Shaping bursting by electrical coupling and noise

Gap-junctional coupling is an important way of communication between neurons and other excitable cells. Strong electrical coupling synchronizes activity across cell ensembles. Surprisingly, in the presence of noise synchronous oscillations generated by an electrically coupled network may differ qualitatively from the oscillations produced by uncoupled individual cells forming the network. A prominent example of such behavior is the synchronized bursting in islets of Langerhans formed by pancreatic \beta-cells, which in isolation are known to exhibit irregular spiking. At the heart of this intriguing phenomenon lies denoising, a remarkable ability of electrical coupling to diminish the effects of noise acting on individual cells. In this paper, we derive quantitative estimates characterizing denoising in electrically coupled networks of conductance-based models of square wave bursting cells. Our analysis reveals the interplay of the intrinsic properties of the individual cells and network topology and their respective contributions to this important effect. In particular, we show that networks on graphs with large algebraic connectivity or small total effective resistance are better equipped for implementing denoising. As a by-product of the analysis of denoising, we analytically estimate the rate with which trajectories converge to the synchronization subspace and the stability of the latter to random perturbations. These estimates reveal the role of the network topology in synchronization. The analysis is complemented by numerical simulations of electrically coupled conductance-based networks. Taken together, these results explain the mechanisms underlying synchronization and denoising in an important class of biological models

A Predator from East Africa that Chooses Malaria Vectors as Preferred Prey

BACKGROUND: All vectors of human malaria, a disease responsible for more than one million deaths per year, are female mosquitoes from the genus Anopheles. Evarcha culicivora is an East African jumping spider (Salticidae) that feeds indirectly on vertebrate blood by selecting blood-carrying female mosquitoes as preferred prey. METHODOLOGY/PRINCIPAL FINDINGS: By testing with motionless lures made from mounting dead insects in lifelike posture on cork discs, we show that E. culicivora selects Anopheles mosquitoes in preference to other mosquitoes and that this predator can identify Anopheles by static appearance alone. Tests using active (grooming) virtual mosquitoes rendered in 3-D animation show that Anopheles' characteristic resting posture is an important prey-choice cue for E. culicivora. Expression of the spider's preference for Anopheles varies with the spider's size, varies with its prior feeding condition and is independent of the spider gaining a blood meal. CONCLUSIONS/SIGNIFICANCE: This is the first experimental study to show that a predator of any type actively chooses Anopheles as preferred prey, suggesting that specialized predators having a role in the biological control of disease vectors is a realistic possibility

Computational identification of condition-specific miRNA targets based on gene expression profiles and sequence information

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are small and noncoding RNAs that play important roles in various biological processes. They regulate target mRNAs post-transcriptionally through complementary base pairing. Since the changes of miRNAs affect the expression of target genes, the expression levels of target genes in specific biological processes could be different from those of non-target genes. Here we demonstrate that gene expression profiles contain useful information in separating miRNA targets from non-targets.</p> <p>Results</p> <p>The gene expression profiles related to various developmental processes and stresses, as well as the sequences of miRNAs and mRNAs in <it>Arabidopsis</it>, were used to determine whether a given gene is a miRNA target. It is based on the model combining the support vector machine (SVM) classifier and the scoring method based on complementary base pairing between miRNAs and mRNAs. The proposed model yielded low false positive rate and retrieved condition-specific candidate targets through a genome-wide screening.</p> <p>Conclusion</p> <p>Our approach provides a novel framework into screening target genes by considering the gene regulation of miRNAs. It can be broadly applied to identify condition-specific targets computationally by embedding information of gene expression profiles.</p

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

A potent betulinic acid analogue ascertains an antagonistic mechanism between autophagy and proteasomal degradation pathway in HT-29 cells

