The Relationship Between LRP-5 and LRP-6 Gene Mutations and Postmenopausal Type 2 Diabetes and Obesity.

Background: Single nucleotide polymorphisms (SNPs) in the low-density lipoprotein receptor-related protein 5 (LRP5) and the low-density lipoprotein receptor-related protein 5 (LRP6) genes have been implicated in the pathogenesis of type 2 diabetes mellitus (T2DM) and obesity (OB). This study aimed to evaluate the polymorphisms in LRP5 and LRP6 genes in postmenopausal patients with T2DM and OB.

Methods: Participants were categorized into the Non-T2DM group (n = 53) and the T2DM group (n = 89) based on glycemic levels.

SynSig2Vec: Forgery-Free Learning of Dynamic Signature Representations by Sigma Lognormal-Based Synthesis and 1D CNN.

Handwritten signature verification is a challenging task because signatures of a writer may be skillfully imitated by a forger. As skilled forgeries are generally difficult to acquire for training, in this paper, we propose a deep learning-based dynamic signature verification framework, SynSig2Vec, to address the skilled forgery attack without training with any skilled forgeries. Specifically, SynSig2Vec consists of a novel learning-by-synthesis method for training and a 1D convolutional neural network model, called Sig2Vec, for signature representation extraction.