Magnetic Response of Magnetospirillum Gryphiswaldense

In this study we modelled and measured the U-turn trajectories of individual magnetotactic bacteria under the application of rotating magnetic fields, ranging in ampitude from 1 to 12 mT. The model is based on the balance between rotational drag and magnetic torque. For accurate verification of this model, bacteria were observed inside 5 m tall microfluidic channels, so that they remained in focus during the entire trajectory. From the analysis of hundreds of trajectories and accurate measurements of bacteria and magnetosome chain dimensions, we confirmed that the model is correct within measurement error. The resulting average rate of rotation of Magnetospirillum Gryphiswaldense is 0.74 +- 0.03 rad/mTs.Comment: 17 pages, 12 figure

Role of transport performance on neuron cell morphology

The compartmental model is a basic tool for studying signal propagation in neurons, and, if the model parameters are adequately defined, it can also be of help in the study of electrical or fluid transport. Here we show that the input resistance, in different networks which simulate the passive properties of neurons, is the result of an interplay between the relevant conductances, morphology and size. These results suggest that neurons must grow in such a way that facilitates the current flow. We propose that power consumption is an important factor by which neurons attain their final morphological appearance.Comment: 9 pages with 3 figures, submitted to Neuroscience Letter

Visualizing the Anthropocene dialectically: Jessica Woodworth and Peter Brosens’ eco-crisis trilogy

The ambition of this article is to propose a way of visualizing the Anthropocene dialectically. As suggested by the Dutch atmospheric chemist Paul Crutzen and the professor of biology Eugene F. Stoermer, the term Anthropocene refers to a historical period in which humankind has turned into a geological force that transforms the natural environment in such a way that it is hard to distinguish between the human and the natural world. Crutzen and Stoermer explain that the Anthropocene has begun after the Holocene, the geological epoch that followed the last ice age and lasted until the industrial revolution. Drawing on a number of figures such as the “tenfold” increase in urbanisation, the extreme transformation of land surface by human action, the use of more than 50% of all accessible fresh water by humans, and the massive increase in greenhouse emissions, Crutzen and Stoermer conclude that the term Anthropocene describes aptly mankind's influence on ecological and geological cycles (Crutzen & Stoermer, 2000, p.17). The wager of this article is that we need to identify ways to visualize the Anthropocene dialectically and I proceed to do so using as a case study Jessica Woodworth's and Peter Brosen's trilogy on the conflict between humans and nature, which consists of Khadak (2006), Altiplano (2009), and The Fifth Season (La Cinquième Saison, 2012)

Simplivariate Models: Uncovering the Underlying Biology in Functional Genomics Data

One of the first steps in analyzing high-dimensional functional genomics data is an exploratory analysis of such data. Cluster Analysis and Principal Component Analysis are then usually the method of choice. Despite their versatility they also have a severe drawback: they do not always generate simple and interpretable solutions. On the basis of the observation that functional genomics data often contain both informative and non-informative variation, we propose a method that finds sets of variables containing informative variation. This informative variation is subsequently expressed in easily interpretable simplivariate components

Novel role for the innate immune receptor toll-like receptor 4 (TLR4) in the regulation of the wnt signaling pathway and photoreceptor apoptosis

Recent evidence has implicated innate immunity in regulating neuronal survival in the brain during stroke and other neurodegenerations. Photoreceptors are specialized light-detecting neurons in the retina that are essential for vision. In this study, we investigated the role of the innate immunity receptor TLR4 in photoreceptors. TLR4 activation by lipopolysaccharide (LPS) significantly reduced the survival of cultured mouse photoreceptors exposed to oxidative stress. With respect to mechanism, TLR4 suppressed Wnt signaling, decreased phosphorylation and activation of the Wnt receptor LRP6, and blocked the protective effect of the Wnt3a ligand. Paradoxically, TLR4 activation prior to oxidative injury protected photoreceptors, in a phenomenon known as preconditioning. Expression of TNFα and its receptors TNFR1 and TNFR2 decreased during preconditioning, and preconditioning was mimicked by TNFα antagonists, but was independent of Wnt signaling. Therefore, TLR4 is a novel regulator of photoreceptor survival that acts through the Wnt and TNFα pathways. © 2012 Yi et al

Characteristics of small breast and/or ovarian cancer families with germline mutations in BRCA1 and BRCA2

For families with a small number of cases of breast and/or ovarian cancer, limited data are available to predict the likelihood of genetic predisposition due to mutations in BRCA1 or BRCA2. In 104 families with three or more affected individuals (average 3.8) seeking counselling at family cancer clinics, mutation analysis was performed in the open reading frame of BRCA1 and BRCA2 by the protein truncation test and mutation-specific assays. In 31 of the 104 families tested, mutations were detected (30%). The majority of these mutations (25) occurred in BRCA1. Mutations were detected in 15 out of 25 families (60%) with both breast and ovarian cancer and in 16 out of 79 families (20%) with exclusively cases of breast cancer. Thus, an ovarian cancer case strongly predicted finding a mutation (P < 0.001). Within the group of small breast-cancer-only families, a bilateral breast cancer case or a unilateral breast cancer case diagnosed before age 40 independently predicted finding a BRCA1 or BRCA2 mutation (P = 0.005 and P = 0.02, respectively). Therefore, even small breast/ovarian cancer families with at least one case of ovarian cancer, bilateral breast cancer, or a case of breast cancer diagnosed before age 40, should be referred for mutation screening. © 1999 Cancer Research Campaig

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data

<p>Abstract</p> <p>Background</p> <p>Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline.</p> <p>Results</p> <p>We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data.</p> <p>Conclusions</p> <p>The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from <url>http://code.google.com/p/speaq/</url>.</p

Recent Advances in the Diagnosis and Treatment of Influenza Pneumonia

A potentially fatal complication of influenza infection is the development of pneumonia, caused either directly by the influenza virus, or by secondary bacterial infection. Pneumonia related to the 2009 influenza A pandemic was found to be underestimated by commonly used pneumonia severity scores in many cases, and to be rapidly progressive, leading to respiratory failure. Confirmation of etiology by laboratory testing is warranted in such cases. Rapid antigen and immunofluorescence testing are useful screening tests, but have limited sensitivity. Confirmation of pandemic H1N1 influenza A infection can only be made by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) or viral culture. The most effective preventive measure is annual influenza vaccination in selected individuals. Decisions to administer antiviral medications for influenza treatment or chemoprophylaxis should be based upon clinical and epidemiological factors, and should not be delayed by confirmatory laboratory testing results. Neuraminidase inhibitors (NI) are the agents of choice