syndrome score， blood lipid levels， and liver function parameters. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups； the Wilcoxon rank-sum test was used for comparison of ranked data between two groups； the generalized estimating equation was used to analyze repeated measures data. ResultsAfter 8 weeks of treatment， the treatment group had a significantly smaller diameter of polyps and a significantly lower number of polyps than the control group （Z=-1.76 and -1.80， both P<0.05）， and after 24 weeks of treatment， the treatment group had a significantly higher polyp reduction rate than the control group （30.51% vs 10.91%， P<0.05）. The subgroup analysis showed that patients receiving combined antiviral therapy， male patients， patients with a diameter of polyps of <5 mm， and patients with multiple polyps tended to achieve significantly greater benefits. At week 8 of treatment， the treatment group had a significantly better TCM syndrome score than the control group （Z=-2.35， P<0.05）； after treatment， compared with the control group， the treatment group had a significantly greater increase in high-density lipoprotein （Z=-1.85， P<0.05） and significantly lower levels of alanine aminotransferase （Z=-2.06， P <0.05）， aspartate aminotransferase （Z=-2.13， P<0.05）， total bilirubin （Z=-2.12， P<0.05）， and direct bilirubin （Z=-3.09， P<0.05）. No serious adverse events were reported in either group. ConclusionBBD can effectively reduce the size of gallbladder polyps， improve TCM syndrome score， and reduce the level of bilirubin in patients with chronic HBV infection with damp-heat in the liver and gallbladder， with a favorable safety profile， and it may be more suitable for patients receiving combined antiviral therapy and specific subgroups （male patients， patients with a diameter of polyps of <5 mm， and patients with multiple polyps.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Purpose To evaluate the value of multimodality MRI-based nomogram model for predicting peritumoral brain tissue invasion in atypical meningioma.Materials and Methods A total of 187 patients with pathologically diagnosed atypical meningioma in the First Affiliated Hospital Fujian Medical University from January 2018 to January 2023 were retrospectively enrolled,including 130 cases of peritumoral brain tissue invasion and 57 cases of none peritumoral brain tissue invasion.Clinical data and multimodality MRI features,including age,gender,tumor location,maximum diameter,peritumoral oedema,tumor-brain interface,lobulated sign,dural tail sign,cyst degeneration/necrosis,relative minimum apparent diffusion coefficient(rADCmin)and intratumoral susceptibility signal were analyzed.Univariate and multivariate Logistic regression analysis were performed to screen the independent predictors of peritumoral brain tissue invasion in atypical meningioma,then a multimodality MRI prediction model was constructed,and was visualized as a nomogram.The prediction performance of multimodality MRI-based nomogram model and each independent predictor were assessed using receiver operating characteristic curve.Results The maximum diameter(OR=0.705,95%CI 0.539-0.920,P=0.010),peritumoral oedema(OR=1.333,95%CI 1.095-1.624,P=0.004),tumor-brain interface(OR=5.121,95%CI 2.045-12.806,P＜0.001)and rADCmin(OR=0.126,95%CI 0.033-0.483,P=0.002)were independent predictors of peritumoral brain tissue invasion in atypical meningioma.The area under the curve,sensitivity and specificity of the multimodality MRI-based nomogram model for predicting peritumoral brain tissue invasion in atypical meningioma was 0.80(95%CI 0.73-0.88),87.69%and 66.67%,respectively.The multimodality MRI-based nomogram model showed significantly higher area under the curve than that of the maximum diameter,peritumoral oedema,tumor-brain interface and rADCmin of atypical meningioma(all Z=3.665,3.904,4.359,3.701,P＜0.05).Conclusion The multimodality MRI-based nomogram model may be helpful for the prediction of peritumoral brain tissue invasion in atypical meningioma.

