Discovery of a black smoker vent field and vent fauna at the Arctic Mid-Ocean Ridge

The Arctic Mid-Ocean Ridge (AMOR) represents one of the most slow-spreading ridge systems on Earth. Previous attempts to locate hydrothermal vent fields and unravel the nature of venting, as well as the provenance of vent fauna at this northern and insular termination of the global ridge system, have been unsuccessful. Here, we report the first discovery of a black smoker vent field at the AMOR. The field is located on the crest of an axial volcanic ridge (AVR) and is associated with an unusually large hydrothermal deposit, which documents that extensive venting and long-lived hydrothermal systems exist at ultraslow-spreading ridges, despite their strongly reduced volcanic activity. The vent field hosts a distinct vent fauna that differs from the fauna to the south along the Mid-Atlantic Ridge. The novel vent fauna seems to have developed by local specialization and by migration of fauna from cold seeps and the Pacific

T-Analyst: a program for efficient analysis of protein conformational changes by torsion angles

T-Analyst is a user-friendly computer program for analyzing trajectories from molecular modeling. Instead of using Cartesian coordinates for protein conformational analysis, T-Analyst is based on internal bond-angle-torsion coordinates in which internal torsion angle movements, such as side-chain rotations, can be easily detected. The program computes entropy and automatically detects and corrects angle periodicity to produce accurate rotameric states of dihedrals. It also clusters multiple conformations and detects dihedral rotations that contribute hinge-like motions. Correlated motions between selected dihedrals can also be observed from the correlation map. T-Analyst focuses on showing changes in protein flexibility between different states and selecting representative protein conformations for molecular docking studies. The program is provided with instructions and full source code in Perl

Position Paper on Olfactory Dysfunction

Background: Olfactory dysfunction is an increasingly recognised condition, associated with reduced quality of life and major health outcomes such as neurodegeneration and death. However, translational research in this field is limited by heterogeneity in methodological approach, including definitions of impairment, improvement and appropriate assessment techniques. Accordingly, effective treatments are limited. In an effort to encourage high quality and comparable work in this field, among others, we propose the following ideas and recommendations. Whilst full recommendations are outlined in the main document, key points include: -Patients with suspected olfactory loss should undergo a full examination of the head and neck, including rigid nasal endoscopy. -Subjective olfactory assessment should not be undertaken in isolation, given its poor reliability. -Psychophysical assessment tools used in clinical and research settings should include reliable and validated tests of odour threshold, and/or one of odour identification or discrimination. -Comprehensive chemosensory assessment should include gustatory screening. -Smell training can be helpful in patients with olfactory loss of several aetiologies. Conclusions: We hope the current manuscript will encourage clinicians and researchers to adopt a common language, and in so doing, increase the methodological quality, consistency and generalisability of work in this field

Robust probabilistic superposition and comparison of protein structures

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is a central issue in structural bioinformatics. The standard dissimilarity measure for protein structures is the root mean square deviation (RMSD) of representative atom positions such as α-carbons. To evaluate the RMSD the structures under comparison must be superimposed optimally so as to minimize the RMSD. How to evaluate optimal fits becomes a matter of debate, if the structures contain regions which differ largely - a situation encountered in NMR ensembles and proteins undergoing large-scale conformational transitions.</p> <p>Results</p> <p>We present a probabilistic method for robust superposition and comparison of protein structures. Our method aims to identify the largest structurally invariant core. To do so, we model non-rigid displacements in protein structures with outlier-tolerant probability distributions. These distributions exhibit heavier tails than the Gaussian distribution underlying standard RMSD minimization and thus accommodate highly divergent structural regions. The drawback is that under a heavy-tailed model analytical expressions for the optimal superposition no longer exist. To circumvent this problem we work with a scale mixture representation, which implies a weighted RMSD. We develop two iterative procedures, an Expectation Maximization algorithm and a Gibbs sampler, to estimate the local weights, the optimal superposition, and the parameters of the heavy-tailed distribution. Applications demonstrate that heavy-tailed models capture differences between structures undergoing substantial conformational changes and can be used to assess the precision of NMR structures. By comparing Bayes factors we can automatically choose the most adequate model. Therefore our method is parameter-free.</p> <p>Conclusions</p> <p>Heavy-tailed distributions are well-suited to describe large-scale conformational differences in protein structures. A scale mixture representation facilitates the fitting of these distributions and enables outlier-tolerant superposition.</p

Transient Changes in Bacterioplankton Communities Induced by the Submarine Volcanic Eruption of El Hierro (Canary Islands)

