Deterministic mechanical model of T-killer cell polarization reproduces the wandering of aim between simultaneously engaged targets

T-killer cells of the immune system eliminate virus-infected and tumorous cells through direct cell-cell interactions. Reorientation of the killing apparatus inside the T cell to the T-cell interface with the target cell ensures specificity of the immune response. The killing apparatus can also oscillate next to the cell-cell interface. When two target cells are engaged by the T cell simultaneously, the killing apparatus can oscillate between the two interface areas. This oscillation is one of the most striking examples of cell movements that give the microscopist an unmechanistic impression of the cell's fidgety indecision. We have constructed a three-dimensional, numerical biomechanical model of the molecular-motor-driven microtubule cytoskeleton that positions the killing apparatus. The model demonstrates that the cortical pulling mechanism is indeed capable of orienting the killing apparatus into the functional position under a range of conditions. The model also predicts experimentally testable limitations of this commonly hypothesized mechanism of T-cell polarization. After the reorientation, the numerical solution exhibits complex, multidirectional, multiperiodic, and sustained oscillations in the absence of any external guidance or stochasticity. These computational results demonstrate that the strikingly animate wandering of aim in T-killer cells has a purely mechanical and deterministic explanation. © 2009 Kim, Maly

Substrate Induced Strain Field in FeRh Epilayers Grown on Single Crystal MgO (001) Substrates

Equi-atomic FeRh is highly unusual in that it undergoes a first order meta-magnetic phase transition from an antiferromagnet to a ferromagnet above room temperature (Tr ≈ 370 K). This behavior opens new possibilities for creating multifunctional magnetic and spintronic devices which can utilise both thermal and applied field energy to change state and functionalise composites. A key requirement in realising multifunctional devices is the need to understand and control the properties of FeRh in the extreme thin film limit (tFeRh < 10 nm) where interfaces are crucial. Here we determine the properties of FeRh films in the thickness range 2.5–10 nm grown directly on MgO substrates. Our magnetometry and structural measurements show that a perpendicular strain field exists in these thin films which results in an increase in the phase transition temperature as thickness is reduced. Modelling using a spin dynamics approach supports the experimental observations demonstrating the critical role of the atomic layers close to the MgO interface

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p

Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us

Supernova remnants (SNRs) arise from the interaction between the ejecta of a supernova (SN) explosion and the surrounding circumstellar and interstellar medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However, to understand SNRs as a whole, large samples of SNRs must be assembled and studied. Here, we describe the radio, optical, and X-ray techniques which have been used to identify and characterize almost 300 Galactic SNRs and more than 1200 extragalactic SNRs. We then discuss which types of SNRs are being found and which are not. We examine the degree to which the luminosity functions, surface-brightness distributions and multi-wavelength comparisons of the samples can be interpreted to determine the class properties of SNRs and describe efforts to establish the type of SN explosion associated with a SNR. We conclude that in order to better understand the class properties of SNRs, it is more important to study (and obtain additional data on) the SNRs in galaxies with extant samples at multiple wavelength bands than it is to obtain samples of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin. Final version available at https://doi.org/10.1007/978-3-319-20794-0_90-

Canonical A-to-I and C-to-U RNA Editing Is Enriched at 3′UTRs and microRNA Target Sites in Multiple Mouse Tissues

RNA editing is a process that modifies RNA nucleotides and changes the efficiency and fidelity of the central dogma. Enzymes that catalyze RNA editing are required for life, and defects in RNA editing are associated with many diseases. Recent advances in sequencing have enabled the genome-wide identification of RNA editing sites in mammalian transcriptomes. Here, we demonstrate that canonical RNA editing (A-to-I and C-to-U) occurs in liver, white adipose, and bone tissues of the laboratory mouse, and we show that apparent non-canonical editing (all other possible base substitutions) is an artifact of current high-throughput sequencing technology. Further, we report that high-confidence canonical RNA editing sites can cause non-synonymous amino acid changes and are significantly enriched in 3′ UTRs, specifically at microRNA target sites, suggesting both regulatory and functional consequences for RNA editing

Construction of 3D models of the CYP11B family as a tool to predict ligand binding characteristics

