OBJECTIVE: To investigate the clinical efficacy and advantages of robot-assisted total knee arthroplasty (TKA) in patients with varus knee osteoarthritis. METHODS: Between October 2022 and June 2023, a total of 59 patients with severe knee osteoarthritis resulting in varus were treated with total knee arthroplasty, aged from 59 to 81 years with an average (70.90±4.63) years, including 19 mals and 40 females. The patients were divided into two groups based on the surgical method used:28 patients in the robot group and 31 patients in the traditional group. The robot group consisted of 8 males and 20 femalse patients, with an average age of (70.54±4.80) years and an average disease duration of (14.89±8.72) months. The traditional group consisted of 11 males and 20 females patients, with an average age of (71.39±4.5) years and an average disease duration of (12.32±6.73) months. The operative duration, amount of bleeding during the operation, postoperative activity time after the operation, hip-knee-ankle angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and complications were compared between the two groups before and after the operation. Lateral tibia component (LTC), frontal tibia component (FTC), frontal femoral component (FFC) and lateral femoral component (LFC) were measured 6 months after operation Additionally, the degree of knee joint motility, American Knee Society score (KSS), and visual analogue scale(VAS) were compared before and after the operation. RESULTS: All patients had gradeⅠwound healing without any complications, and all patients were followed up for 6 to 8 months, with an average of (6.5±1.5) months. There were no significant differences preoperative imaging evaluation indexes (including HKA, LDFA, and MPTA), preoperative knee mobility, preoperative VAS, and preoperative KSS between the two groups (P>0.05). Comparing the operation time (109.11±7.16) min vs. (83.90±7.85) min, length of the incision (16.60±2.33) cm vs. (14.47±1.41) cm, intraoperative bleeding (106.93±6.15) ml vs. (147.97±7.62) ml, postoperative activity time (17.86±1.84) h vs. (21.77±2.68) h, between the two groups showed statistically significant differences (P<0.05). There were significant differences in FFC (88.96±0.84)° vs. (87.93±1.09)° and LFC (88.57±1.10)° vs. (87.16±1.2)° between the two groups at 6 months after operation (P<0.05). The robotic group 1, 3, 6 months after KSS (75.96±3.96), (81.53±3.78), (84.50±3.29) scores, VAS (3.68±0.67), (2.43±0.79), (0.54±0.64), knee joint mobility (113.32±4.72) °, (123.93±3.99) °, (135.36±2.34) °;Traditional group KSS (73.77±4.18), (76.48±3.60), (80.19±3.28) scores, VAS (4.16±1.04), (3.03±0.75), (1.42±0.76) scores, knee joint mobility (109.19±6.95) °, (119.94±6.08) °, (134.48±2.14) °. Compared to before surgery, both groups showed significant improvement in KSS, VAS and knee mobility during the three follow-up visits (P<0.001). Additionally, postoperative HKA (180.39±1.95)° vs. (178.52±2.23)°, LDFA (89.67±0.63) ° vs. (89.63±0.63)°, and MPTA (89.44±0.55)° vs. (89.29±0.60)° were significantly improved in both groups compared to before surgery (P<0.001). The robotic group had higher KSS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). The robotic group also had lower VAS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). Furthermore, knee mobility was higher in the robotic group than those in the traditional group at 1 and 6 months after surgery (P<0.05), but there was no significant difference between the two groups at 6 months after surgery. CONCLUSION Robot-assisted total knee arthroplasty is a safe and effective method for total knee replacement. The use of robotics can improve the limb axis and prosthesis alignment for patients with preoperative varus deformity, resulting in better clinical and imaging outcomes compared to the conventional group.
Humans ; Female ; Male ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Robotic Surgical Procedures/methods*

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.

