No abstract

Background The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and approximately 40% of tumours smaller than 2 cm evade detection. Convolutional neural networks (CNNs) have shown promise in image analysis, but the networks' potential for pancreatic cancer detection and diagnosis is unclear. We aimed to investigate whether CNN could distinguish individuals with and without pancreatic cancer on CT, compared with radiologist interpretation. MethodsIn this retrospective, diagnostic study, contrast-enhanced CT images of 370 patients with pancreatic cancer and 320 controls from a Taiwanese centre were manually labelled and randomly divided for training and validation (295 patients with pancreatic cancer and 256 controls) and testing (75 patients with pancreatic cancer and 64 controls; local test set 1). Images were preprocessed into patches, and a CNN was trained to classify patches as cancerous or non-cancerous. Individuals were classified as with or without pancreatic cancer on the basis of the proportion of patches diagnosed as cancerous by the CNN, using a cutoff determined using the training and validation set. The CNN was further tested with another local test set (101 patients with pancreatic cancers and 88 controls; local test set 2) and a US dataset (281 pancreatic cancers and 82 controls). Radiologist reports of pancreatic cancer images in the local test sets were retrieved for comparison.

Genetic manipulation of cells for desired traits is the most appreciable strategy implemented in the field of bioengineering. However, this approach closely relies on the use of plasmids and is commonly afflicted by the potential problem of plasmid instability and safety caution. Meanwhile, it may also lead to the spread of antibiotic-resistant markers with replicons of plasmids to the environment. However, this issue has long been neglected. In this study, we have addressed these subjects by developing replicon-free and markerless methods for chromosomal insertion of genes and controlled expression of genomic genes in Escherichia coli. For the former application, the integration vectors of conditional replication were incorporated with the prophage attachment site and duplicated FRT sites. Their utility was illustrated by site-specific insertion of target genes, the endogenous dxs gene and three heterologous genes consisting of gps, crtI, and crtB, fused to T7 promoter into E. coli genome. For the latter application, the template vectors for promoter replacement were constructed to carry a DNA cassette containing the T7 promoter linked to a selective marker flanked with the FRT site. Subsequently, it was illustrated by replacement of the native promoter of chromosomal pckA by the T7 promoter. Finally, with the aid of FLP recombinase supplied from a helper plasmid, the regions containing replicon and/or selective markers in inserted DNAs were eliminated from integrants for both approaches. As a consequence, the expression of these five genes was subject to control by one response regulator, T7 RNA polymerase, in a regulon way, resulting in a high and stable production of lycopene in the cell. This result indicates the promise of developed methods for genome engineering in E. coli.

A thermophilic Geobacillus bacterium secreting high activity of endo-glucanase (EC 3.2.1.4) was isolated from rice straw compost supplemented with pig manure. A full-length gene of 1,104 bp, celA, encoding this glycosyl hydrolase family 5 endo-glucanase of 368 amino acids was isolated. No related gene from Geobacillus has been reported previously. The recombinant CelA expressed in Escherichia coli had an optimal activity at 65 degrees C and pH 5.0, and it exhibited tenfold greater specific activity than the commercially available Trichoderma reesei endo-glucanase. CelA displayed activity over a broad temperature range from 45 to 75 degrees C and was a thermostable enzyme with 90% activity retained after heating at 65 degrees C for 6 h. Interestingly, CelA activity could be enhanced by 100% in the presence of 2 mM MnSO(4). CelA had high specific activity over beta-D-glucan from barley and Lichenan, making it a potentially useful enzyme in biofuel and food industries.