Aldosterone is synthesised by aldosterone synthase (CYP11B2). CYP11B2 has a highly homologous isoform, steroid 11β-hydroxylase (CYP11B1), which is responsible for the biosynthesis of aldosterone precursors and glucocorticoids. To investigate aldosterone biosynthesis and facilitate the search for selective CYP11B2 inhibitors, we constructed three-dimensional models for CYP11B1 and CYP11B2 for both human and rat. The models were constructed based on the crystal structure of Pseudomonas Putida CYP101 and Oryctolagus Cuniculus CYP2C5. Small steric active site differences between the isoforms were found to be the most important determinants for the regioselective steroid synthesis. A possible explanation for these steric differences for the selective synthesis of aldosterone by CYP11B2 is presented. The activities of the known CYP11B inhibitors metyrapone, R-etomidate, R-fadrazole and S-fadrazole were determined using assays of V79MZ cells that express human CYP11B1 and CYP11B2, respectively. By investigating the inhibitors in the human CYP11B models using molecular docking and molecular dynamics simulations we were able to predict a similar trend in potency for the inhibitors as found in the in vitro assays. Importantly, based on the docking and dynamics simulations it is possible to understand the enantioselectivity of the human enzymes for the inhibitor fadrazole, the R-enantiomer being selective for CYP11B2 and the S-enantiomer being selective for CYP11B1

A Key Role for Neurotensin in Chronic-Stress-Induced Anxiety-Like Behavior in Rats

Accepted ManuscriptChronic stress is a major cause of anxiety disorders that can be reliably modeled preclinically, providing insight into alternative therapeutic targets for this mental health illness. Neuropeptides have been targeted in the past to no avail possibly due to our lack of understanding of their role in pathological models. In this study we use a rat model of chronic stress-induced anxiety-like behaviors and hypothesized that neuropeptidergic modulation of synaptic transmission would be altered in the bed nucleus of the stria terminalis (BNST), a brain region suspected to contribute to anxiety disorders. We use brain slice neurophysiology and behavioral pharmacology to compare the role of locally released endogenous neuropeptides on synaptic transmission in the oval (ov) BNST of non-stressed (NS) or chronic unpredictably stressed (CUS) rats. We found that in NS rats, post-synaptic depolarization induced the release of vesicular neurotensin (NT) and corticotropin-releasing factor (CRF) that co-acted to increase ovBNST inhibitory synaptic transmission in 59% of recorded neurons. CUS bolstered this potentiation (100% of recorded neurons) through an enhanced contribution of NT over CRF. In contrast, locally released opioid neuropeptides decreased ovBNST excitatory synaptic transmission in all recorded neurons, regardless of stress. Consistent with CUS-induced enhanced modulatory effects of NT, blockade of ovBNST NT receptors completely abolished stress-induced anxiety-like behaviors in the elevated plus maze paradigm. The role of NT has been largely unexplored in stress and our findings highlight its potential contribution to an important behavioral consequence of chronic stress, that is, exaggerated avoidance of open space in rats.CPN was funded by CIHR Vanier Graduate Scholarship (338319); APVS was funded by Fundação para a Ciência e Tecnologia (SFRH/BPD/52078/2013); ERH was funded by CIHR Postdoctoral Fellowship (MFE-123712); SA was funded by a Queen Elizabeth II Graduate Scholarship in Science and Technology; ÉCD was funded by the Canadian Institute of Health Research (MOP-25953)info:eu-repo/semantics/publishedVersio

Predicted Disappearance of Cephalantheropsis obcordata in Luofu Mountain Due to Changes in Rainfall Patterns

<div><h3>Background</h3><p>In the past century, the global average temperature has increased by approximately 0.74°C and extreme weather events have become prevalent. Recent studies have shown that species have shifted from high-elevation areas to low ones because the rise in temperature has increased rainfall. These outcomes challenge the existing hypothesis about the responses of species to climate change.</p> <h3>Methodology/Principal Findings</h3><p>With the use of data on the biological characteristics and reproductive behavior of <em>Cephalantheropsis obcordata</em> in Luofu Mountain, Guangdong, China, trends in the population size of the species were predicted based on several factors. The response of <em>C. obcordata</em> to climate change was verified by integrating it with analytical findings on meteorological data and an artificially simulated environment of water change. The results showed that <em>C. obcordata</em> can grow only in waterlogged streams. The species can produce fruit with many seeds by insect pollination; however, very few seeds can burgeon to become seedlings, with most of those seedlings not maturing into the sexually reproductive phase, and grass plants will die after reproduction. The current population's age pyramid is kettle-shaped; it has a Deevey type I survival curve; and its net reproductive rate, intrinsic rate of increase, as well as finite rate of increase are all very low. The population used in the artificial simulation perished due to seasonal drought.</p> <h3>Conclusions</h3><p>The change in rainfall patterns caused by climate warming has altered the water environment of <em>C. obcordata</em> in Luofu Mountain, thereby restricting seed burgeoning as well as seedling growth and shortening the life span of the plant. The growth rate of the <em>C. obcordata</em> population is in descending order, and models of population trend predict that the population in Luofu Mountain will disappear in 23 years.</p> </div