No abstract

A semiphenomenological elastic theory for ionic clustering is proposed. The free energy of the system is obtained by assuming the elastic energy necessary to create the volume in the matrix for the hydrated cluster is balanced by the energy produced by the favorable hydrophilic interactions at the surface and in the cluster interior. An expression for the cluster diameter is obtained by minimizing this free energy. This expression correctly describes the experimental variation in cluster diameter with cation form, equivalent weight, and water content which has been reported recently for one perfluorinated ionomer.1 The model also predicts that short channels connecting adjacent clusters are thermodynamically stable, in support of the cluster-network model proposed by us earlier.2

No abstract

No abstract

Meta-analysis of current literature shows T&A offers prominent improvement in a variety of sleep parameters. Improvements in non-obese children exceeded those for obese children. Postoperative residual OSA remained in roughly half of the children, especially those with severe disease and obesity, making additional treatment strategies and/or long-term follow-up highly desirable.

More detailed information about T and N classification of NPC was provided by MRI than by CT, which led to better target delineation for radiotherapy.

No abstract

BackgroundTo appraise the ability of a radiomics based analysis to predict local response and overall survival for patients with hepatocellular carcinoma.MethodsA set of 138 consecutive patients (112 males and 26 females, median age 66 years) presented with Barcelona Clinic Liver Cancer (BCLC) stage A to C were retrospectively studied. For a subset of these patients (106) complete information about treatment outcome, namely local control, was available. Radiomic features were computed for the clinical target volume. A total of 35 features were extracted and analyzed. Univariate analysis was used to identify clinical and radiomics significant features. Multivariate models by Cox-regression hazards model were built for local control and survival outcome. Models were evaluated by area under the curve (AUC) of receiver operating characteristic (ROC) curve. For the LC analysis, two models selecting two groups of uncorrelated features were analyzes while one single model was built for the OS analysis.ResultsThe univariate analysis lead to the identification of 15 significant radiomics features but the analysis of cross correlation showed several cross related covariates. The un-correlated variables were used to build two separate models; both resulted into a single significant radiomic covariate: model-1: energy p < 0.05, AUC of ROC 0.6659, C.I.: 0.5585–0.7732; model-2: GLNU p < 0.05, AUC 0.6396, C.I.:0.5266–0.7526.The univariate analysis for covariates significant with respect to local control resulted in 9 clinical and 13 radiomics features with multiple and complex cross-correlations. After elastic net regularization, the most significant covariates were compacity and BCLC stage, with only compacity significant to Cox model fitting (Cox model likelihood ratio test p < 0.0001, compacity p < 0.00001; AUC of the model is 0.8014 (C.I. = 0.7232–0.8797)).ConclusionA robust radiomic signature, made by one single feature was finally identified. A validation phases, based on independent set of patients is scheduled to be performed to confirm the results.