Unsupervised Triplet Hashing for Fast Image Retrieval

Hashing has played a pivotal role in large-scale image retrieval. With the development of Convolutional Neural Network (CNN), hashing learning has shown great promise. But existing methods are mostly tuned for classification, which are not optimized for retrieval tasks, especially for instance-level retrieval. In this study, we propose a novel hashing method for large-scale image retrieval. Considering the difficulty in obtaining labeled datasets for image retrieval task in large scale, we propose a novel CNN-based unsupervised hashing method, namely Unsupervised Triplet Hashing (UTH). The unsupervised hashing network is designed under the following three principles: 1) more discriminative representations for image retrieval; 2) minimum quantization loss between the original real-valued feature descriptors and the learned hash codes; 3) maximum information entropy for the learned hash codes. Extensive experiments on CIFAR-10, MNIST and In-shop datasets have shown that UTH outperforms several state-of-the-art unsupervised hashing methods in terms of retrieval accuracy

Two variants on T2DM susceptible gene HHEX are associated with CRC risk in a Chinese population

Increasing amounts of evidence has demonstrated that T2DM (Type 2 Diabetes Mellitus) patients have increased susceptibility to CRC (colorectal cancer). As HHEX is a recognized susceptibility gene in T2DM, this work was focused on two SNPs in HHEX, rs1111875 and rs7923837, to study their association with CRC. T2DM patients without CRC (T2DM-only, n=300), T2DM with CRC (T2DM/CRC, n=135), cancer-free controls (Control, n=570), and CRC without T2DM (CRC-only, n=642) cases were enrolled. DNA samples were extracted from the peripheral blood leukocytes of the patients and sequenced by direct sequencing. The χ(2) test was used to compare categorical data. We found that in T2DM patients, rs1111875 but not the rs7923837 in HHEX gene was associated with the occurrence of CRC (p= 0.006). for rs1111875, TC/CC patients had an increased risk of CRC (p=0.019, OR=1.592, 95%CI=1.046-2.423). Moreover, our results also indicated that the two variants of HEEX gene could be risk factors for CRC in general population, independent on T2DM (p< 0.001 for rs1111875, p=0.001 for rs7923837). For rs1111875, increased risk of CRC was observed in TC or TC/CC than CC individuals (p<0.001, OR= 1.780, 95%CI= 1.385-2.287; p<0.001, OR= 1.695, 95%CI= 1.335-2.152). For rs7923837, increased CRC risk was observed in AG, GG, and AG/GG than AA individuals (p< 0.001, OR= 1.520, 95%CI= 1.200-1.924; p=0.036, OR= 1.739, 95%CI= 0.989-3.058; p< 0.001, OR= 1.540, 95%CI= 1.225-1.936). This finding highlights the potentially functional alteration with HHEX rs1111875 and rs7923837 polymorphisms may increase CRC susceptibility. Risk effects and the functional impact of these polymorphisms need further validation

Talatisamine, a C19-diterpenoid alkaloid from Chinese traditional herbal ‘Chuanwu’

The title compound [systematic name: (1S,4S,5R,7S,8S,9R,10R,11S,13S,14S,16S,17R)-N-methyl-8,14-dihy­droxy-1,16-tri­meth­oxy-4-(meth­oxy­methyl­ene)aconitane], C24H39NO5, was isolated from the roots of Aconitum carmichaelii Debx., which is known as ‘Chuanwu’ in Chinese traditional herbal medicine. The mol­ecule has an aconitane carbon skeleton with four six-membered rings and two five-membered rings, including a six-membered N-containing heterocyclic ring. Both five-membered rings adopt envelope conformations. The four six-membered adopt chair conformations. Two intra­molecular O—H⋯O hydrogen bonds occur