01). A nomogram that consisted of Rad scores, CT-reported parenchymal atrophy, and CT-reported LN status performed well in terms of predictive power in the training cohort (area under the curve, 0.92), and this was confirmed in the validation cohort (area under the curve, 0.95). The nomogram also performed well in the calibration test and decision curve analysis, demonstrating its potential clinical value.
 
  A multidimensional radiomics nomogram consisting of Rad scores, CT-reported parenchymal atrophy, and CT-reported LN status may contribute to the non-invasive evaluation of LN status in PDAC patients.
 A multidimensional radiomics nomogram consisting of Rad scores, CT-reported parenchymal atrophy, and CT-reported LN status may contribute to the non-invasive evaluation of LN status in PDAC patients.We present the genetic profile of kidney giant leiomyosarcoma characterized by sequencing of 409 cancer related genes and chromosomal microarray analysis. Renal leiomyosarcomas are extremely rare neoplasms with aggressive behavior and poor survival prognosis. Most frequent somatic events in leiomyosarcomas are mutations in the TP53, RB1, ATRX, and PTEN genes, chromosomal instability (CIN) and chromoanagenesis. 67-year-old woman presented with a right kidney completely replaced by tumor. Immunohistochemical reaction on surgical material was positive to desmin and smooth muscle actin. Molecular genetic analysis revealed that tumor harbored monosomy of chromosomes 3 and 11, gain of Xp (ATRX) arm and three chromoanasynthesis regions (6q21-q27, 7p22.3-p12.1, and 12q13.11-q21.2), with MDM2 and CDK4 oncogenes copy number gains, whereas no copy number variations (CNVs) or tumor specific single nucleotide variants (SNVs) in TP53, RB1, and PTEN genes were present. We hypothesize that chromoanasynthesis in 12q13.11-q21.2 could be a trigger of observed CIN in this tumor.Objective To define the effectiveness of different anastomosis on clinically relevant postoperative fistula in patients with soft pancreas using the newest version of the fistula definition and criteria. Background Different criteria of clinically relevant postoperative pancreatic fistula (POPF) result in the optimal anastomosis technique remaining controversial. Methods PubMed, Embase, Web of Science, the Cochrane Central Library, and ClinicalTrials.gov were systematically searched up to 20 April 2020, and were evaluated by Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Randomized controlled trials comparing duct-to-mucosa anastomosis vs. invagination anastomosis in pancreatic surgery were included. Result Seven studies involving 1,110 participants were included. Using the postoperative pancreatic fistula definition provided by the International Study Group of Pancreatic Surgery 2016, the incidence rate of grade B/C pancreatic fistula was significantly lower in patien two anastomosis techniques in patients with a hard pancreas. We found a lower rate of clinically relevant postoperative pancreatic fistula in the invagination group, in patients with a soft pancreas.Osteosarcoma is one of the most aggressive malignant bone tumors worldwide. Although great advancements have been made in its treatment owing to the advent of neoadjuvant chemotherapy, the problem of lung metastasis is a major obstacle in the improvement of survival outcomes. Thus, the aim of the present study is to screen novel and key biomarkers, which may act as potential prognostic markers and therapeutic targets in osteosarcoma. We utilized the robust rank aggregation (RRA) method to integrate three osteosarcoma microarray datasets downloaded from the Gene Expression Omnibus (GEO) database, and we identified the robust differentially expressed genes (DEGs) between primary and metastatic osteosarcoma tissues.  https://www.selleckchem.com/products/cl-amidine.html  Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functions of robust DEGs. The results of enrichment analysis showed that the robust DEGs were closely associated with osteosarcoma development and progression. Immune cell infiltration analysis was also conducted by CIBERSORT algorithm, and we found that macrophages are the most principal infiltrating immune cells in osteosarcoma, especially macrophages M0 and M2. Then, the protein-protein interaction network and key modules were constructed by Cytoscape, and 10 hub genes were selected by plugin cytoHubba from the whole network. The survival analysis of hub genes was also carried out based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The integrated bioinformatics analysis was utilized to provide new insight into osteosarcoma development and metastasis and identified EGR1, CXCL10, MYC, and CXCR4 as potential biomarkers for prognosis of osteosarcoma.
  To develop and validate a radiomics model of diffusion kurtosis imaging (DKI) and T2 weighted imaging for discriminating pancreatic neuroendocrine tumors (PNETs) from solid pseudopapillary tumors (SPTs).
 
  Sixty-six patients with histopathological confirmed PNETs (
  = 31) and SPTs (
  = 35) were enrolled in this study. ROIs of tumors were manually drawn on each slice at T2WI and DWI (
  = 1,500 s/mm
  ) from 3T MRI. Intraclass correlation coefficients were used to evaluate the interobserver agreement. Mean diffusivity (MD) and mean kurtosis (MK) were derived from DKI. The least absolute shrinkage and selection operator regression were used for feature selection.
 
  MD and MK had a moderate diagnostic performancewith the area under curve (AUC) of 0.71 and 0.65, respectively. A radiomics model, which incorporated sex and age of patients and radiomics signature of the tumor, showed excellent discrimination performance with AUC of 0.97 and 0.86 in the primary and validation cohort. Moreover, the new model had better diagnostic performance than that of MD (
  = 0.023) and MK (
  = 0.004), and showed excellent differentiation with a sensitivity of 95.00% and specificity of 91.67% in primary cohort, and the sensitivity of 90.91% and specificity of 81.82% in the validation cohort. The accuracy of radiomics analysis, radiologist 1, and radiologist 2 for diagnosing SPTs and PNETs were 92.42, 77.27, and 78.79%, respectively. The accuracy of radiomics analysis was significantly higher than that of subjective diagnosis (
  < 0.05).
 
  Radiomics model could improve the diagnostic accuracy of SPTs and PNETs and contribute to determining an appropriate treatment strategy for pancreatic tumors.
 Radiomics model could improve the diagnostic accuracy of SPTs and PNETs and contribute to determining an appropriate treatment strategy for pancreatic tumors.