Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

Novel Genetic Determinants of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a devastating diabetes complication, with known heritability not fully revealed by previous genetics studies. We performed the largest genome-wide association study of type 1 DKD to date, in a 13-cohort consortium of 15,590 individuals of European ancestry genotyped on the Illumina HumanCoreExome Beadchip, which allows exploration of coding variation in addition to genomic markers.

As prior work has shown that different characterizations of the DKD phenotype highlight distinct genetic associations, we investigated a spectrum of DKD definitions based on proteinuria and renal function criteria. Controls were DKD-free after a minimum of 15 years diabetes duration; cases had diabetes for at least 10 years prior to DKD diagnosis. We also performed a quantitative trait analysis of estimated glomerular filtration rate in all participants.

Our top finding was a missense mutation in COL4A3, rs55703767 (Asp326Tyr); the minor allele is common in Europeans (20%) and East Asians (13%) but not Africans (2%). This SNP had a genome-wide significant association with traditionally defined DKD (macroalbuminuria or end-stage renal disease [ESRD], (OR= 0.79, P=1.9×10-9), and a suggestive association with macroalbuminuria (OR= 0.79, P=1.6×10-6) and ESRD (OR= 0.79, P=4.5×10-5) individually. Though its PolyPhen score is 0.3 (benign), this SNP has been implicated as a splice site disruptor.

The COL4A3 gene encodes the alpha 3 subunit of Type IV collagen, the major structural component of basement membranes. Pathogenic mutations in COL4A3 have been identified in thin basement membrane nephropathy, familial focal segmental glomerulosclerosis, and Alport syndrome. A proxy (r2=0.6) for rs55703767 had no significant associations in the CKDGen consortium, suggesting its pathogenicity occurs solely in the setting of hyperglycemia.

By significantly increasing sample size we have discovered a novel locus underlying DKD risk, paving the way for better understanding of pathology, prevention, and treatment.