Cultivation of a novel cold-adapted nitrite oxidizing betaproteobacterium from the Siberian Arctic

Permafrost-affected soils of the Siberian Arctic were investigated with regard to identification of nitrite oxidizing bacteria active at low temperature. Analysis of the fatty acid profiles of enrichment cultures grown at 4°C, 10°C and 17°C revealed a pattern that was different from that of known nitrite oxidizers but was similar to fatty acid profiles of Betaproteobacteria. Electron microscopy of two enrichment cultures grown at 10°C showed prevalent cells with a conspicuous ultrastructure. Sequence analysis of the 16S rRNA genes allocated the organisms to a so far uncultivated cluster of the Betaproteobacteria, with Gallionella ferruginea as next related taxonomically described organism. The results demonstrate that a novel genus of chemolithoautotrophic nitrite oxidizing bacteria is present in polygonal tundra soils and can be enriched at low temperatures up to 17°C. Cloned sequences with high sequence similarities were previously reported from mesophilic habitats like activated sludge and therefore an involvement of this taxon in nitrite oxidation in nonarctic habitats is suggested. The presented culture will provide an opportunity to correlate nitrification with nonidentified environmental clones in moderate habitats and give insights into mechanisms of cold adaptation. We propose provisional classification of the novel nitrite oxidizing bacterium as 'Candidatus Nitrotoga arctica'

Models and simulations for the photometric lsst astronomical time series classification challenge (Plasticc)

We describe the simulated data sample for the "Photometric LSST Astronomical Time Series Classification Challenge" (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the Large Synoptic Survey Telescope (LSST), a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to 2018 December 17, and included 1,094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at this https URL. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of type Ia supernova used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models

Men's values-based factors on prostate cancer risk genetic testing: A telephone survey

BACKGROUND: While a definitive genetic test for Hereditary Prostate Cancer (HPC) is not yet available, future HPC risk testing may become available. Past survey data have shown high interest in HPC testing, but without an in-depth analysis of its underlying rationale to those considering it. METHODS: Telephone computer-assisted interviews of 400 men were conducted in a large metropolitan East-coast city, with subsequent development of psychometric scales and their correlation with intention to receive testing. RESULTS: Approximately 82% of men interviewed expressed that they "probably" or "definitely" would get genetic testing for prostate cancer risk if offered now. Factor analysis revealed four distinct, meaningful factors for intention to receive genetic testing for prostate cancer risk. These factors reflected attitudes toward testing and were labeled "motivation to get testing," "consequences and actions after knowing the test result," "psychological distress," and "beliefs of favorable outcomes if tested" (α = 0.89, 0.73, 0.73, and 0.60, respectively). These factors accounted for 70% of the total variability. The domains of motivation (directly), consequences (inversely), distress (inversely), and positive expectations (directly) all correlated with intention to receive genetic testing (p < 0.001). CONCLUSIONS: Men have strong attitudes favoring genetic testing for prostate cancer risk. The factors most associated with testing intention include those noted in past cancer genetics studies, and also highlights the relevance in considering one's motivation and perception of positive outcomes in genetic decision-making

Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)

Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set

Terrestrial invasion of pomatiopsid gastropods in the heavy-snow region of the Japanese Archipelago

<p>Abstract</p> <p>Background</p> <p>Gastropod mollusks are one of the most successful animals that have diversified in the fully terrestrial habitat. They have evolved terrestrial taxa in more than nine lineages, most of which originated during the Paleozoic or Mesozoic. The rissooidean gastropod family Pomatiopsidae is one of the few groups that have evolved fully terrestrial taxa during the late Cenozoic. The pomatiopsine diversity is particularly high in the Japanese Archipelago and the terrestrial taxa occur only in this region. In this study, we conducted thorough samplings of Japanese pomatiopsid species and performed molecular phylogenetic analyses to explore the patterns of diversification and terrestrial invasion.</p> <p>Results</p> <p>Molecular phylogenetic analyses revealed that Japanese Pomatiopsinae derived from multiple colonization of the Eurasian Continent and that subsequent habitat shifts from aquatic to terrestrial life occurred at least twice within two Japanese endemic lineages. Each lineage comprises amphibious and terrestrial species, both of which are confined to the mountains in heavy-snow regions facing the Japan Sea. The estimated divergence time suggested that diversification of these terrestrial lineages started in the Late Miocene, when active orogenesis of the Japanese landmass and establishment of snowy conditions began.</p> <p>Conclusions</p> <p>The terrestrial invasion of Japanese Pomatiopsinae occurred at least twice beside the mountain streamlets of heavy-snow regions, which is considered the first case of this event in the area. Because snow coverage maintains stable temperatures and high humidity on the ground surface, heavy-snow conditions may have paved the way for these organisms from freshwater to land via mountain streamlets by preventing winter desiccation in mountain valleys. The fact that the terrestrialization of Pomatiopsidae occurred only in year-round wet environments, but not in seasonally dried regions, provides new insight into ancient molluscan terrestrialization.</p

