The central pathway of primary olfactory axons is abnormal in mice lacking the N-CAM-180 isoform

Although N-CAM has previously been implicated in the growth and fasciculation of axons, the development of axon tracts in transgenic mice with a targeted deletion of the 180-kD isoform of the neural cell adhesion molecule (N-CAM-180) appears grossly normal in comparison to wild-type mice. We examined the organization of the olfactory nerve projection from the olfactory neuroepithelium to glomeruli in the olfactory bulb of postnatal N-CAM-180 null mutant mice. Immunostaining for olfactory marker protein revealed the normal presence of fully mature primary olfactory neurons within the olfactory neuroepithelium of mutant mice. The axons of these neurons form an olfactory nerve, enter the nerve fiber layer of the olfactory bulb, and terminate in olfactory glomeruli as in wild-type control animals. The olfactory bulb is smaller and the nerve fiber layer is relatively thicker in mutants than in wild-type mice. Previous studies have revealed that the plant lectin Dolichos biflorus agglutinin (DBA) clearly stains the perikarya and axons of a subpopulation of primary olfactory neurons. Thus, DBA staining enabled the morphology of the olfactory nerve pathway to be examined at higher resolution in both control and mutant animals. Despite a normal spatial pattern of DBA-stained neurons within the nasal cavity, there was a distorted axonal projection of these neurons onto the surface of the olfactory bulb in N-CAM-180 null mutants. In particular, DBA-stained axons formed fewer and smaller glomeruli in the olfactory bulbs of mutants in comparison to wild-type mice. Many primary olfactory axons failed to exit the nerve fiber layer and contribute to glomerular formation. These results indicate that N-CAM-180 plays an important role in the growth and fasciculation of primary olfactory axons and is essential for normal development of olfactory glomeruli. (C) 1997 John Wiley & Sons, Inc.

Critical comparison of Julius Kruttschnitt Mineral Research Centre (JKMRC) blast fragmentation models

Blast fragmentation can have a significant impact on the profitability of a mine. An optimum run of mine (ROM) size distribution is required to maximise the performance of downstream processes. If this fragmentation size distribution can be modelled and controlled, the operation will have made a significant advancement towards improving its performance. Blast fragmentation modelling is an important step in Mine to Mill™ optimisation. It allows the estimation of blast fragmentation distributions for a number of different rock mass, blast geometry, and explosive parameters. These distributions can then be modelled in downstream mining and milling processes to determine the optimum blast design. When a blast hole is detonated rock breakage occurs in two different stress regions - compressive and tensile. In the-first region, compressive stress waves form a 'crushed zone' directly adjacent to the blast hole. The second region, termed the 'cracked zone', occurs outside the crush one. The widely used Kuz-Ram model does not recognise these two blast regions. In the Kuz-Ram model the mean fragment size from the blast is approximated and is then used to estimate the remaining size distribution. Experience has shown that this model predicts the coarse end reasonably accurately, but it can significantly underestimate the amount of fines generated. As part of the Australian Mineral Industries Research Association (AMIRA) P483A Mine to Mill™ project, the Two-Component Model (TCM) and Crush Zone Model (CZM), developed by the Julius Kruttschnitt Mineral Research Centre (JKMRC), were compared and evaluated to measured ROM fragmentation distributions. An important criteria for this comparison was the variation of model results from measured ROM in the-fine to intermediate section (1-100 mm) of the fragmentation curve. This region of the distribution is important for Mine to Mill™ optimisation. The comparison of modelled and Split ROM fragmentation distributions has been conducted in harder ores (UCS greater than 80 MPa). Further work involves modelling softer ores. The comparisons will be continued with future site surveys to increase confidence in the comparison of the CZM and TCM to Split results. Stochastic fragmentation modelling will then be conducted to take into account variation of input parameters. A window of possible fragmentation distributions can be compared to those obtained by Split . Following this work, an improved fragmentation model will be developed in response to these findings.