Designing Volumetric Truss Structures

We present the first algorithm for designing volumetric Michell Trusses. Our method uses a parametrization approach to generate trusses made of structural elements aligned with the primary direction of an object's stress field. Such trusses exhibit high strength-to-weight ratios. We demonstrate the structural robustness of our designs via a posteriori physical simulation. We believe our algorithm serves as an important complement to existing structural optimization tools and as a novel standalone design tool itself

Kruppel-like factor 4 (KLF4) represses histidine decarboxylase gene expression through an upstream Sp1 site and downstream gastrin responsive elements

Histidine decarboxylase (HDC) is the enzyme that catalyzes the conversion of histidine to histamine, a bioamine that plays an important role in allergic responses, inflammation, neurotransmission, and gastric acid secretion. Previously, we demonstrated that gastrin activates HDC promoter activity in a gastric cancer (AGS-E) cell line through three overlapping downstream promoter elements. In the current study, we used the yeast one-hybrid strategy to identify nuclear factors that bind to these three elements. Among eight positives from the one-hybrid screen, we identified Kruppel-like factor 4 (KLF4) (previously known as gut-enriched Kruppel-like factor (GKLF)) as one factor that binds to the gastrin responsive elements in the HDC promoter. Electrophoretic mobility shift assays confirmed that KLF4 is able to bind all three gastrin responsive elements. In addition, transient cotransfection experiments showed that overexpression of KLF4 dose dependently and specifically inhibited HDC promoter activity. Regulation of HDC transcription by KLF4 was confirmed by changes in the endogenous HDC messenger RNA by KLF4 small interfering RNA and KLF4 overexpression. We further showed that KLF4 inhibits HDC promoter activity by competing with Sp1 at the upstream GC box and also independently by binding the three downstream gastrin responsive elements. Taken together, these results indicate that KLF4 can act to repress HDC gene expression by Sp1-dependent and -independent mechanisms

Mapping of catalytically important residues in the rat L-histidine decarboxylase enzyme using bioinformatic and site-directed mutagenesis approaches.

HDC (L-histidine decarboxylase), the enzyme responsible for the catalytic production of histamine from L-histidine, belongs to an evolutionarily conserved family of vitamin B6-dependent enzymes known as the group II decarboxylases. Yet despite the obvious importance of histamine, mammalian HDC enzymes remain poorly characterized at both the biochemical and structural levels. By comparison with the recently described crystal structure of the homologous enzyme L-DOPA decarboxylase, we have been able to identify a number of conserved domains and motifs that are important also for HDC catalysis. This includes residues that were proposed to mediate events within the active site, and HDC proteins carrying mutations in these residues were inactive when expressed in reticulocyte cell lysates reactions. Our studies also suggest that a significant change in quartenary structure occurs during catalysis. This involves a protease sensitive loop, and incubating recombinant HDC with an L-histidine substrate analogue altered enzyme structure so that the loop was no longer exposed for tryptic proteolysis. In total, 27 mutant proteins were used to test the proposed importance of 34 different amino acid residues. This is the most extensive mutagenesis study yet to identify catalytically important residues in a mammalian HDC protein sequence and it provides a number of novel insights into the mechanism of histamine biosynthesis

Similarities between Line Fishing and Baited Stereo-Video Estimations of Length-Frequency: Novel Application of Kernel Density Estimates

<div><p>Age structure data is essential for single species stock assessments but length-frequency data can provide complementary information. In south-western Australia, the majority of these data for exploited species are derived from line caught fish. However, baited remote underwater stereo-video systems (stereo-BRUVS) surveys have also been found to provide accurate length measurements. Given that line fishing tends to be biased towards larger fish, we predicted that, stereo-BRUVS would yield length-frequency data with a smaller mean length and skewed towards smaller fish than that collected by fisheries-independent line fishing. To assess the biases and selectivity of stereo-BRUVS and line fishing we compared the length-frequencies obtained for three commonly fished species, using a novel application of the Kernel Density Estimate (KDE) method and the established Kolmogorov–Smirnov (KS) test. The shape of the length-frequency distribution obtained for the labrid <i>Choerodon rubescens</i> by stereo-BRUVS and line fishing did not differ significantly, but, as predicted, the mean length estimated from stereo-BRUVS was 17% smaller. Contrary to our predictions, the mean length and shape of the length-frequency distribution for the epinephelid <i>Epinephelides armatus</i> did not differ significantly between line fishing and stereo-BRUVS. For the sparid <i>Pagrus auratus</i>, the length frequency distribution derived from the stereo-BRUVS method was bi-modal, while that from line fishing was uni-modal. However, the location of the first modal length class for <i>P. auratus</i> observed by each sampling method was similar. No differences were found between the results of the KS and KDE tests, however, KDE provided a data-driven method for approximating length-frequency data to a probability function and a useful way of describing and testing any differences between length-frequency samples. This study found the overall size selectivity of line fishing and stereo-BRUVS were unexpectedly similar.</p></div

Length-frequency distribution for <i>Choerodon rubescens</i>, <i>Epinephelides armatus</i> and <i>Pagrus auratus</i> sampled using either line fishing (Line) or stereo-BRUVS.

<p>The separate bandwidth ‘h’ of each KDE was chosen by the Sheather & Jones (1991) bandwidth selection procedure. Length classes for the histogram of each species were chosen to match the KDE; <i>C. rubescens</i> 50 mm, <i>E. armatus</i> 40 mm and <i>P. auratus</i> 50 mm. Rug plot just above the x-axis indicate individual length observations. Dashed vertical lines indicate the minimum legal length of retention for each species and ‘n’, indicates the sample size.</p

Minimum legal length of retention (MLL), length-frequency mean and standard deviation (SD) and mode, estimated by the kernel density estimate (KDE) for <i>Choerodon rubescens</i>, <i>Epinephelides armatus</i> and <i>Pagrus auratus</i> sampled by fishing (Line) and baited remote underwater stereo-video (stereo-BRUVS).

<p>Minimum legal length of retention (MLL), length-frequency mean and standard deviation (SD) and mode, estimated by the kernel density estimate (KDE) for <i>Choerodon rubescens</i>, <i>Epinephelides armatus</i> and <i>Pagrus auratus</i> sampled by fishing (Line) and baited remote underwater stereo-video (stereo-BRUVS).</p