Pediatric DXA: technique and interpretation

This article reviews dual X-ray absorptiometry (DXA) technique and interpretation with emphasis on the considerations unique to pediatrics. Specifically, the use of DXA in children requires the radiologist to be a “clinical pathologist” monitoring the technical aspects of the DXA acquisition, a “statistician” knowledgeable in the concepts of Z-scores and least significant changes, and a “bone specialist” providing the referring clinician a meaningful context for the numeric result generated by DXA. The patient factors that most significantly influence bone mineral density are discussed and are reviewed with respect to available normative databases. The effects the growing skeleton has on the DXA result are also presented. Most important, the need for the radiologist to be actively involved in the technical and interpretive aspects of DXA is stressed. Finally, the diagnosis of osteoporosis should not be made on DXA results alone but should take into account other patient factors

Polarizable Water Model for the Coarse-Grained MARTINI Force Field

Coarse-grained (CG) simulations have become an essential tool to study a large variety of biomolecular processes, exploring temporal and spatial scales inaccessible to traditional models of atomistic resolution. One of the major simplifications of CG models is the representation of the solvent, which is either implicit or modeled explicitly as a van der Waals particle. The effect of polarization, and thus a proper screening of interactions depending on the local environment, is absent. Given the important role of water as a ubiquitous solvent in biological systems, its treatment is crucial to the properties derived from simulation studies. Here, we parameterize a polarizable coarse-grained water model to be used in combination with the CG MARTINI force field. Using a three-bead model to represent four water molecules, we show that the orientational polarizability of real water can be effectively accounted for. This has the consequence that the dielectric screening of bulk water is reproduced. At the same time, we parameterized our new water model such that bulk water density and oil/water partitioning data remain at the same level of accuracy as for the standard MARTINI force field. We apply the new model to two cases for which current CG force fields are inadequate. First, we address the transport of ions across a lipid membrane. The computed potential of mean force shows that the ions now naturally feel the change in dielectric medium when moving from the high dielectric aqueous phase toward the low dielectric membrane interior. In the second application we consider the electroporation process of both an oil slab and a lipid bilayer. The electrostatic field drives the formation of water filled pores in both cases, following a similar mechanism as seen with atomistically detailed models

Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock

<p>Abstract</p> <p>Background</p> <p>Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.</p> <p>Results</p> <p>The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.</p> <p>Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.</p> <p>Conclusion</p> <p>Our results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.</p

Autophagy Protein Atg3 is Essential for Maintaining Mitochondrial Integrity and for Normal Intracellular Development of Toxoplasma gondii Tachyzoites

Autophagy is a cellular process that is highly conserved among eukaryotes and permits the degradation of cellular material. Autophagy is involved in multiple survival-promoting processes. It not only facilitates the maintenance of cell homeostasis by degrading long-lived proteins and damaged organelles, but it also plays a role in cell differentiation and cell development. Equally important is its function for survival in stress-related conditions such as recycling of proteins and organelles during nutrient starvation. Protozoan parasites have complex life cycles and face dramatically changing environmental conditions; whether autophagy represents a critical coping mechanism throughout these changes remains poorly documented. To investigate this in Toxoplasma gondii, we have used TgAtg8 as an autophagosome marker and showed that autophagy and the associated cellular machinery are present and functional in the parasite. In extracellular T. gondii tachyzoites, autophagosomes were induced in response to amino acid starvation, but they could also be observed in culture during the normal intracellular development of the parasites. Moreover, we generated a conditional T. gondii mutant lacking the orthologue of Atg3, a key autophagy protein. TgAtg3-depleted parasites were unable to regulate the conjugation of TgAtg8 to the autophagosomal membrane. The mutant parasites also exhibited a pronounced fragmentation of their mitochondrion and a drastic growth phenotype. Overall, our results show that TgAtg3-dependent autophagy might be regulating mitochondrial homeostasis during cell division and is essential for the normal development of T. gondii tachyzoites