Computational identification of significant actors in paintings through symbols and attributes

The automatic analysis of fine art paintings presents a number of novel technical challenges to artificial intelligence, computer vision, machine learning, and knowledge representation quite distinct from those arising in the analysis of traditional photographs. The most important difference is that many realist paintings depict stories or episodes in order to convey a lesson, moral, or meaning. One early step in automatic interpretation and extraction of meaning in artworks is the identifications of figures (actors). In Christian art, specifically, one must identify the actors in order to identify the Biblical episode or story depicted, an important step in understanding the artwork. We designed an automatic system based on deep convolutional neural networks and simple knowledge database to identify saints throughout six centuries of Christian art based in large part upon saints symbols or attributes. Our work represents initial steps in the broad task of automatic semantic interpretation of messages and meaning in fine art

Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits

Despite the recent rapid growth in genome-wide data, much of human variation remains entirely unexplained. A significant challenge in the pursuit of the genetic basis for variation in common human traits is the efficient, coordinated collection of genotype and phenotype data. We have developed a novel research framework that facilitates the parallel study of a wide assortment of traits within a single cohort. The approach takes advantage of the interactivity of the Web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design. Here we report initial results from a participant-driven study of 22 traits. Replications of associations (in the genes OCA2, HERC2, SLC45A2, SLC24A4, IRF4, TYR, TYRP1, ASIP, and MC1R) for hair color, eye color, and freckling validate the Web-based, self-reporting paradigm. The identification of novel associations for hair morphology (rs17646946, near TCHH; rs7349332, near WNT10A; and rs1556547, near OFCC1), freckling (rs2153271, in BNC2), the ability to smell the methanethiol produced after eating asparagus (rs4481887, near OR2M7), and photic sneeze reflex (rs10427255, near ZEB2, and rs11856995, near NR2F2) illustrates the power of the approach

Widespread divergence of the CEACAM/PSG genes in vertebrates and humans suggests sensitivity to selection

In mammals, carcinoembryonic antigen cell adhesion molecules (CEACAMs) and pregnancy-specific glycoproteins (PSGs) play important roles in the regulation of pathogen transmission, tumorigenesis, insulin signaling turnover, and fetal–maternal interactions. However, how these genes evolved and to what extent they diverged in humans remain to be investigated specifically. Based on syntenic mapping of chordate genomes, we reveal that diverging homologs with a prototypic CEACAM architecture–including an extracellular domain with immunoglobulin variable and constant domain-like regions, and an intracellular domain containing ITAM motif–are present from cartilaginous fish to humans, but are absent in sea lamprey, cephalochordate or urochordate. Interestingly, the CEACAM/PSG gene inventory underwent radical divergence in various vertebrate lineages: from zero in avian species to dozens in therian mammals. In addition, analyses of genetic variations in human populations showed the presence of various types of copy number variations (CNVs) at the CEACAM/PSG locus. These copy number polymorphisms have 3–80% frequency in select populations, and encompass single to more than six PSG genes. Furthermore, we found that CEACAM/PSG genes contain a significantly higher density of nonsynonymous single nucleotide polymorphism (SNP) compared to the chromosome average, and many CEACAM/PSG SNPs exhibit high population differentiation. Taken together, our study suggested that CEACAM/PSG genes have had a more dynamic evolutionary history in vertebrates than previously thought. Given that CEACAM/PSGs play important roles in maternal–fetal interaction and pathogen recognition, these data have laid the groundwork for future analysis of adaptive CEACAM/PSG genotype-phenotypic relationships in normal and complicated pregnancies as well as other etiologies.Chia Lin Chang, Jenia Semyonov, Po Jen Cheng, Shang Yu Huang, Jae Il Park, Huai-Jen Tsai, Cheng-Yung Lin, Frank Grützner, Yung Kuei Soong, James J. Cai, Sheau Yu Teddy Hs