6 resultados para Two-Dimensional Electrophoresis
em Publishing Network for Geoscientific
Resumo:
Matlab script file of a two-dimensional (2-D) peat microtopographical model together with other supplementary files that are required to run the model.
Resumo:
Ocean acidification (OA) is beginning to have noticeable negative impact on calcification rate, shell structure and physiological energy budgeting of several marine organisms; these alter the growth of many economically important shellfish including oysters. Early life stages of oysters may be particularly vulnerable to OA-driven low pH conditions because their shell is made up of the highly soluble form of calcium carbonate (CaCO3) mineral, aragonite. Our long-term CO2 perturbation experiment showed that larval shell growth rate of the oyster species Crassostrea hongkongensis was significantly reduced at pH < 7.9 compared to the control (8.2). To gain new insights into the underlying mechanisms of low-pH-induced delays in larval growth, we have examined the effect of pH on the protein expression pattern, including protein phosphorylation status at the pediveliger larval stage. Using two-dimensional electrophoresis and mass spectrometry, we demonstrated that the larval proteome was significantly altered by the two low pH treatments (7.9 and 7.6) compared to the control pH (8.2). Generally, the number of expressed proteins and their phosphorylation level decreased with low pH. Proteins involved in larval energy metabolism and calcification appeared to be down-regulated in response to low pH, whereas cell motility and production of cytoskeletal proteins were increased. This study on larval growth coupled with proteome change is the first step toward the search for novel Protein Expression Signatures indicative of low pH, which may help in understanding the mechanisms involved in low pH tolerance.
Resumo:
Ocean acidification and warming are both primarily caused by increased levels of atmospheric CO2, and marine organisms are exposed to these two stressors simultaneously. Although the effects of temperature on fish have been investigated over the last century, the long-term effects of moderate CO2 exposure and the combination of both stressors are almost entirely unknown. A proteomics approach was used to assess the adverse physiological and biochemical changes that may occur from the exposure to these two environmental stressors. We analysed gills and blood plasma of Atlantic halibut (Hippoglossus hippoglossus) exposed to temperatures of 12°C (control) and 18°C (impaired growth) in combination with control (400 µatm) or high-CO2 water (1000 µatm) for 14 weeks. The proteomic analysis was performed using two-dimensional gel electrophoresis (2DE) followed by Nanoflow LC-MS/MS using a LTQ-Orbitrap. The high-CO2 treatment induced the up-regulation of immune system-related proteins, as indicated by the up-regulation of the plasma proteins complement component C3 and fibrinogen beta chain precursor in both temperature treatments. Changes in gill proteome in the high-CO2 (18°C) group were mostly related to increased energy metabolism proteins (ATP synthase, malate dehydrogenase, malate dehydrogenase thermostable, and fructose-1,6-bisphosphate aldolase), possibly coupled to a higher energy demand. Gills from fish exposed to high-CO2 at both temperature treatments showed changes in proteins associated with increased cellular turnover and apoptosis signalling (annexin 5, eukaryotic translation elongation factor 1 gamma, receptor for protein kinase C, and putative ribosomal protein S27). This study indicates that moderate CO2-driven acidification, alone and combined with high temperature, can elicit biochemical changes that may affect fish health.
Resumo:
In low-accumulation regions, the reliability of d18O-derived temperature signals from ice cores within the Holocene is unclear, primarily due to the small climate changes relative to the intrinsic noise of the isotopic signal. In order to learn about the representativity of single ice cores and to optimise future ice-core-based climate reconstructions, we studied the stable-water isotope composition of firn at Kohnen station, Dronning Maud Land, Antarctica. Analysing d18O in two 50 m long snow trenches allowed us to create an unprecedented, two-dimensional image characterising the isotopic variations from the centimetre to the hundred-metre scale. This data set includes the complete trench oxygen isotope record together with the meta data used in the study.
Resumo:
Increasing amounts of data is collected in most areas of research and application. The degree to which this data can be accessed, analyzed, and retrieved, is a decisive in obtaining progress in fields such as scientific research or industrial production. We present a novel methodology supporting content-based retrieval and exploratory search in repositories of multivariate research data. In particular, our methods are able to describe two-dimensional functional dependencies in research data, e.g. the relationship between ination and unemployment in economics. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models to describe the data mathematically. We denote this approach Regressional Features and use it for content-based search and, since our approach motivates an intuitive definition of interestingness, for exploring the most interesting data. We apply our method on considerable real-world research datasets, showing the usefulness of our approach for user-centered access to research data in a Digital Library system.
Resumo:
The density of firn is an important property for monitoring and modeling the ice sheet as well as to model the pore close-off and thus to interpret ice core-based greenhouse gas records. One feature, which is still in debate, is the potential existence of an annual cycle of firn density in low-accumulation regions. Several studies describe or assume seasonally successive density layers, horizontally evenly distributed, as seen in radar data. On the other hand, high-resolution density measurements on firn cores in Antarctica and Greenland showed no clear seasonal cycle in the top few meters. A major caveat of most existing snow-pit and firn-core based studies is that they represent one vertical profile from a laterally heterogeneous density field. To overcome this, we created an extensive dataset of horizontal and vertical density data at Kohnen Station, Dronning Maud Land on the East Antarctic Plateau. We drilled and analyzed three 90 m long firn cores as well as 160 one meter long vertical profiles from two elongated snow trenches to obtain a two dimensional view of the density variations. The analysis of the 45 m wide and 1 m deep density fields reveals a seasonal cycle in density. However, the seasonality is overprinted by strong stratigraphic noise, making it invisible when analyzing single firn cores. Our density dataset extends the view from the local ice-core perspective to a hundred meter scale and thus supports linking spatially integrating methods such as radar and seismic studies to ice and firn cores.