Surface Characterisation Based Tool Wear Monitoring in Peripheral milling

The progress of surface metrology in the last decade has led to improved 3D characterisation of surfaces which offers the possibility of monitoring manufacturing operations to give highly detailed information regarding the machine tool condition. This paper presents a case study where areal surface characterisation is used to monitor tool wear in peripheral milling. Due to the fact that tool wear has a direct effect on the machined workpiece surface, the machined surface topography contains much information concerning the machining conditions including the tool wear state. Through analysing the often subtle changes in the surface topography the tool wear state can be highlighted. This paper utilises areal surface characterization, areal auto-correlation function (AACF) and pattern analysis to illustrate the effect of tool wear on the workpiece surface. The result shows that: (1) tool wear, previously difficult to detect will influence almost all of the areal surface parameters; (2) the pattern features of AACF spectrum can reflect the subtle surface texture variation with increasing tool wear. The authors consider that, combined analysis of the surface roughness and its AACF spectrum are a good choice for monitoring the tool wear state especially with the latest developments in on-machine surface metrology

iQuantitator: A tool for protein expression inference using iTRAQ

<p>Abstract</p> <p>Background</p> <p>Isobaric Tags for Relative and Absolute Quantitation (iTRAQ™) [Applied Biosystems] have seen increased application in differential protein expression analysis. To facilitate the growing need to analyze iTRAQ data, especially for cases involving multiple iTRAQ experiments, we have developed a modeling approach, statistical methods, and tools for estimating the relative changes in protein expression under various treatments and experimental conditions.</p> <p>Results</p> <p>This modeling approach provides a unified analysis of data from multiple iTRAQ experiments and links the observed quantity (reporter ion peak area) to the experiment design and the calculated quantity of interest (treatment-dependent protein and peptide fold change) through an additive model under log transformation. Others have demonstrated, through a case study, this modeling approach and noted the computational challenges of parameter inference in the unbalanced data set typical of multiple iTRAQ experiments. Here we present the development of an inference approach, based on hierarchical regression with batching of regression coefficients and Markov Chain Monte Carlo (MCMC) methods that overcomes some of these challenges. In addition to our discussion of the underlying method, we also present our implementation of the software, simulation results, experimental results, and sample output from the resulting analysis report.</p> <p>Conclusion</p> <p>iQuantitator's process-based modeling approach overcomes limitations in current methods and allows for application in a variety of experimental designs. Additionally, hypertext-linked documents produced by the tool aid in the interpretation and exploration of results.</p

Role of Sphingomyelin Synthase in Controlling the Antimicrobial Activity of Neutrophils against Cryptococcus neoformans

The key host cellular pathway(s) necessary to control the infection caused by inhalation of the environmental fungal pathogen Cryptococcus neoformans are still largely unknown. Here we have identified that the sphingolipid pathway in neutrophils is required for them to exert their killing activity on the fungus. In particular, using both pharmacological and genetic approaches, we show that inhibition of sphingomyelin synthase (SMS) activity profoundly impairs the killing ability of neutrophils by preventing the extracellular release of an antifungal factor(s). We next found that inhibition of protein kinase D (PKD), which controls vesicular sorting and secretion and is regulated by diacylglycerol (DAG) produced by SMS, totally blocks the extracellular killing activity of neutrophils against C. neoformans. The expression of SMS genes, SMS activity and the levels of the lipids regulated by SMS (namely sphingomyelin (SM) and DAG) are up-regulated during neutrophil differentiation. Finally, tissue imaging of lungs infected with C. neoformans using matrix-assisted laser desorption-ionization mass spectrometry (MALDI-MS), revealed that specific SM species are associated with neutrophil infiltration at the site of the infection. This study establishes a key role for SMS in the regulation of the killing activity of neutrophils against C. neoformans through a DAG-PKD dependent mechanism, and provides, for the first time, new insights into the protective role of host sphingolipids against a fungal infection