Objective To investigate the correlation and clinical diagnosis significance between ultrasound elastography and the distribution of myofibroblast in breast tumor.To assess the value of ultrasonic elastography and myofibroblast in the diagnosis of breast cancers.MethodsThree-hundred and fifteen patients recruited from May 2009 to November 2010 were divided into benign group and malignant group according to postoperative pathological diagnosis results considered as gold standard.The clinical value of the score of ultrasonic elastography was evaluated.The expression levels of CD34 and α-SMA protein in breast tissues were examined by immunohistochemistry.ResultsThe difference was statistically significant for the expression level of CD34 and α-SMA between malignant breast tumor patients compared with benign ( P ＜0.05).The expression level of CD34 was lower,but α-SMA was higher in the patients of breast cancer compared with benign tumor.However,the expression level of CD34 and α-SMA was just the opposite in the patients of benign tumor.The expression level of CD34 was the negative correlation with the elastography score ( P ＜0.05) in the breast tumor,but α SMA just the opposite situation.Conclusions The score of ultrasound elastography can represent MFS distribution characteristics in breast tumors in the result that α-SMA +/CD34- can determine the existence of myofibroblast.

Objective To investigate the role of myeloid dendritic cells(mDC)in the pathogenesis of ankylosing spondylitis (AS),and to study the mechanism of tumour necrosis factor (TNF)-α blocker on the treatment of AS by counting the number of mDC before and after the treatment.Methods Peripheral blood from 21 AS patients treated with 50 mg rhTNFR-Fc and 15 AS patients treated with placebo were investigated at week 0,week 2 and week 6 in a randomized,double-blind,placebo-controlled trial.Three-color flow cytometry analysis was used to investigate the change of the number of mDC before and after the treatment.And their correlation with the clinical parameters was analyzed.Results MHC Class Ⅰ positive mDC(Lin-/CD11c+/HLA-abc+)in AS patients was slightly less than in healthy controls (not statistically significant).No significant change in MHC Class Ⅰ mDC number was observed after drug treatment.The number of MHC Class Ⅱ mDC cells was not correlated with clinical parameters.Conclusion The treatment with rhTNFR-Fc in AS induces a significant upregnlation of MHC-Ⅱ DC.

Objective:To explore the expression of caveolin-1 (Cav-1) and Chitinase-40 (YKL-40) in acute cerebral infarction and the value of combined detection in prognosis evaluation.Methods:118 patients with acute cerebral infarction admitted to the First Affiliated Hospital of Hebei Northern University from January 2016 to June 2019 were selected as the research objects. According to the cerebral infarction volume, the patients were divided into small infarction group (<5 cm 3), middle infarction group (5-10 cm 3) and large infarction group (>10 cm 3). 108 healthy people were selected as the healthy control group. The serum levels of Cav-1 and YKL-40 were compared in the 3 groups, and the correlation between the degree of cerebral infarction and serum levels of Cav-1 and YKL-40 was analyzed. Receiver operating characteristic curve (ROC) was used to analyze the diagnostic value of the expression levels of Cav-1 and YKL-40 in patients with acute cerebral infarction; the patients were followed up for one year and the prognosis was evaluated by modified Rankin Scale (mRS); the correlation between serum Cav-1 and YKL-40 and prognosis was analyzed. Results:The expression levels of serum Cav-1 and YKL-40 in patients with acute cerebral infarction were significantly higher than those in healthy group ( P<0.001). The serum levels of Cav-1 and YKL-40 were positively correlated with the infarct volume of acute cerebral infarction ( r=0.854, P=0.004; r=0.867, P=0.002). ROC curve analysis showed that the sensitivity, Youden index and area under ROC curve of Cav-1 (21.78 μg/L) combined with YKL-40 (158.69 ng/ml) in the diagnosis of acute cerebral infarction were 85.59%, 0.532 and 0.896 (95% CI: 0.741-0.932), respectively, which were significantly higher than those of single index ( P<0.05). At 8 and 12 months of follow-up, the proportion of death and mRS score in the positive group were significantly higher than those in the negative group ( P<0.05). Conclusions:The serum Cav-1 and YKL-40 levels are significantly higher in patients with acute cerebral infarction. The combined examination of Cav-1 and YKL-40 can improve the diagnostic efficiency and has potential application value for early diagnosis and prognosis prediction of patients.