Betulinic acid (BA), a member of pentacyclic triterpenes has shown important biological activities like anti-bacterial, anti-malarial, anti-inflammatory and most interestingly anticancer property. To overcome its poor aqueous solubility and low bioavailability, structural modifications of its functional groups are made to generate novel lead(s) having better efficacy and less toxicity than the parent compound. BA analogue, 2c was found most potent inhibitor of colon cancer cell line, HT-29 cells with IC50 value 14.9 μM which is significantly lower than standard drug 5-fluorouracil as well as parent compound, Betulinic acid. We have studied another mode of PCD, autophagy which is one of the important constituent of cellular catabolic system as well as we also studied proteasomal degradation pathway to investigate whole catabolic pathway after exploration of 2c on HT-29 cells. Mechanism of autophagic cell death was studied using fluorescent dye like acridine orange (AO) and monodansylcadaverin (MDC) staining by using fluorescence microscopy. Various autophagic protein expression levels were determined by Western Blotting, qRT-PCR and Immunostaining. Confocal Laser Scanning Microscopy (CLSM) was used to study the colocalization of various autophagic proteins. These were accompanied by formation of autophagic vacuoles as revealed by FACS and transmission electron microscopy (TEM). Proteasomal degradation pathway was studied by proteasome-Glo™ assay systems using luminometer.The formation of autophagic vacuoles in HT-29 cells after 2c treatment was determined by fluorescence staining – confirming the occurrence of autophagy. In addition, 2c was found to alter expression levels of different autophagic proteins like Beclin-1, Atg 5, Atg 7, Atg 5-Atg 12, LC3B and autophagic adapter protein, p62. Furthermore we found the formation of autophagolysosome by colocalization of LAMP-1 with LC3B, LC3B with Lysosome, p62 with lysosome. Finally, as proteasomal degradation pathway downregulated after 2c treatment colocalization of ubiquitin with lysosome and LC3B with p62 was studied to confirm that protein degradation in autophagy induced HT-29 cells follows autolysosomal pathway. In summary, betulinic acid analogue, 2c was able to induce autophagy in HT-29 cells and as proteasomal degradation pathway downregulated after 2c treatment so protein degradation in autophagy induced HT-29 cell

Isotropic 3D Nuclear Morphometry of Normal, Fibrocystic and Malignant Breast Epithelial Cells Reveals New Structural Alterations

Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis

Non-Coding RNA Prediction and Verification in Saccharomyces cerevisiae

Non-coding RNA (ncRNA) play an important and varied role in cellular function. A significant amount of research has been devoted to computational prediction of these genes from genomic sequence, but the ability to do so has remained elusive due to a lack of apparent genomic features. In this work, thermodynamic stability of ncRNA structural elements, as summarized in a Z-score, is used to predict ncRNA in the yeast Saccharomyces cerevisiae. This analysis was coupled with comparative genomics to search for ncRNA genes on chromosome six of S. cerevisiae and S. bayanus. Sets of positive and negative control genes were evaluated to determine the efficacy of thermodynamic stability for discriminating ncRNA from background sequence. The effect of window sizes and step sizes on the sensitivity of ncRNA identification was also explored. Non-coding RNA gene candidates, common to both S. cerevisiae and S. bayanus, were verified using northern blot analysis, rapid amplification of cDNA ends (RACE), and publicly available cDNA library data. Four ncRNA transcripts are well supported by experimental data (RUF10, RUF11, RUF12, RUF13), while one additional putative ncRNA transcript is well supported but the data are not entirely conclusive. Six candidates appear to be structural elements in 5′ or 3′ untranslated regions of annotated protein-coding genes. This work shows that thermodynamic stability, coupled with comparative genomics, can be used to predict ncRNA with significant structural elements

Parametric exploration of the liver by magnetic resonance methods

MRI, as a completely noninvasive technique, can provide quantitative assessment of perfusion, diffusion, viscoelasticity and metabolism, yielding diverse information about liver function. Furthermore, pathological accumulations of iron and lipids can be quantified. Perfusion MRI with various contrast agents is commonly used for the detection and characterization of focal liver disease and the quantification of blood flow parameters. An extended new application is the evaluation of the therapeutic effect of antiangiogenic drugs on liver tumours. Novel, but already widespread, is a histologically validated relaxometry method using five gradient echo sequences for quantifying liver iron content elevation, a measure of inflammation, liver disease and cancer. Because of the high perfusion fraction in the liver, the apparent diffusion coefficients strongly depend on the gradient factors used in diffusion-weighted MRI. While complicating analysis, this offers the opportunity to study perfusion without contrast injection. Another novel method, MR elastography, has already been established as the only technique able to stage fibrosis or diagnose mild disease. Liver fat content is accurately determined with multivoxel MR spectroscopy (MRS) or by faster MRI methods that are, despite their widespread use, prone to systematic error. Focal liver disease characterisation will be of great benefit once multivoxel methods with fat suppression are implemented in proton MRS, in particular on high-field MR systems providing gains in signal-to-noise ratio and spectral resolution