Conclusions: BDL rats exhibit loss of bone mass and structure, which can be prevented by the intermittent administration of hPTH 1-34, a potential therapy for osteoporosis in PBC.”
“Topological network motifs represent

functional relationships within and between regulatory and protein-protein interaction networks. Enriched motifs often aggregate into self-contained units forming functional modules. Theoretical models for network evolution by duplication-divergence mechanisms and for network topology by hierarchical scale-free networks have suggested a one-to-one relation between network motif enrichment and aggregation, but this relation has never been tested quantitatively in real biological interaction networks. Here Selleck Galardin we introduce a novel method for assessing the statistical significance of network motif aggregation and for identifying clusters of overlapping network Rabusertib chemical structure motifs. Using an integrated network of transcriptional, posttranslational

and protein-protein interactions in yeast we show that network motif aggregation reflects a local modularity property which is independent of network motif enrichment. In particular our method identified novel functional network themes for a set of motifs which are not enriched yet aggregate significantly and challenges the conventional view that network motif enrichment is the most basic organizational principle of complex networks.”
“Purpose: Monte Carlo simulations were used to investigate a range of phantom configurations

to establish enabling three-dimensional proton radiographic techniques.\n\nMethods: A large parameter space of stacked phantom geometries composed of tissue inhomogeneity materials AZD6094 ic50 such as lung, bone, and cartilage inserted within water background were simulated using a purposefully modified version of TOPAS, an application running on top of the GEANT4 Monte Carlo code. The phantoms were grouped in two classes, one with the inhomogeneity inserted only half-way in the lateral direction and another with complete inhomogeneity insertion. The former class was used to calculate the track count and the energy fluence of the protons as they exit the phantoms either having traversed the inhomogeneity or not. The latter class was used to calculate one yield value accounting for loss of protons due to physical processes only and another yield value accounting for deliberately discarded protons due to large scattering angles. A graphical fingerprinting method was developed to determine the inhomogeneity thickness and location within the phantom based on track count and energy fluence information. Two additional yield values extended this method to the general case which also determines the inhomogeneity material and the phantom thickness.