Recommendations for the categorization of germ cell mutagens

Germ cell mutagens are currently classified into three categories in the German List of MAK- and BAT-Values. These categories have been revised and extended in analogy to the new categories for carcinogenic chemicals. Germ cell mutagens produce heritable gene mutations, and heritable structural and numerical chromosome aberrations in germ cells. The original categories 1 and 2 for germ cell mutagens remained unchanged. Two new categories 3 A and 3 B are proposed for chemicals which are suspected to be germ cell mutagens. A new category 5 is proposed for germ cell mutagens with low potency which contribute negligibly to human genetic risk provided the MAK value is observed. The following categories are presented for further discussion. 1. Germ cell mutagens which have been shown to increase the mutant frequency among the progeny of exposed humans. 2. Germ cell mutagens which have been shown to increase the mutant frequency among the progeny of exposed animals. 3 A. Substances which have been shown to induce genetic damage in germ cells of humans or animals, or which are mutagenic in somatic cells and have been shown to reach the germ cells in their active forms. 3 B. Substances which are suspected of being germ cell mutagens because of their genotoxic effects in mammalian somatic cells in vivo or, in exceptional cases in the absence of in vivo data, if they are clearly mutagenic in vitro and structurally related to in vivo mutagens. 4. not applicable (Category 4 was introduced for carcinogenic substances with nongenotoxic modes of action. By definition, germ cell mutagens are genotoxic. Therefore, a Category 4 for germ cell mutagens cannot exist.) 5. Germ cell mutagens, the potency of which is considered to be so low that, provided the MAK value is observed, their contribution to genetic risk is expected not to be significant.

Tubule detection in testis images using boundary weighting and circular shortest path

In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.

The role of germline polymorphisms in the T-cell receptor in susceptibility to ankylosing spondylitis

The role of germline polymorphisms of the T-cell receptor A/D and B loci in susceptibility to ankylosing spondylitis was investigated by linkage studies using microsatellite markers in 215 affected sibling pairs. The presence of a significant susceptibility gene (lambda ≤ 1.6) at the TCRA/D locus was excluded (LOD score < -2.0). At the TCRB locus, there was weak evidence of the presence of a susceptibility gene (P = 0.01, LOD score 1.1). Further family studies will be required to determine whether this is a true or false-positive finding. It is unlikely that either the TCRA/D or TCRB loci contain genes responsible for more than a moderate proportion of the non-MHC genetic susceptibility to ankylosing spondylitis.

Effective Cell-Centred Time-Domain Maxwell's Equations Numerical Solvers

This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed.

Combining ganglion cell topology and data of patients with glaucoma to determine a structure-function map

PURPOSE: To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph. METHODS: Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10 degrees ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40 degrees of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant. RESULTS: The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye. CONCLUSIONS: A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.

Regulation of human stem cell research in Australia

Australia is currently well placed to contribute to the global growth of human stem cell research. However, as the science has progressed, authorities have had to deal with the ongoing challenges of regulating such a fast moving field of scientific endeavour. Australia’s past and current approach to regulating the use of embryos in human embryonic stem cell research provides an insight into how Australia may continue to adapt to future regulatory challenges presented by human stem cell research. In the broader context, a number of issues have been identified that may impact upon the success of future human stem cell research in Australia.