Microdissection: A method developed to investigate mechanisms involved in transmissible spongiform encephalopathy pathogenesis

BACKGROUND: The transmissible spongiform encephalopathies (TSEs) are a group of neurodegenerative diseases affecting both human and animals. The neuroanatomical changes which occur in the central nervous system (CNS) of TSE infected animals include vacuolation, gliosis, neuronal loss and the deposition of a disease specific protein, PrP(Sc). Experimental murine models of scrapie, a TSE of sheep, have revealed that pathology may be confined to specific brain areas with targeting of particular neuronal subsets depending on route of injection and scrapie isolate. To assess the biochemical changes which are taking place in these targeted areas it was necessary to develop a reliable sampling procedure (microdissection) which could be used for a variety of tests such as western blotting and magnetic resonance spectroscopy. METHODS: The method described is for the microdissection of murine brains. To assess the usefulness of this dissection technique for producing similar sample types for analysis by various down-stream biochemical techniques, the areas dissected were analysed for PrP(Sc )by western blotting and compared to immunocytochemical (ICC) techniques. RESULTS: Results show that the method generates samples yielding a consistent protein content which can be analysed for PrP(Sc). The areas in which PrP(Sc )is found by western blotting compares well with localisation visualised by immunocytochemistry. CONCLUSION: The microdisssection method described can be used to generate samples suitable for a range of biochemical techniques. Using these samples a range of assays can be carried out which will help to elucidate the molecular and cellular mechanisms underlying TSE pathogenesis. The method would also be useful for any study requiring the investigation of discrete areas within the murine brain

Fluid dynamic lateral slicing of high tensile strength carbon nanotubes

Lateral slicing of micron length carbon nanotubes (CNTs) is effective on laser irradiation of the materials suspended within dynamic liquid thin films in a microfluidic vortex fluidic device (VFD). The method produces sliced CNTs with minimal defects in the absence of any chemical stabilizers, having broad length distributions centred at ca 190, 160 nm and 171 nm for single, double and multi walled CNTs respectively, as established using atomic force microscopy and supported by small angle neutron scattering solution data. Molecular dynamics simulations on a bent single walled carbon nanotube (SWCNT) with a radius of curvature of order 10 nm results in tearing across the tube upon heating, highlighting the role of shear forces which bend the tube forming strained bonds which are ruptured by the laser irradiation. CNT slicing occurs with the VFD operating in both the confined mode for a finite volume of liquid and continuous flow for scalability purposes

Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises

Volcano observatories provide near real-time information and, ultimately, forecasts about volcano activity. For this reason, multiple physical and chemical parameters are continuously monitored. Here, we present a new method to efficiently estimate the location and evolution of magmatic sources based on a stream of real-time surface deformation data, such as High-Rate GPS, and a free-geometry magmatic source model. The tool allows tracking inflation and deflation sources in time, providing estimates of where a volcano might erupt, which is important in understanding an on-going crisis. We show a successful simulated application to the pre-eruptive period of May 2008, at Mount Etna (Italy). The proposed methodology is able to track the fast dynamics of the magma migration by inverting the real-time data within seconds. This general method is suitable for integration in any volcano observatory. The method provides first order unsupervised and realistic estimates of the locations of magmatic sources and of potential eruption sites, information that is especially important for civil protection purposes

First recorded eruption of Nabro volcano, Eritrea, 2011

We present a synthesis of diverse observations of the first recorded eruption of Nabro volcano, Eritrea, which began on 12 June 2011. While no monitoring of the volcano was in effect at the time, it has been possible to reconstruct the nature and evolution of the eruption through analysis of re- gional seismological and infrasound data and satellite remote sensing data, supplemented by petrological analysis of erupted products and brief field surveys. The event is notable for the comparative rarity of recorded historical eruptions in the region and of caldera systems in general, for the prodi- gious quantity of SO2 emitted into the atmosphere and the significant human impacts that ensued notwithstanding the low population density of the Afar region. It is also relevant in understanding the broader magmatic and tectonic signifi- cance of the volcanic massif of which Nabro forms a part and which strikes obliquely to the principal rifting directions in the Red Sea and northern Afar. The whole-rock compositions of Editorial responsibility: G. Giordano the erupted lavas and tephra range from trachybasaltic to trachybasaltic andesite, and crystal-hosted melt inclusions contain up to 3,000 ppm of sulphur by weight. The eruption was preceded by significant seismicity, detected by regional networks of sensors and accompanied by sustained tremor. Substantial infrasound was recorded at distances of hundreds to thousands of kilometres from the vent, beginning at the onset of the eruption and continuing for weeks. Analysis of ground deformation suggests the eruption was fed by a shal- low, NW–SE-trending dike, which is consistent with field and satellite observations of vent distributions. Despite lack of prior planning and preparedness for volcanic events in the country, rapid coordination of the emergency response miti- gated the human costs of the eruption

Crystal and melt inclusion timescales reveal the evolution of magma migration before eruption

Volatile element concentrations measured in melt inclusions are a key tool used to understand magma migration and degassing, although their original values may be affected by different re-equilibration processes. Additionally, the inclusion-bearing crystals can have a wide range of origins and ages, further complicating the interpretation of magmatic processes. To clarify some of these issues, here we combined olivine diffusion chronometry and melt inclusion data from the 2008 eruption of Llaima volcano (Chile). We found that magma intrusion occurred about 4 years before the eruption at a minimum depth of approximately 8 km. Magma migration and reaction became shallower with time, and about 6 months before the eruption magma reached 3–4 km depth. This can be linked to reported seismicity and ash emissions. Although some ambiguities of interpretation still remain, crystal zoning and melt inclusion studies allow a more complete understanding of magma ascent, degassing, and volcano monitoring data.NRF (Natl Research Foundation, S’pore)MOE (Min. of Education, S’pore)Published versio

Accurate molecular classification of cancer using simple rules

<p>Abstract</p> <p>Background</p> <p>One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.</p> <p>Methods</p> <p>We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.</p> <p>Results</p> <p>We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.</p> <p>Conclusion</p> <p>In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.</p