No abstract

In patients undergoing video-assisted thoracoscopic surgery, intraoperative urinary output and postoperative renal function are not affected by administration of fluids in the range of 2 to 8 mL/(kg · h). The clinical practice of administering fluids to enhance diuresis in the perioperative period should therefore be abandoned.

CXCR4 expression in neuroblastoma tumors correlates with disease severity. In this study, we describe mechanisms by which CXCR4 signaling controls neuroblastoma tumor growth and response to therapy. We found that overexpression of CXCR4 or stimulation with CXCL12 supports neuroblastoma tumorigenesis. Moreover, CXCR4 inhibition with the high-affinity CXCR4 antagonist BL-8040 prevented tumor growth and reduced survival of tumor cells. These effects were mediated by the upregulation of miR-15a/16-1, which resulted in downregulation of their target genes BCL-2 and cyclin D1, as well as inhibition of ERK. Overexpression of miR-15a/16-1 in cells increased cell death, whereas antagomirs to miR-15a/16-1 abolished the proapoptotic effects of BL-8040. CXCR4 overexpression also increased miR-15a/16-1, shifting their oncogenic dependency from the BCL-2 to the ERK signaling pathway. Overall, our results demonstrate the therapeutic potential of CXCR4 inhibition in neuroblastoma treatment and provide a rationale to test combination therapies employing CXCR4 and BCL-2 inhibitors to increase the efficacy of these agents. These results provide a mechanistic rationale for combination therapy of CXCR4 and BCL-2 inhibitors to treat a common and commonly aggressive pediatric cancer..

We present a novel method for the automatic classification and grading of liver fibrosis based on hepatic hemodynamic changes measured noninvasively from functional MRI (fMRI) scans combined with hypercapnia and hyperoxia. The supervised learning method automatically creates a classification and grading model for liver fibrosis grade from training datasets. It constructs a statistical model of liver fibrosis by evaluating the signal intensity time course and local variance in T2(*)-W fMRI scans acquired during the breathing of air, air-carbon dioxide, and carbogen with a hierarchical multiclass binary-based support vector machine (SVM) classifier. Two experimental studies on 162 slices from 34 mice with the hierarchical multiclass binary-based SVM classifier yield 96.9% separation accuracy between healthy and histological-based fibrosis graded subjects, and an overall accuracy of 75.3% for healthy, fibrotic, and cirrhotic subjects. These results outperform existing image-based methods that can discriminate between healthy and mild-grade fibrosis subjects.