Objective To evaluate the efficacy and safety of short-term sensor-augmented insulin-pump (SAP) therapy for poorly controlled patients with type 1 diabetes mellitus (T1DM).Methods Sixty T1DM patients with glycosylated hemoglobin (HbA1c)>9.0% were randomly assigned to 2 groups treated with SAP or multiple daily insulin injection ( MDI) for 6 days, then all patients converted to MDI therapy. Results Compared with MDI group and before therapy, the mean blood glucose concentration ( MBG) , SD of blood glucose, mean amplitude of glycemic excursion ( MAGE) and 24-h area under curve at 10.0 ( AUC10.0 ) levels in SAP group significantly decreased after 6-day therapy ( compared with MDI group:t=1.761,P=0.028, t=2.569,P=0.037, t=2.712,P=0.020, t=2.985,P=0.014, compared with before therapy:t=3.128,P=0.006, t=2.689,P=0.024, t=2.966,P=0.013, t=3.076,P=0.009);while there was no difference in 24-h area under curve at 3.9 (AUC3.9) between groups (P>0.05).After 1 month follow-up HbA1c levels decreased in SAP group (t=2.344,P=0.023) and were significantly lower than those in MDI group (t=1.844, P=0.035).There was no difference in daily insulin dosage, fasting C peptide (FCP) and postprandial 2h C peptide (2hCP) between two groups (P>0.05).Age (t=2.125, P=0.012) and SAP therapy (t=3.376, P=0.009) were independently correlated with the HbA1c after 1 month.Conclusion Short-term SAP therapy is effective and safe for poorly controlled T1DM patients with rapid glucose lowering and glycemic excursions reduction.

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Medical Physics is an interdiscipline which is formed by applying the basic principles, methods, and techniques of physics to clinical medical research such as prevention, diagnosis, and treatment of human diseases, and it is a compulsory professional basic course for medical students. However, there are many medical students reflect that the content of this course is obscure and difficult to understand. Teaching effect is not ideal. The main reasons are that the teaching method is single and the reference materials are few. Based on the actual situation of the course, Hebei Medical University, China promotes formative evaluation from the content of teaching materials, teaching means, and other aspects. At the same time, by combining with the Internet, the digital construction has been realized, deepening the reform of the Medical Physics curriculum, and remarkable results have been achieved.

Objective:To explore the application value of non-invasive myocardial work imaging in evaluating the cardiac function of ST-segment elevation myocardial infarction (STEMI) patients with left ventricular remodeling (LVR) after percutaneous coronary intervention (PCI).Methods:One hundred and twenty-six patients with STEMI undergoing PCI in General Hospital of Ningxia Medical University from December 2021 to September 2022 were prospectively collected and divided into left ventricular remodeling group (LVR group, 34 cases) and non left ventricular remodeling group (NLVR group, 92 cases) according to whether there was left ventricular remodeling 3 months after surgery. General data were collected. Routine echocardiography and noninvasive myocardial work imaging were performed before, 1 week, 1 month, and 3 months after surgery, the differences in the above parameters between the two groups were compared. Pearson correlation analysis was used to analyze the correlation between the indicators.Logistic regression analysis was used to determine the independent risk factors of left ventricular remodeling after STEMI, and a predictive model was obtained. The diagnostic value of the model was judged by ROC curve.Results:①General information comparison: There were statistically significant differences between the two groups in BMI, systolic blood pressure, diastolic blood pressure, average number of stents implanted, and history of hyperlipidemia (all P<0.05), but there was no significant difference in other data (all P>0.05). There was no statistically significant difference in two-dimensional transthoracic echocardiography (2D-TTE) parameters and non-invasive myocardial work (MW) parameters between the two groups before and 1 week after operation (both P>0.05). ②2D-TTE parameter comparison: LVESV and LVEDV at 3 months after PCI in the LVR group were significantly higher than those in the NLVR group, and LVEF and E/A were significantly lower than those in the NLVR group (all P<0.05); There were no significant differences in other indexes between the two groups by conventional echocardiography at 3 months after PCI(all P>0.05). ③Comparisons of noninvasive myocardial work parameters: GLS, GWE, GWI, GCW at 1 month and 3 months after PCI in the LVR group were significantly lower than those in the NLVR group, and GWW were significantly higher than those in the NLVR group ( P<0.001). ④Correlation analysis: GLS, GWE, GCW, GWI and LVEDV were negatively correlated at 1 month after operation ( r=-0.42, -0.38, -0.50, -0.53, all P<0.001), GWW was positively correlated with LVEDV ( r=0.45, P<0.001). ⑤Logistic regression analysis: GLS<17%, GCW<1 900 mmHg%, GWW>105 mmHg%, and GWE<90 mmHg% at 1 month after PCI were independent predictors for LVR in STEMI patients after PCI (all P<0.05). The predictive model was Logit (P)=0.692GLS+ 0.804GCW+ 0.972GWW+ 0.880GWE. The AUC of this model was 0.886, 95% CI=0.845-0.926, which was significantly higher than single index, the sensitivity was 0.86, and the specificity was 0.79. Conclusions:GLS, GWE, GWI, GCW are positively correlated with LVR, while GWW is negatively correlated with left ventricular remodeling. Noninvasive myocardial work parameters are independent risk factors for left ventricular remodeling in patients with STEMI after PCI surgery. This technique can be used to evaluate LVR and has great clinical application value.