82 research outputs found
Water induced sediment levitation enhances downslope transport on Mars
On Mars, locally warm surface temperatures (~293 K) occur, leading to the possibility of (transient) liquid water on the surface. However, water exposed to the martian atmosphere will boil, and the sediment transport capacity of such unstable water is not well understood. Here, we present laboratory studies of a newly recognized transport mechanism: “levitation” of saturated sediment bodies on a cushion of vapor released by boiling. Sediment transport where this mechanism is active is about nine times greater than without this effect, reducing the amount of water required to transport comparable sediment volumes by nearly an order of magnitude. Our calculations show that the effect of levitation could persist up to ~48 times longer under reduced martian gravity. Sediment levitation must therefore be considered when evaluating the formation of recent and present-day martian mass wasting features, as much less water may be required to form such features than previously thought
Formation of gullies on Mars by debris flows triggered by CO_2 sublimation
Martian gully landforms resemble terrestrial debris flows formed by the action of liquid water and have thus been interpreted as evidence for potential habitable environments on Mars within the past few millennia. However, ongoing gully formation has been detected under surface conditions much too cold for liquid water, but at times in the martian year when a thin layer of seasonal CO_2 frost is present and defrosting above the regolith. These observations suggest that the CO_2 condensation–sublimation cycle could play a role in gully formation. Here we use a thermo-physical numerical model of the martian regolith underlying a CO_2 ice layer and atmosphere to show that the pores beneath the ice layer can be filled with CO_2 ice and subjected to extreme pressure variations during the defrosting season. The subsequent gas fluxes can destabilize the regolith material and induce gas-lubricated debris flows with geomorphic characteristics similar to martian gullies. Moreover, we find that subsurface CO_2 ice condensation, sublimation and pressurization occurs at conditions found at latitudes and slope orientations where gullies are observed. We conclude that martian gullies can result from geologic dry ice processes that have no terrestrial analogues and do not require liquid water. Such dry ice processes may have helped shape the evolution of landforms elsewhere on the martian surface
A large new grater exposes the limits of water ice on Mars
Water ice in the Martian mid-latitudes has advanced and retreated in response to variations in the planet's orbit, obliquity, and climate. A 150 m-diameter new impact crater near 35°N provides the lowest-latitude impact exposure of subsurface ice on Mars. This is the largest known ice-exposing crater and provides key constraints on Martian climate history. This crater indicates a regional, relatively pure ice deposit that is unstable and has nearly vanished. In the past, this deposit may have been tens of meters thick and extended equatorward of 35°N. We infer that it is overlain by pore ice emplaced during temporary stable intervals, due to recent climate variability. The marginal survival of ice here suggests that it is near the edge of shallow ice that regularly exchanges with the atmosphere
Largest recent impact craters on Mars: Orbital imaging and surface seismic co-investigation.
Two >130-meter-diameter impact craters formed on Mars during the later half of 2021. These are the two largest fresh impact craters discovered by the Mars Reconnaissance Orbiter since operations started 16 years ago. The impacts created two of the largest seismic events (magnitudes greater than 4) recorded by InSight during its 3-year mission. The combination of orbital imagery and seismic ground motion enables the investigation of subsurface and atmospheric energy partitioning of the impact process on a planet with a thin atmosphere and the first direct test of martian deep-interior seismic models with known event distances. The impact at 35°N excavated blocks of water ice, which is the lowest latitude at which ice has been directly observed on Mars
Maintaining RNA integrity in a homogeneous population of mammary epithelial cells isolated by Laser Capture Microdissection
Background: Laser-capture microdissection (LCM) that enables the isolation of specific cell populations from complex tissues under morphological control is increasingly used for subsequent gene expression studies in cell biology by methods such as real-time quantitative PCR (qPCR), microarrays and most recently by RNA-sequencing. Challenges are i) to select precisely and efficiently cells of interest and ii) to maintain RNA integrity. The mammary gland which is a complex and heterogeneous tissue, consists of multiple cell types, changing in relative proportion during its development and thus hampering gene expression profiling comparison on whole tissue between physiological stages. During lactation, mammary epithelial cells (MEC) are predominant. However several other cell types, including myoepithelial (MMC) and immune cells are present, making it difficult to precisely determine the specificity of gene expression to the cell type of origin. In this work, an optimized reliable procedure for producing RNA from alveolar epithelial cells isolated from frozen histological sections of lactating goat, sheep and cow mammary glands using an infrared-laser based Arcturus Veritas LCM (Applied Biosystems®) system has been developed. The following steps of the microdissection workflow: cryosectioning, staining, dehydration and harvesting of microdissected cells have been carefully considered and designed to ensure cell capture efficiency without compromising RNA integrity.