Triorganoindium reagents in Rh-catalyzed C–H activation/C–C cross-coupling reactions of 2-arylpyridines

[Abstract] The activation of C–H bonds through catalytic reactions using transition metals is an important challenge in organic chemistry in which the intermediates are related to those produced in the classical cross-coupling reactions. As part of our research program devoted to the development of metal-catalyzed reactions using indium organometallics, a protocol for the C–H activation and C–C coupling of 2-arylpyridines with triorganoindium reagents under Rh(I) catalysis is reported. Under the optimized conditions, we found that Me3In and Ar3In reagents reacted with 2-arylpyridines and related compounds in the presence of Rh(PPh3)3Cl, in PhCl/THF (9:1), at 120 °C for 48 h, to afford the ortho-coupling products in moderate to good yields. The nitrogen atom in the pyridine ring acts as a directing group to assist the functionalization at the ortho position of the aryl group forming a new C–C bond at this position.Ministerio de Economía y Competitividad; CTQ2015-68369-PXunta de Galicia; GRC2014/04

Real-time polyp detection model using convolutional neural networks

Colorectal cancer is a major health problem, where advances towards computer-aided diagnosis (CAD) systems to assist the endoscopist can be a promising path to improvement. Here, a deep learning model for real-time polyp detection based on a pre-trained YOLOv3 (You Only Look Once) architecture and complemented with a post-processing step based on an object-tracking algorithm to reduce false positives is reported. The base YOLOv3 network was fine-tuned using a dataset composed of 28,576 images labelled with locations of 941 polyps that will be made public soon. In a frame-based evaluation using isolated images containing polyps, a general F1 score of 0.88 was achieved (recall = 0.87, precision = 0.89), with lower predictive performance in flat polyps, but higher for sessile, and pedunculated morphologies, as well as with the usage of narrow band imaging, whereas polyp size < 5 mm does not seem to have significant impact. In a polyp-based evaluation using polyp and normal mucosa videos, with a positive criterion defined as the presence of at least one 50-frames-length (window size) segment with a ratio of 75% of frames with predicted bounding boxes (frames positivity), 72.61% of sensitivity (95% CI 68.99–75.95) and 83.04% of specificity (95% CI 76.70–87.92) were achieved (Youden = 0.55, diagnostic odds ratio (DOR) = 12.98). When the positive criterion is less stringent (window size = 25, frames positivity = 50%), sensitivity reaches around 90% (sensitivity = 89.91%, 95% CI 87.20–91.94; specificity = 54.97%, 95% CI 47.49–62.24; Youden = 0.45; DOR = 10.76). The object-tracking algorithm has demonstrated a significant improvement in specificity whereas maintaining sensitivity, as well as a marginal impact on computational performance. These results suggest that the model could be effectively integrated into a CAD system.Agencia Estatal de Investigación | Ref. DPI2017-87494-RXunta de Galicia | Ref. ED431C2018/55Xunta de Galicia | Ref. ED481A-2019/29