Postprint4,411

siRNA inhibition of telomerase enhances the anti-cancer effect of doxorubicin in breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Doxorubicin is an effective breast cancer drug but is hampered by a severe, dose-dependent toxicity. Concomitant administration of doxorubicin and another cancer drug may be able to sensitize tumor cells to the cytotoxicity of doxorubicin and lowers the therapeutic dosage. In this study, we examined the combined effect of low-dose doxorubicin and siRNA inhibition of telomerase on breast cancer cells. We found that when used individually, both treatments were rapid and potent apoptosis inducers; and when the two treatments were combined, we observed an enhanced and sustained apoptosis induction in breast cancer cells.</p> <p>Methods</p> <p>siRNA targeting the mRNA of the protein component of telomerase, the telomerase reverse transcriptase (hTERT), was transfected into two breast cancer cell lines. The siRNA inhibition was confirmed by RT-PCR and western blot on hTERT mRNA and protein levels, respectively, and by measuring the activity level of telomerase using the TRAP assay. The effect of the hTERT siRNA on the tumorigenicity of the breast cancer cells was also studied <it>in vivo </it>by injection of the siRNA-transfected breast cancer cells into nude mice.</p> <p>The effects on cell viability, apoptosis and senescence of cells treated with hTERT siRNA, doxorubicin, and the combined treatment of doxorubicin and hTERT siRNA, were examined <it>in vitro </it>by MTT assay, FACS and SA-β-galactosidase staining.</p> <p>Results</p> <p>The hTERT siRNA effectively knocked down the mRNA and protein levels of hTERT, and reduced the telomerase activity to 30% of the untreated control. <it>In vivo</it>, the tumors induced by the hTERT siRNA-transfected cells were of reduced sizes, indicating that the hTERT siRNA also reduced the tumorigenic potential of the breast cancer cells. The siRNA treatment reduced cell viability by 50% in breast cancer cells within two days after transfection, while 0.5 μM doxorubicin treatment had a comparable effect but with a slower kinetics. The combination of hTERT siRNA and 0.5 μM doxorubicin killed twice as many cancer cells, showing a cumulative effect of the two treatments.</p> <p>Conclusion</p> <p>The study demonstrated the potential of telomerase inhibition as an effective treatment for breast cancer. When used in conjunction to doxorubicin, it could potentiate the cytotoxic effect of the drug to breast cancer cells.</p

Basin-scale transport of hydrothermal dissolved metals across the South Pacific Ocean

Hydrothermal venting along mid-ocean ridges exerts an important control on the chemical composition of sea water by serving as a major source or sink for a number of trace elements in the ocean(1-3). Of these, iron has received considerable attention because of its role as an essential and often limiting nutrient for primary production in regions of the ocean that are of critical importance for the global carbon cycle(4). It has been thought that most of the dissolved iron discharged by hydrothermal vents is lost from solution close to ridge-axis sources(2,5) and is thus of limited importance for ocean biogeochemistry(6). This long-standing view is challenged by recent studies which suggest that stabilization of hydrothermal dissolved iron may facilitate its longrange oceanic transport(7-10). Such transport has been subsequently inferred from spatially limited oceanographic observations(11-13). Here we report data from the US GEOTRACES Eastern Pacific Zonal Transect (EPZT) that demonstrate lateral transport of hydrothermal dissolved iron, manganese, and aluminium from the southern East Pacific Rise (SEPR) several thousand kilometres westward across the South Pacific Ocean. Dissolved iron exhibits nearly conservative (that is, no loss from solution during transport and mixing) behaviour in this hydrothermal plume, implying a greater longevity in the deep ocean than previously assumed(6,14). Based on our observations, we estimate a global hydrothermal dissolved iron input of three to four gigamoles per year to the ocean interior, which is more than fourfold higher than previous estimates(7,11,14). Complementary simulations with a global-scale ocean biogeochemical model suggest that the observed transport of hydrothermal dissolved iron requires some means of physicochemical stabilization and indicate that hydrothermally derived iron sustains a large fraction of Southern Ocean export productio

IDSS: deformation invariant signatures for molecular shape comparison

<p>Abstract</p> <p>Background</p> <p>Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules.</p> <p>Results</p> <p>To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms.</p> <p>Conclusion</p> <p>The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from <url>https://engineering.purdue.edu/PRECISE/IDSS</url>.</p

Using diffusion distances for flexible molecular shape comparison

<p>Abstract</p> <p>Background</p> <p>Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition.</p> <p>Results</p> <p>In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms.</p> <p>Conclusions</p> <p>We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions.</p