Multivariable analysis of the mechanics of penetration of high speed particles

Multivariable analysis of mechanics of penetration of high speed particle

bak deletion stimulates gastric epithelial proliferation and enhances Helicobacter felis-induced gastric atrophy and dysplasia in mice

Helicobacter infection causes a chronic superficial gastritis that in some cases progresses via atrophic gastritis to adenocarcinoma. Proapoptotic bak has been shown to regulate radiation-induced apoptosis in the stomach and colon and also susceptibility to colorectal carcinogenesis in vivo. Therefore we investigated the gastric mucosal pathology following H. felis infection in bak-null mice at 6 or 48 wk postinfection. Primary gastric gland culture from bak-null mice was also used to assess the effects of bak deletion on IFN-γ-, TNF-α-, or IL-1β-induced apoptosis. bak-null gastric corpus glands were longer, had increased epithelial Ki-67 expression, and contained fewer parietal and enteroendocrine cells compared with the wild type (wt). In wt mice, bak was expressed at the luminal surface of gastric corpus glands, and this increased 2 wk post-H. felis infection. Apoptotic cell numbers were decreased in bak-null corpus 6 and 48 wk following infection and in primary gland cultures following cytokine administration. Increased gastric epithelial Ki-67 labeling index was observed in C57BL/6 mice after H. felis infection, whereas no such increase was detected in bak-null mice. More severe gastric atrophy was observed in bak-null compared with C57BL/6 mice 6 and 48 wk postinfection, and 76% of bak-null compared with 25% of C57BL/6 mice showed evidence of gastric dysplasia following long-term infection. Collectively, bak therefore regulates gastric epithelial cell apoptosis, proliferation, differentiation, mucosal thickness, and susceptibility to gastric atrophy and dysplasia following H. felis infection

The Impact of Strategic Trajectory Optimization on Illusory Target Biases During Goal-Directed Aiming

During rapid aiming, movements are planned and executed to avoid worst-case outcomes that require time and energy to correct. As such, downward movements initially undershoot the target to avoid corrections against gravity. Illusory target context can also impact aiming bias. Here, the authors sought to determine how strategic biases mediate illusory biases. Participants aimed to Müller-Lyer figures in different directions (forward, backward, up, down). Downward biases emerged late in the movement and illusory biases emerged from peak velocity. The illusory effects were greater for downward movements at terminal endpoint. These results indicate that strategic biases interact with the limb-target control processes associated with illusory biases. Thus, multiple control processes during rapid aiming may combine and later affect endpoint accuracy (D. Elliott et al., 2010)

Eigenvalue spectral properties of sparse random matrices obeying Dale's law

Understanding the dynamics of large networks of neurons with heterogeneous connectivity architectures is a complex physics problem that demands novel mathematical techniques. Biological neural networks are inherently spatially heterogeneous, making them difficult to mathematically model. Random recurrent neural networks capture complex network connectivity structures and enable mathematically tractability. Our paper generalises previous classical results to sparse connectivity matrices which have distinct excitatory (E) or inhibitory (I) neural populations. By investigating sparse networks we construct our analysis to examine the impacts of all levels of network sparseness, and discover a novel nonlinear interaction between the connectivity matrix and resulting network dynamics, in both the balanced and unbalanced cases. Specifically, we deduce new mathematical dependencies describing the influence of sparsity and distinct E/I distributions on the distribution of eigenvalues (eigenspectrum) of the networked Jacobian. Furthermore, we illustrate that the previous classical results are special cases of the more general results we have described here. Understanding the impacts of sparse connectivities on network dynamics is of particular importance for both theoretical neuroscience and mathematical physics as it pertains to the structure-function relationship of networked systems and their dynamics. Our results are an important step towards developing analysis techniques that are essential to studying the impacts of larger scale network connectivity on network function, and furthering our understanding of brain function and dysfunction.Comment: 18 pages, 6 figure

Submicromolar quantification of pyocyanin in complex biological fluids using pad-printed carbon electrodes

Pyocyanin, a toxin produced by Pseudomonas aeruginosa, offers potential as a biomarker for the indirect detection of this bacterium of major importance for infections in burns, woundcare and cystic fibrosis. Pad-printed carbon electrodes are herein explored using square wave voltammetry to detect pyocyanin in a range of buffered and biological media. Third-order polynomial baseline fitting was explored to enhance the analytical sensitivity and extend the linear range to submicromolar concentrations. These modelling baselines showed excellent correlation with the experimental data, confirmed by high Interclass Correlation Coefficients of 0.995–0.998, and enabled the quantification of pyocyanin – with linearity extended down to 0.18 μM in Human Serum and 0.336 μM in both Britton-Robinson buffer and Simulated Wound Fluid, and derived Limits of Detection of 0.17, 0.15 and 0.09 μM, respectively, in this proof-of-concept study. Therefore, the use of very simple, cost-effective printed carbon materials enabled the detection of clinically relevant concentrations of this important biomarker through a new baseline fitting model and offers a novel approach for point-of-care diagnostics where Pseudomonas aeruginosa infections are critical