No abstract

No abstract

Background The aim of this study was to quantitatively measure the morphology of the patellofemoral joint by magnetic resonance imaging (MRI) in young adults, to investigate the relationship between the morphology of the patellofemoral joint and chondromalacia patellae (CP), and to provide an imaging reference for early clinical diagnosis of CP. Methods A total of 57 cases of CP and 138 cases of normal knees were retrospectively collected and assigned to the CP group and control group, respectively. The morphological parameters of the patellofemoral joint were measured systematically. The statistical software SPSS 22.0 was used in correlation analysis. Logistic regression was used for univariate analysis. A P value <0.05 was defined as statistically significant. Results Wiberg index, patellar depth, and the lateral angle of the patella in the CP group were significantly lower than those in the control group (P=0.043, 0.001, 0.040, respectively). The width of the medial side of the trochlea, the ratio of the internal and external articular surfaces of the trochlea, the depth of the trochlea, and the inclination angle of the lateral trochlea in the CP group were significantly lower than those in the control group (P=0.003, 0.020, 0.000, 0.040, respectively), whereas the angle of the trochlea in the CP group was significantly higher than that in the control group (P=0.010). The lateral patellofemoral angle (LPA) and lateral patellofemoral contact width in the CP group were significantly lower than those in the control group (P=0.010, 0.010, respectively). In the CP group, with gender as a covariate, there were significant statistical differences between male and female in patellar depth, lateral patellar inclination angle, lateral trochlear inclination (LTI) angle, and lateral patellar contact surface width (P<0.05), whereas in the control group, there were significant differences in Wiberg index, patellar depth, medial trochlear width, and lateral patellofemoral contact surface width between male and female gender (P<0.05). Conclusions The prevalence of CP in women was significantly higher than that in men and the reduction of trochlea width and the patella depth is an important factor for the incidence of female CP. Morphological characteristics of the patellofemoral joint are significantly correlated with the occurrence of CP in young adults.

BackgroundCOVID-19, a worldwideinfectious disease, has killed more than 420000 people, whichis extremely harmful.MethodsIn this single-center retrospective study, we included the novel coronavirus pneumonia confirmed in our hospital. This study collected the basic information andclinical examination features.ResultsThe enrolled 704 patients were affirmed infected with 2019-nCoV by the test of throat swabs. There are 334 men and 369 women, and gender, age, combined with basic diseasesare distinct in diverse disease classification (p<0.05). From the symptom analysis, the proportion of fever over 38 degrees, dyspnea, fatigue, poor appetite and other symptoms is diverse in different types of diseases (p<0.05). As the severity of the disease increases, the median lymphocyte count decreases, C-reactive protein increase, erythrocyte sedimentation rateincrease, albumin decrease, pleural effusion increase, D-Dimer and NT-proBNP increase significantly (p<0.05).As the disease severity increases, the average value of MuLBSTA score obviously ascend (p<0.05), MuLBSTA scoring system predicts novel coronavirus pneumonia patients' prognosis is still insufficient, and may require additional indicators including anorexia, fatigue, C reactive protein, etc (p<0.05).ConclusionThe MuLBSTA evaluation system has certain value for the evaluation of the disease, but it needs to be improved.

The physical properties and mechanical characteristics of storage materials are significantly different from those of ordinary solids and liquids. The distribution of dynamic wall pressure during silo discharge is quite complicated. Considering the nonlinear relationship between the factors which affect the dynamic lateral pressure of silos, a prediction method of dynamic wall pressure for silos based on support vector machine (SVM) is proposed here, and furthermore, the modified grid search method (GSM) is incorporated in obtaining the optimal support vector machine parameters to improve the accuracy of the prediction. Comparing the results of the proposed prediction model with the results of experiment methods and simulation methods, it can be found that the SVM prediction model shows high accuracy and high generalization ability, and the prediction results of the model fit well with the results of experiment and simulation methods. The proposed method can provide reference for the prediction of the dynamic wall pressure of silos.