Transplantation of human fetal blood stem cells in the osteogenesis imperfecta mouse leads to improvement in multiscale tissue properties.

Osteogenesis imperfecta (OI or brittle bone disease) is a disorder of connective tissues caused by mutations in the collagen genes. We previously showed that intrauterine transplantation of human blood fetal stem/stromal cells in OI mice (oim) resulted in a significant reduction of bone fracture. This work examines the cellular mechanisms and mechanical bone modifications underlying these therapeutic effects, particularly examining the direct effects of donor collagen expression on bone material properties. In this study, we found an 84% reduction in femoral fractures in transplanted oim mice. Fetal blood stem/stromal cells engrafted in bones, differentiated into mature osteoblasts, expressed osteocalcin, and produced COL1a2 protein, which is absent in oim mice. The presence of normal collagen decreased hydroxyproline content in bones, altered the apatite crystal structure, increased the bone matrix stiffness, and reduced bone brittleness. In conclusion, expression of normal collagen from mature osteoblast of donor origin significantly decreased bone brittleness by improving the mechanical integrity of the bone at the molecular, tissue, and whole bone levels.

Multiscale analysis of factors that affect the distribution of sharks throughout the northern Gulf of Mexico

Identification of the spatial scale at which marine communities are organized is critical to proper management, yet this is particularly difficult to determine for highly migratory species like sharks. We used shark catch data collected during 2006–09 from fishery-independent bottom-longline surveys, as well as biotic and abiotic explanatory data to identify the factors that affect the distribution of coastal sharks at 2 spatial scales in the northern Gulf of Mexico. Centered principal component analyses (PCAs) were used to visualize the patterns that characterize shark distributions at small (Alabama and Mississippi coast) and large (northern Gulf of Mexico) spatial scales. Environmental data on temperature, salinity, dissolved oxygen (DO), depth, fish and crustacean biomass, and chlorophyll-a (chl-a) concentration were analyzed with normed PCAs at both spatial scales. The relationships between values of shark catch per unit of effort (CPUE) and environmental factors were then analyzed at each scale with co-inertia analysis (COIA). Results from COIA indicated that the degree of agreement between the structure of the environmental and shark data sets was relatively higher at the small spatial scale than at the large one. CPUE of Blacktip Shark (Carcharhinus limbatus) was related positively with crustacean biomass at both spatial scales. Similarly, CPUE of Atlantic Sharpnose Shark (Rhizoprionodon terraenovae) was related positively with chl-a concentration and negatively with DO at both spatial scales. Conversely, distribution of Blacknose Shark (C. acronotus) displayed a contrasting relationship with depth at the 2 scales considered. Our results indicate that the factors influencing the distribution of sharks in the northern Gulf of Mexico are species specific but generally transcend the spatial boundaries used in our analyses.

Development of low entropy coding in a recurrent network.

In this paper we present an unsupervised neural network which exhibits competition between units via inhibitory feedback. The operation is such as to minimize reconstruction error, both for individual patterns, and over the entire training set. A key difference from networks which perform principal components analysis, or one of its variants, is the ability to converge to non-orthogonal weight values. We discuss the network's operation in relation to the twin goals of maximizing information transfer and minimizing code entropy, and show how the assignment of prior probabilities to network outputs can help to reduce entropy. We present results from two binary coding problems, and from experiments with image coding.