During neural circuit formation, most axons are guided to complex environments, coming into contact with multiple potential synaptic partners. However, it is critical that they recognize specific neurons with which to form synapses. Here, we utilize the split GFP-based marker Neuroligin-1 GFP Reconstitution Across Synaptic Partners (NLG-1 GRASP) to visualize specific synapses in live animals, and a circuit-specific behavioral assay to probe circuit function. We demonstrate that the receptor protein tyrosine phosphatase (RPTP) clr-1 is necessary for synaptic partner recognition (SPR) between the PHB sensory neurons and the AVA interneurons in C. elegans. Mutations in clr-1/RPTP result in reduced NLG-1 GRASP fluorescence and impaired behavioral output of the PHB circuit. Temperature-shift experiments demonstrate that clr-1/RPTP acts early in development, consistent with a role in SPR. Expression and cell-specific rescue experiments indicate that clr-1/RPTP functions in postsynaptic AVA neurons, and overexpression of clr-1/RPTP in AVA neurons is sufficient to direct additional PHB-AVA synaptogenesis. Genetic analysis reveals that clr-1/RPTP acts in the same pathway as the unc-6/Netrin ligand and the unc-40/DCC receptor, which act in AVA and PHB neurons, respectively. This study defines a new mechanism by which SPR is governed, and demonstrates that these three conserved families of molecules, with roles in neurological disorders and cancer, can act together to regulate communication between cells.

Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator "opening" can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. Unfortunately, aggregate grain surfaces lead to pore anisotropy. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), presented herein, and random node structuring (RaNoS) provide such information. The latter method will be introduced in a next issue of Image Anal Stereol.

No abstract

Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of the aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator "opening" can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. However, aggregate grain surfaces lead to anisotropy in porosity. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Doublerandom multiple tree structuring (DRaMuTS), introduced earlier in this journal and random node structuring (RaNoS) provide such information.

No abstract