Objective To investigate the improvement effects of homogeneous fecal microbiota transplantation(FMT)on chemotherapy-induced diarrhea(CID)in mice.Methods Fifteen C57BL/6N mice were divided into control group,CID model group and CID+FMT group according to the random number distribution and remainder grouping method,with 5 mice per group.Control group received no intervention,and their feces were used to prepare fecal bacteria suspension.CID model group was injected intraperitoneally with fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,followed by gavage with 0.1 ml of saline on alternate days.CID+FMT group was given 0.1 ml fecal bacteria suspension gavage on alternate days for one week,followed by intraperitoneal injection of fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,with the experiment ending on the 14th day.During the experiment,the mice's food intake and body weight were recorded.At the end of the experiment,the mice were euthanized with deep carbon dioxide anesthesia,and the mice colonic specimens from cecum to anus were collected for hematoxylin and eosin(HE)staining and histopathological examination.Fecal samples were collected for 16S rRNA gene sequencing.Shannon index,Simpson index and Chao1 algorithm were used to analyze the α-diversity species of the intestinal flora in each group of mice.Similarity analysis(Anosim)was used to perform non-parametric on the inter-group differences of intestinal flora among the mice.Linear discriminate analysis size effect(LEfSe)and nonmetric multidimensional scaling(NMDS)were employed to analyze the intestinal dominant flora and the similarity classification relationships in each group of mice.Results The colonic specimen's length from cecum to anus in CID model group was significantly shorter than that in control group(P<0.05),while there was no significant difference between CID+FMT group and CID model group(P>0.05).The weight of mice in CID model group decreased by 42.04%,while control group mice gained 10.24%,with a significant difference between the two groups(P<0.05).The weight of mice in CID+FMT group decreased by 8.12%,which was significantly improved compared to CID model group(P<0.05).HE staining results revealed the intestinal mucosal structure in CID model group was severely damaged,with atrophy and deformation,accompanied by inflammatory cell infiltration,and the pathological score was higher than that of control group(P<0.05).Compared with CID model group,the intestinal mucosal integrity and crypt cells in the CID+FMT group were improved,with less damage,and the pathological score was lower than that of CID model group,but the difference was not statistically significant(P>0.05).The α-diversity analysis showed that there were significant differences in the Shannon,Simpson and Chao1 indices among the three groups(P<0.05).ANOSIM and NMDS analysis revealed that the intestinal flora in CID+FMT group was closer to the normal intestinal flora compared to CID model group.LEfSe analysis showed that the intestinal flora in CID model group was enriched in famliy_Bacteroidaceae,and the intestinal flora in CID+FMT group was similar to that of control group,with an enrichenment of familiy_Enterobacteriaceae.Conclusion Homogeneous FMT can improve the abundance of intestinal flora in CID mice,making it more similar to normal intestinal flora,thereby protecting intestinal mucosa,reducing damage and alleviating the severity of CID.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Epilepsy is a common neurological disease,has the characteristics of recurrent attacks and long-term treatment,thus bringing great pressure to patients and their families.Therefore,it is particularly important to do a good job of disability assessment.In recent years,with the development of the discipline,academic organizations such as the International League Against Epilepsy(ILAE)and China Association Against Epilepsy(CAAE)have successively updated the definition and diagnostic criteria of epilepsy and seizures.However,some items of epilepsy in the current Criteria for Disability Rating of Military Personnel(Trial)issued by People's Liberation Army(PLA)in 2011 can no longer meet the latest guidelines at home and abroad.Therefore,we suggest that the items related to epilepsy in the Criteria for Disability Rating of Military Personnel(Trial)should be revised to ensure that the disability evaluation being completed fairly and successfully.

