Objective To evaluate the effect of contrast-enhanced ultrasound(CEUS) in the real-time monitoring treatment of ultrasound-guided high intensity focused ultrasound (HIFU ) for uterine adenomyosis .Methods From January 2013 to September 2013 ,a total of 67 patients who were clinically diagnosticated as uterine adenomyosis were enrolled in this study .49 patients were diffuse type and 18 patients were localized .CEUS was used before ,in ,after ultrasonic treatment to make sure lesions and evaluate the ablation effect .Results 67 patients were 100% perfused before HIFU treatment by CEUS ,the non-perfused volume ratio of 15 patients(22 .4% ) were not enough during treatment ,and more energy were given .During HIFU treatment ,uniform grey scale change was observed in 42 of 67(62 .7% ) patients and massive grey scale change was observed in 25 of 67(37 .3% ) patients .The margin of targets and the non-perfused volume were clearly detected by CEUS .The size of target andymyosis ,the volume ,the non-perfused volume ,and non-perfused volume ratio were(4 .8 ± 1 .5)cm ,(63 .1 ± 57 .2)cm3 ,(59 .1 ± 53 .4 )cm3 ,(76 .4 ± 27 .0)% .The adverse effects occurred in the treatment were not related to CEUS .Conclusion CEUS is an accurate method in assessing the treat-ment effect of HIFU and could be safely used during HIFU treatment for uterine adenomyosis .

Objective To compare the advantages and disadvantages of high intensity focused ultrasound (HIFU ) and total abdominal hysterectomy for the treatment of uterine fibroids .Methods 167 patients with symptomatic uterine fibroids were divid‐ed into the HIFU treatment group(n=86) and the hysterectomy group(n=81) .The adverse events were recorded before operation and at postoperative 1 ,3 ,6 months .The questionnaire survey of the uterine fibroid symptoms‐quality of life (UFS‐QOL) was con‐ducted .The health related living quality was evaluated by using the health survey questionnaire‐36(SF‐36) .Results There were no severe adverse events in either group .The significant clinical complications and adverse events in the HIFU group were lower than those in the hysterectomy group .The UFS‐QOL scores in the HIFU group were superior to those in the hysterectomy group ,but the SF‐36 scores at postopertive 3 ,6 months had statistically significant differences between the two groups (P>0 .05) .Conclusion The patients who are unable to tolerate surgery or hope to preserve the uterus and its physiological function are suitable for HI‐FU treatment .

Objective: To explore the impact of insulin resistance (IR) and adiponectin (APN) lacking on myocardial remodeling in experimental mice. Methods:16 normal C57 mice were divided into 2 groups: Control group and IR group; in addition, 16 APN gene knockout(APNKO) mice were divided into another 2 groups: APNKO group and APNKO+IR group.n=8 in each group. The mice in Control group and APNKO group were fed with normal diet, in IR group and APNKO+IR group were fed with high fat diet to create the IR model. All animals were treated for 12 weeks. Blood levels of total cholesterol(TC), triglycerides(TG),fasting plasma glucose(FPG) and fasting insulin(FINS) were examined; heart weight and left ventricular weight were measured; left ventricular myocardial morphological changes and the degree of ifbrosis were assessed by HE staining and Masson staining; protein expressions of myocardial matrix metalloproteinase-9 (MMP-9) and APN were detected by immunehistochemistry and Western blot analysis. Results: Compared with Control group, IR group, APNKO group and APNKO+IR group showed elevated blood levels of TC, TG, FPG and FINS; increased heart weight and left ventricular weight, allP<0.05; IR group, APNKO group and APNKO+IR group presented more myocardial hypertrophy, decreased protein expression of APN and increased protein expression of MMP-9, allP<0.05.Conclusion: IR and APN lacking could incur myocardial remodeling in experimental mice and they had synergistically facilitated effect.

BACKGROUND: As an ideal scaffold of cartilage tissue engineering, demineralized bone matrix (DBM) has been widespread used. But some of biological characters remain poorly understood.OBJECTIVE: To determine the degradation capacity, interval porosity and adhesion rate of mesenchymal stem cells (MSCs) onto DBM in vitro.DESIGN, TIME AND SETTING: An observation experiment in vitro was complicated in Institute of Orthopedics, Second Hospital of Lanzhou University from January 8~(th) to April 15~(th) in 2005 and Central Laboratory of Guilin Medical University from August 1~(st) to November 15~(th) in 2007.MATERIALS: One chinchilla rabbit was killed under anesthesia. Referring to the method described by Urist, DBM was made by cancellated bone harvested from metaphysis and vertebral body METHODS: DBM was soaked into phosphate buffered solution to determine its degradation capacity; liquid replacement method was used to test its interval porosity; The 3~(rd) passage MSCs at a concentration of 1×10~8/L were cocultured with DBM in vitro and adhesion rate of MSCs onto DBM was tested using cytometry.MAIN OUTCOME MEASURES: The degradation capacity, interval porosity and adhesion rate of MSCs onto DBM.RESULTS: The degradation rate of DBM was accelerated with the prolonging of time, and the complete degrading time was about 10-12 weeks; The holing rate tested was (77.15±3.44)%; The 3~(rd) passage cells had a higher adhesive rate of 71.25% onto DBM.CONCLUSION: DBM degradation curve is consistent with MSCs proliferation curve, indicating a satisfactory adhesion capacity and interval porosity and DBM is an ideal biological scaffold material for cartilage tissue engineering.

Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

Objective To study the expression of ALK protein in pulmonary adenocarcinoma as detected by Ventana immunohistochemistry, with correlation of clinicopathologic features. Methods Immunohistochemical study for ALK protein using Ventana ALK ( D5F3) kit was carried in 7 371 pulmonary adenocarcinoma samples.The clinicopathologic features were subsequently analyzed.Results ALK fusion protein was detected in 446 of the 7 371 lung adenocarcinoma samples studied ( 6.05%) .The ALK positivity rate in small biopsy samples was higher than that in surgical specimens [ 9.02% ( 153/1 696 ) versus 5.16%(293/5 675);P<0.01] .ALK fusion protein expression correlated with patient age, sample type and smoking history.ALK positivity rate in each age group increased with younger patient age.ALK positivity rate was 45.45%(10/22) in patients younger than 30 years old.The positivity rate of ALK fusion protein in adenocarcinoma in-situ, minimally invasive adenocarcinoma and invasive adenocarcinoma was 0, 0.48%(2/418) and 5.63% (291/5 165), respectively.The differences of ALK positivity rate amongst different subtypes had statistical significance ( P<0.01 ).Invasive mucinous adenocarcinoma had highest ALK positivity rate, followed by invasive adenocarcinoma with predominantly solid pattern.Conclusions ALK fusion protein is more often found in young patients with pulmonary adenocarcinoma, especially in those younger than 30 years old.ALK fusion protein is rarely expressed in early-stage pulmonary adenocarcinoma. Invasive mucinous adenocarcinoma and invasive adenocarcinoma with solid pattern have higher ALK positivity rate than other adenocarcinoma subtypes.