Objectives:The ORION-18 study has demonstrated that inclisiran can significantly reduce low-density lipoprotein cholesterol(LDL-C)and has good safety in Asian atherosclerotic cardiovascular disease(ASCVD)patients or ASCVD high-risk population.This subgroup analysis aims to further evaluate the efficacy and safety of inclisiran in Chinese mainland population.Methods:ORION-18 study is a multi-center,randomized,double-blind,placebo-controlled,phase Ⅲ clinical trial among Asian subjects,Chinese mainland subgroup included 232 ASCVD patients or ASCVD high-risk subjects who had already been treated with diet control and maximum tolerated doses of statins treatment(with or without other lipid-lowering treatments)but still had elevated LDL-C levels.Subjects were randomized in a 1:1 ratio to the inclisiran group and the placebo group(n=116 each),and received 300 mg of inclisiran or placebo respectively on day 0,90 and 270.The primary endpoint was the percentage change in LDL-C from baseline to day 330.The secondary endpoints included the time-adjusted percentage change and absolute change in LDL-C from baseline after day 90 and up to day 360,the absolute change in LDL-C from baseline to day 330,and the percentage changes from baseline to day 330 in proprotein convertase subtilisin/kexin type 9(PCSK9),total cholesterol,apolipoprotein B(ApoB),non-high-density lipoprotein cholesterol(non-HDL-C).Other secondary endpoints included the proportion of participants reaching LDL-C levels of<1.8 mmol/L at day 330,the proportion of participants with≥50%LDL-C reduction from baseline to day 330 and the proportion of participants who attained global lipid targets(the LDL-C target was<1.4 mmol/L for ASCVD patients and<1.8 mmol/L for ASCVD high-risk subjects)at day 330.Safety endpoints included adverse events during treatment,aboratory test abnormalities during treatment,serious adverse events,and assessed their severity and relation to treatment.Results:The inclisiran group showed a placebo-corrected percentage change in LDL-C from baseline to day 330 of-61.16%,and an absolute change of-1.73 mmol/L(both P<0.0001).Compared to the placebo group,the inclisiran group's time-adjusted percentage change in LDL-C from baseline between day 90 and day 360 was-58.51%,and an absolute change of was-1.64 mmol/L(both P<0.0001).At day 330,reductions from baseline were observed in the inclisiran group for PCSK9,total cholesterol,ApoB,non-HDL-C,with placebo-corrected percentage changes of-77.44%,-35.65%,-43.43%,-50.90%(all P<0.0001),respectively.At day 330,79.6%(74/93)of patients in the inclisiran group and 7.8%(6/77)in the placebo group achieved LDL-C levels<1.8 mmol/L,69.9%(65/93)of patients in the inclisiran group and 0%(0/77)in the placebo group achieved≥50%LDL-C reduction from baseline,66.7%(62/93)of patients in the inclisiran group and 2.6%(2/77)in the placebo group achieved their global LDL-C targets.The safety profile of inclisiran treatment over 12 months was comparable to that of the placebo,with no occurrence of treatment-related serious adverse events.Conclusions:In ASCVD patients or ASCVD high-risk subjects in Chinese mainland who have received diet control and maximum tolerable dose statins treatment(with or without other lipid-lowering treatments)and still have elevated LDL-C,inclisiran has a definite efficacy and good safety in reducing LDL-C.The efficacy and safety results of inclisiran assessed in Chinese mainland population are consistent with those of the general Asia population.

Objective To measure the three-dimensional(3D)motion of the knee joint in healthy people and patients after total knee arthroplasty(TKA).Methods The coordinate system for the tibia and femur of the knee joint was established,and the marking points were pasted at the bone landmarks.Then the 3D motion of human knee joint was measured by biplane high-speed photogrammetry,and the data were processed according to the coordinate transformation.Results The peak values of adduction and abduction,internal and external rotation,internal and external translation,and proximal and distal movement of the artificial knee joint were larger than those of the healthy knee joint(P<0.05),but there was no statitistic difference in posterior displacement between the artificial and healthy knee joints(P=0.05).Conclusions By measuring the knee joint motion,not only the difference in knee joint motion between the healthy volunteers and TKA patients was revealed,but also the effectiveness of biplane high-speed photography in knee joint kinematic measurement was demonstrated.