Osteoarthritis (OA) is a chronic degenerative joint disease and the most common type of arthritis. It involves almost any joint and can lead to chronic pain and disability. In the late 19th century, Roentgen discovered X-rays, and then began to use radiotherapy to treat tumors. In the 1980s, Luckey thought that low-level radiation (LDRT) might be beneficial to biology, and it was gradually applied to the treatment of some diseases. This paper introduces the epidemiology, risk factors, clinical manifestations and treatment methods of OA, points out that the cartilage injury and the important effect of synovial inflammation in the pathogenesis of OA, namely when the homeostasis of articular cartilage are destroyed, synthetic metabolism and catabolism imbalances, cartilage cells damaged their breakdown products consumed by synovial cells. Synovial cells and synovial macrophages secrete proinflammatory cytokines, metalloproteinases and proteolytic enzymes, leading to cartilage matrix degradation and chondrocyte damage, which aggravates synovial inflammation and cartilage damage, forming a vicious cycle. The possible mechanism and clinical research progress of LDRT in alleviating OA are discussed. LDRT can regulate inflammatory response, inhibit the production of pro-inflammatory cytokines, and promote the production of anti-inflammatory cytokines, thereby achieving anti-inflammatory effect. Studies have shown that after irradiation, the expression of inducible nitric oxide synthase (iNOS) was decreased, the release of reactive oxygen species (ROS) and the production of superoxide were inhibited, the anti-inflammatory phenotype of macrophages was differentiated from M1 to M2, the inflammatory CD8⁺ T cells were transformed into CD4⁺ T cells, and the number of dendritic cells (DC) was significantly reduced. LDRT inhibit the production of proinflammatory factors in leukocytes, reduce their recruitment and adhesion, and down-regulate the expression levels of cell adhesion molecules such as selectin, intercellular adhesion molecule (ICAM) and vascular endothelial cell adhesion molecule (VCAM). LDRT can regulate endothelial cells, stimulate endothelial cells to produce a large amount of TGF-β1, reduce the adhesion of endothelial cells to peripheral blood mononuclear cells (PBMC), and contribute to the anti-inflammatory effect of LDRT. It also exerted anti-inflammatory effects by regulating mitochondrial growth differentiation factor 15 (GDF15). After low-level radiation, the MMP-13 (matrix metalloproteinases-13) and the ADAMTS5 (recombinant a disintegrin and metalloproteinase with thrombospondin-5) decreased, the Col2a1 (collagen type 2) increased in chondrocytes. In the existing clinical studies, most patients can achieve relief of joint pain and recovery of joint mobility after irradiation, and the patients have good feedback on the efficacy. The adverse reactions (acute reactions and carcinogenic risks) caused by LDRT in the treatment of OA are also discussed. During the treatment of OA, a few patients have symptoms such as redness, dryness or itching at the joint skin, and the symptoms are mild and do not require further treatment. Patients are thus able to tolerate more frequent and longer doses of radiotherapy. In general, LDRT itself has the advantages of non-invasive, less adverse reactions, and shows the effect of pain relief and movement improvement in the treatment of OA. Therefore, LDRT has a broad application prospect in the treatment of OA.

During the progression of heart failure(HF),abnormal transduction of the transforming growth factor-β(TGF-β)/Smads signaling pathway is important mechanism of myocardial fibrosis(MF)in HF.TGF-β,a key factor in MF,is in an overexpression state in the process of MF in HF,and Smads is a major effector downstream of TGF-β.The TGF-β/Smads pathway induces abnormal proliferation of myofibroblasts,aggravates myocardial extracellular matrix deposition,and reduces the ability of the cardiac tissues to resist fibrosis,which plays a complex role in the pathogenesis of MF in HF.Traditional Chinese medicine(TCM)has the efficacy of unequivocal inhibiting myocardial collagen deposition,anti-MF,protecting the myocardium and improving cardiac function in the prevention and treatment of MF in HF and so on,and the TGF-β/Smads pathway is one of the key pathways through which TCM monomers,TCM combinations,and proprietary medicines can exert their cardioprotective effects on the HF.This paper reviews the existing experimental research results of TCM intervening in the TGF-β/Smads pathway for the treatment of MF in HF over the past 10 years,with a view to providing theoretical basis for the prevention and treatment of HF MF well as the development and of new drugs.