[br/] Results: The best results were obtained when staining 8 μm-thick sections with Cresyl violet® (Ambion, Applied Biosystems®) and capturing microdissected cells during less than 2 hours before RNA extraction. In addition, particular attention was paid to animal preparation before biopsies or slaughtering (milking) and freezing of tissue blocks which were embedded in a cryoprotective compound before being immersed in isopentane. The amount of RNA thus obtained from ca.150 to 250 acini (300,000 to 600,000 μm2) ranges between 5 to 10 ng. RNA integrity number (RIN) was ca. 8.0 and selectivity of this LCM protocol was demonstrated through qPCR analyses for several alveolar cell specific genes, including LALBA (α-lactalbumin) and CSN1S2 (αs2-casein), as well as Krt14 (cytokeratin 14), CD3e and CD68 which are specific markers of MMC, lymphocytes and macrophages, respectively.[br/] Conclusions: RNAs isolated from MEC in this manner were of very good quality for subsequent linear amplification, thus making it possible to establish a referential gene expression profile of the healthy MEC, a useful platform for tumor biomarker discovery
Text Mining Improves Prediction of Protein Functional Sites
We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions
The ineffectiveness of entrepreneurship policy:Is policy formulation to blame?
Entrepreneurship policy has been criticised for its lack of effectiveness. Some scholars, such as Scott Shane in this journal, have argued that it is ‘bad’ public policy. But this simply begs the question why the legislative process should generate bad policy? To answer this question this study examines the UK’s enterprise policy process in the 2009–2010 period. It suggests that a key factor for the ineffectiveness of policy is how it is formulated. This stage in the policy process is seldom visible to those outside of government departments and has been largely ignored by prior research. The application of institutional theory provides a detailed theoretical understanding of the actors and the process by which enterprise policy is formulated. We find that by opening up the ‘black box’ of enterprise policy formulation, the process is dominated by powerful actors who govern the process with their interests
Innovation Practices in Emerging Economies: Do University Partnerships Matter?
Enterprises’ resources and capabilities determine their ability to achieve competitive advantage. In this regard, the key innovation challenges that enterprises face are liabilities associated with their age and size, and the entry barriers imposed on them. In this line, a growing number of enterprises are starting to implement innovation practices in which they employ both internal/external flows of knowledge in order to explore/exploit innovation in collaboration with commercial or scientific agents. Within this context, universities play a significant role providing fertile knowledge-intensive environments to support the exploration and exploitation of innovative and entrepreneurial ideas, especially in emerging economies, where governments have created subsidies to promote enterprise innovation through compulsory university partnerships. Based on these ideas, the purpose of this exploratory research is to provide a better understanding about the role of universities on enterprises’ innovation practices in emerging economies. More concretely, in the context of Mexico, we explored the enterprises’ motivations to collaborate with universities in terms of innovation purposes (exploration and exploitation) or alternatives to access to public funds (compulsory requirement of being involved in a university partnership). Using a sample of 10,167 Mexican enterprises in the 2012 Research and Technological Development Survey collected by the Mexican National Institute of Statistics and Geography, we tested a multinomial regression model. Our results provide insights about the relevant role of universities inside enterprises’ exploratory innovation practices, as well as, in the access of R&D research subsidies
Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction
The comparison of eight tools applicable to ligand-binding site prediction is presented. The methods examined cover three types of approaches: the geometrical (CASTp, PASS, Pocket-Finder), the physicochemical (Q-SiteFinder, FOD) and the knowledge-based (ConSurf, SuMo, WebFEATURE). The accuracy of predictions was measured in reference to the catalytic residues documented in the Catalytic Site Atlas. The test was performed on a set comprising selected chains of hydrolases. The results were analysed with regard to size, polarity, secondary structure, accessible solvent area of predicted sites as well as parameters commonly used in machine learning (F-measure, MCC). The relative accuracies of predictions are presented in the ROC space, allowing determination of the optimal methods by means of the ROC convex hull. Additionally the minimum expected cost analysis was performed. Both advantages and disadvantages of the eight methods are presented. Characterization of protein chains in respect to the level of difficulty in the active site prediction is introduced. The main reasons for failures are discussed. Overall, the best performance offers SuMo followed by FOD, while Pocket-Finder is the best method among the geometrical approaches
Inequalities in mortality among refugees and immigrants compared to native Danes – a historical prospective cohort study
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