Objective:To evaluate the efficacy and analyze the causes of complications of allogeneic decellularized dermal matrix grafts in the treatment of gingival recession using tunneling technology.Methods:Sixty patients with single or multiple gingival re-cession were randomly divided into an allogeneic decellularized matrix(ADM)group and a connective tissue(SCTG)group.Tunne-ling technique(TUN)were used in both groups to cover the root surface,and the gingival margin position,gingival margin morpholo-gy,and mucogingival junction position of the affected teeth at 1 week,3 weeks,3 months,and 6 months after surgery were observed.Check and record the gingival recession depth(RD)and mean root coverage(MRC)at the implant site before and 6 months after surgery.Record patient satisfaction at 3 weeks and 6 months after surgery.Results:Compared with the traditional SCTG group,the MRC of the ADM group was significantly lower before surgery and 6 months after surgery(P＜0.05).The satisfaction level of the ADM group was higher 3 weeks after surgery,with a significant difference compared to the SCTG group(P＜0.05).But 6 months after surgery,the satisfaction levels of the two groups tended to be consistent,with no significant difference.After TUN+ADM surgery,there was 1 case of abscess infection lesion,and another 3 cases showed local tissue necrosis at the gingival margin one week after surgery.After 3 months of treatment,the gingival color of these 4 patients was pink and tough texture,without swelling and bleeding.Conclusion:Although ADM is slightly inferior to SCTG in the treatment of gingival recession,it may be related to poor postoperative tissue healing complications.However,as long as it is handled properly,long-term follow-up observations have shown that gingival tissue can still achieve complete healing.TUN+ADM is a highly effective treatment for gingival recession and is suitable for further clinical application.

Objective To study the effect of medial collateral ligament(MCL)release on the squatting motion followling total knee arthroplasty(TKA)and provide reference data for ligament release during knee replacement surgery.Methods Based on CT and MRI images of a volunteer,a three-dimensional(3D)geometric anatomical model of the natural knee joint including bone tissues and major soft tissues was established.A finite element model of the artificial knee joint was established by simulating TKA surgery.The squatting motion after 30％release of the upper end,lower end,and both ends of the MCL was simulated,and motion characteristic data of the knee joint at flexion/extension angles from 0° to 135° were obtained.Results The effects of ligament release at different locations on knee squatting motion varied.After releasing the lower end,the medial translation,posterior translation,superior translation,and adduction of the femur relative to the tibia increased by 13.74％,3.83％,9.74％,and 2.37％,respectively,while the external rotation decreased by 36.8％.After releasing the upper end,the medial translation and posterior translation increased by 10.65％and 10％,respectively,while the superior translation,adduction,and external rotation decreased by 4.52％,33.89％,and 67.1％,respectively.After releasing both ends,the medial translation,posterior translation,and superior translation increased by 14.77％,9.39％,and 22.56％,respectively,while the adduction and external rotation decreased by 15.62％and 47.3％,respectively.Conclusions After MCL released,the medial translation,anterior translation,superior translation,and abduction of the femur relative to the tibia increased,while the external rotation decreased.Releasing the lower end had the least effect on these femoral movements,showing an obvious advantage.

Hepatocellular carcinoma(HCC)is one of the most prevalent malignancies worldwide,and accurate prognostic assessment and treatment planning are vital for improving patient outcomes.Conventional prognostic models,which rely on limited clinicopathological parameters,often fail to capture the profound heterogeneity of HCC.In recent years,artificial intelligence(AI)-particularly machine learning and deep learning-has driven a paradigm shift in precision oncology by leveraging its powerful capabilities in data mining and pattern recognition.This review provides a comprehensive overview of recent advances in AI for prognostic assessment and treatment optimization in HCC,with an emphasis on key methodologies such as radiomics and multi-modal data integration.It further discusses the clinical potential and challenges of AI in predicting postoperative recurrence,evaluating therapeutic response,and supporting individualized treatment decisions,while also outlining future directions in this rapidly evolving field.The review aims to inform and facilitate the clinical translation of AI technologies into the management of HCC.