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Rationale and Objectives: We assess the performance of a model combining a deep convolutional neural network and a hand-crafted radiomics signature for predicting KRAS status in patients with colorectal cancer (CRC).Materials and Methods: The primary cohort consisted of 279 patients with clinicopathologically confirmed CRC between April 2011 and April 2015. Portal venous phase computed tomographic images were analyzed to extract traditional hand-crafted radiomics features as well as deep learning features. A Wilcoxon rank sum test, the minimum redundancy maximum relevance algorithm, and multivariable logistic regression analysis were used to select features and build a radiomics signature. A combined model was then developed using multivariable logistic regression analysis. An independent validation cohort of 119 patients from May 2015 to April 2016 was used to confirm the combined model's predictive performance.Results: The C-index of hand-crafted radiomics signature's discriminative ability was 0.719 (95% confidence interval, CI: 0.658-0.776) for the primary cohort and 0.720 (95% CI: 0.625-0.813) for the validation cohort. The C-index of the deep radiomics signature's discriminative ability was 0.754 (95% CI: 0.696-0.813) for the primary cohort and 0.786 (95% CI: 0.702-0.863) for the validation cohort. The combined model, which merged the hand-crafted radiomics features and deep radiomics features, achieve a C-index of 0.815 (95% CI: 0.766-0.868) for the primary cohort and 0.832 (95% CI: 0.762-0.905) for the validation cohort.Conclusion: This study presents a model that incorporates the hand-crafted and deep radiomics signature, which can be used for individualized preoperative prediction of KRAS mutations in patients with CRC. [ABSTRACT FROM AUTHOR]

This study was conducted to determine the prevalence of integrons and associated gene cassettes in Escherichia coli (E. coli) isolates from waterfowls in Hainan, China. The antimicrobial resistance profile of the isolates was examined by using disc diffusion test. In addition, PCR, RFLP, plasmid replicon typing and DNA sequencing analyses were used for the characterization of integrase genes (class 1, 2 and 3) and associated gene cassettes. Approximatively, 90% of the isolates were positive for the integrase genes by PCR. Specifically, class 1 and class 2 integrons were found in 252 (81%) and 7 (2.3%) strains, respectively. While 21 (6.7%) isolates were positive for both class 1 and class 2 integrons. However, none of the isolate was positive for the class 3 integrons. In addition, 5 various cassette arrays, dfrA1-orfC, aadA2, aadA1, dfrA1-aadA1, and dfrA1-orfC- aadA1, were found within the variable regions (VRs) of class 1 integron isolates. While only single cassette array, dfrA1-sat2- aadA1, was identified within VRs of class 2 integron isolates. We identified incF plasmid as the most common plasmid type, which was detected in 81 of 243 VRs containing isolates. This study is the first report showing the baseline characteristics of integrons in E. coli isolates from waterfowls in Hainan, China. Our results provide evidence of the waterfowl birds as a reservoir of class 1 and class 2 integrons carrying antibiotic resistance gene cassettes. Therefore, strict preventive measures should be taken to avoid the spread of mobile genetic resistance elements in waterfowls in China. Image 1 • Prevalence of class 1, class 2 and class 3 integrons were studied in waterfowl farms. • The waterfowl birds are possible reservoirs of AMRg and integrons. • AMRg were found in various gene cassettes harboring IncF plasmids. • The significant correlations among AMR phenotypes and integrons were detected. [ABSTRACT FROM AUTHOR]