Contrast-enhanced sonography with sulfur hexafluoride microbubbles had good clinical safety, but rare adverse reactions were observed. A comprehensive emergency plan and rescue measures for adverse reactions should be prepared and made available to minimize the occurrence of negative clinical outcomes.

Updated Alpharadin in Symptomatic Prostate Cancer (ALSYMPCA) trial findings show that radium-223 remained well tolerated during treatment and up to 3 yr after each patient's first injection.

MicroRNAs (miRNAs) are some short RNAs that regulate multiple biological functions at post-transcriptional levels, such as tumorigenic processes, inflammatory lesions and cell apoptosis. Zinc finger E-box binding homeobox factor 1 (ZEB1) is a crucial mediator of epithelial-mesenchymal transition (EMT). It induces malignant progression of various cancers including human esophageal squamous-cell carcinoma (ESCC). In this study, we found that miR-128-3p was downregulated in ESCC tissues and cells by using PCR. Moreover, down-regulated expression of miR-128-3p was testified to be associated with poor prognosis of ESCC patients and might be regarded as an independent prognostic factor. Then, we examined the role of miR-128-3p in ESCC cells, and found that miR-128-3p could suppress the cell migration and invasion in vitro. Furthermore, ZEB1 was confirmed to be a direct target of miR-128-3p by luciferase reporter assay. Rescue experiments proved that EMT was regulated by miR-128-3p via suppression of ZEB1. Taken all together, we conclude that miR-128-3p suppresses EMT and metastasis via ZEB1, and miR-128-3p may be a critical mediator in ESCC.

The island sign is a reliable CT imaging marker that independently predicts hematoma expansion and poor outcome in patients with ICH. The noncontrast CT island sign may serve as a potential marker for therapeutic intervention.

Advanced and recurrent endometrial carcinoma (EC) exhibits a poor response to chemotherapy and low survival rates. It has been previously reported that human prolactin (hPRL) is upregulated in endometrial cancer and is associated with worse survival outcomes. We provide evidence for the functional role of hPRL in EC progression. We generated a model for the study of autocrine hPRL-mediated cell functional effects through the forced expression of hPRL in human EC cells. Autocrine hPRL expression stimulated cell proliferation, anchorage-independent growth, migration, and invasion of EC cells and promoted tumor growth, local invasion, and metastatic colonization in xenograft models. In addition, forced expression of hPRL decreased sensitivity of EC cells to chemotherapeutic drugs (i.e., doxorubicin and paclitaxel), both in vitro and in vivo. Consistently, small interfering RNA-mediated depletion of hPRL significantly reduced oncogenicity and enhanced the chemosensitivity of EC cells. As CD24 is hPRL-regulated and has been implicated in drug resistance in EC, we further showed that CD24 is a critical mediator of hPRL-stimulated reduced sensitivity to doxorubicin and paclitaxel in EC cells. Therefore, inhibition of hPRL signaling is a potential therapeutic strategy for the treatment of late-stage EC, which can be used in combination with chemotherapy to improve the chemotherapeutic response.

Background Computed tomography (CT) is commonly used in all stages of oesophageal squamous cell carcinoma (SCC) management. Compared to basic CT features, CT radiomic features can objectively obtain more information about intratumour heterogeneity. Although CT radiomics has been proved useful for predicting treatment response to chemoradiotherapy in oesophageal cancer, the best way to use CT radiomic biomarkers as predictive markers for determining resectability of oesophageal SCC remains to be developed. This study aimed to develop CT radiomic features related to resectability of oesophageal SCC with five predictive models and to determine the most predictive model. Methods Five hundred ninety-one patients with oesophageal SCC undergoing contrast-enhanced CT were enrolled in this study, and were composed by 270 resectable cases and 321 unresectable cases. Of the 270 resectable oesophageal SCCs, 91 cases were primary resectable tumours; and the remained 179 cases received neoadjuvant therapy after CT, shrank on therapy, and changed to resectable tumours. Four hundred thirteen oesophageal SCCs including 189 resectable cancers and 224 unresectable cancers were randomly allocated to the training cohort; and 178 oesophageal SCCs including 81 resectable tumours and 97 unresectable tumours were allocated to the validation group. Four hundred ninety-five radiomic features were extracted from CT data for identifying resectability of oesophageal SCC. Useful radiomic features were generated by dimension reduction using least absolute shrinkage and selection operator. The optimal radiomic features were chosen using multivariable logistic regression, random forest, support vector machine, X-Gradient boost and decision tree classifiers. Discriminating performance was assessed with area under receiver operating characteristic curve (AUC), accuracy and F-1score. Results Eight radiomic features were selected to create radiomic models related to resectability of oesophageal SCC (P-values < 0.01 for both cohorts). Multivariable logistic regression model showed the best performance (AUC = 0.92 ± 0.04 and 0.87 ± 0.02, accuracy = 0.87 and 0.86, and F-1score = 0.93 and 0.86 in training and validation cohorts, respectively) in comparison with any other model (P-value < 0.001). Good calibration was observed for multivariable logistic regression model. Conclusion CT radiomic models could help predict resectability of oesophageal SCC, and multivariable logistic regression model is the most predictive model.

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