Observation and identification of metabolites emerging during postmortem decomposition of brain tissue by means of in situ 1H-magnetic resonance spectroscopy

Postmortem decomposition of brain tissue was investigated by (1)H-magnetic resonance spectroscopy (MRS) in a sheep head model and selected human cases. Aiming at the eventual estimation of postmortem intervals in forensic medicine, this study focuses on the characterization and identification of newly observed metabolites. In situ single-voxel (1)H-MRS at 1.5 T was complemented by multidimensional homo- and heteronuclear high-resolution NMR spectroscopy of an extract of sheep brain tissue. The inclusion of spectra of model solutions in the program LC Model confirmed the assignments in situ. The first postmortem phase was characterized mainly by changes in the concentrations of metabolites usually observed in vivo and by the appearance of previously reported decay products. About 3 days postmortem, new metabolites, including free trimethylammonium, propionate, butyrate, and iso-butyrate, started to appear in situ. Since the observed metabolites and the time course is comparable in sheep and human brain tissue, the model system seems to be appropriate.

INTERACTIVE CONTROLS OF WATER TABLE POSITION AND PLANT FUNCTIONAL TYPES ON PEAT POREWATER CHARACTER IN NORTHERN BOG ECOSYSTEMS: IMPLICATIONS FOR CARBON CYCLING DYNAMICS

Northern wetlands, and particularly peatlands, have been shown to store around 30% of the world's soil carbon and thus play a significant role in the carbon cycle of our planet. Changes in climate are altering peatland hydrology and vegetation communities. These changes are possibly resulting in declines in the ability of peatlands to sequester carbon because losses through carbon oxidation and mineralization are likely to increase relative to C inputs from net primary production in a warmer, drier climate. However, the consequences of interactive effects of altered hydrology and vegetation on carbon storage are not well understood. This research evaluated the importance of plant species, water table, and their interactive effects on porewater quality in a northern peatland with an average pH of 4.54, ranging from 4.15 to 4.8. We assessed the effects of plant functional group (ericaceous shrubs, sedges, and bryophytes) and water table position on biogeochemical processes. Specifically, we measured dissolved organic carbon (DOC), total dissolved nitrogen (TDN), potential enzyme activity, organic acids, anions and cations, spectral indexes of aromaticity, and phenolic content. Our results indicate that acetate and propionate concentrations in the sedge-dominated communities declined with depth and water table drawdown, relative to the control and ericaceous treatments. DOC increased in the lowered water table treatments in all vegetation community types, and the peat porewater C:N ratio declined in the sedge-dominated treatments when the water table was lowered. The relationship between DOC and ferrous iron showed significant responses to vegetation type; the exclusion of Ericaceae resulted in less ferrous iron per unit DOC compared to mixed species treatments and Ericaceae alone. This observation was corroborated with higher mean oxidation redox potential profiles (integrating 20, 40, and 70 cm) measured in the sedge treatments, compared with the mixed and Ericaceae species treatments over a growing season. Enzymatic activities did not show as strong of a response to treatments as expected; the oxidative enzyme peroxidase and the hydrolytic enzyme phosphatase were the only enzymes to respond to water table, where the potential activity of both enzymes increased with water table drawdown. Overall, there were significant interactive effects between changes in vegetation and water table position on peat porewater composition. These data suggest that vegetation effects on oxidation reduction potentials and peat porewater character can be as important as water table position in northern bog ecosystems.

Observation errors in early historical upper-air observations

Upper-air observations are a fundamental data source for global atmospheric data products, but uncertainties, particularly in the early years, are not well known. Most of the early observations, which have now been digitized, are prone to a large variety of undocumented uncertainties (errors) that need to be quantified, e.g., for their assimilation in reanalysis projects. We apply a novel approach to estimate errors in upper-air temperature, geopotential height, and wind observations from the Comprehensive Historical Upper-Air Network for the time period from 1923 to 1966. We distinguish between random errors, biases, and a term that quantifies the representativity of the observations. The method is based on a comparison of neighboring observations and is hence independent of metadata, making it applicable to a wide scope of observational data sets. The estimated mean random errors for all observations within the study period are 1.5 K for air temperature, 1.3 hPa for pressure, 3.0 ms−1for wind speed, and 21.4° for wind direction. The estimates are compared to results of previous studies and analyzed with respect to their spatial and temporal variability.

Developmental Changes in the Structure and Composition of the Postsynaptic Density

The development of the brain and its underlying circuitry is dependent on the formation of trillions of chemical synapses, which are highly specialized contacts that regulate the flow of information from one neuron to the next. It is through these synaptic connections that neurons wire together into networks capable of performing specific tasks, and activity-dependent changes in their structural and physiological state is one way that the brain is thought to adapt and store information. At the ultrastructural level, developmental and activity-dependent changes in the size and shape of dendritic spines have been well documented, and it is widely believed that structural changes in spines are a hallmark sign of synapse maturation and alteration of synaptic physiology. While changes in spine structure have been studied extensively, changes in one of its most prominent components, the postsynaptic density (PSD), have largely evaded observation. The PSD is a protein-rich organelle on the cytoplasmic side of the postsynaptic membrane, where it sits in direct opposition to the presynaptic terminal. The PSD functions both to cluster neurotransmitter receptors at the cell surface as well as organize the intracellular signaling molecules responsible for transducing extracellular signals to the postsynaptic cell. Much is known about the chemical composition of the PSD, but the structural arrangement of its molecular components is not well documented. Adding to the difficulty of understanding such a complex mass of protein machinery is the fact that its protein composition is known to change in response to synaptic activity, meaning that its structure is plastic and no two PSDs are identical. Here, immuno-gold labeling and electron tomography of PSDs isolated throughout development was used to track changes in both the structure and molecular composition of the PSD. State-of-the-art cryo-electron tomography was used to study the fine structure of the PSD during development, and provides an unprecedented glimpse into its molecular architecture in an un-fixed, unstained and hydrated state. Through this analysis, large structural and compositional changes are apparent and suggest a model by which the PSD is first assembled as a mesh-like lattice of proteins that function as support for the later recruitment of various PSD components. Spatial analysis of the recruitment of proteins into the PSD demonstrated that its assembly has an underlying order.

Observation of Electron Neutrino Appearance in a Muon Neutrino Beam

The T2K experiment has observed electron neutrino appearance in a muon neutrino beam produced 295 km from the Super-Kamiokande detector with a peak energy of 0.6 GeV. A total of 28 electron neutrino events were detected with an energy distribution consistent with an appearance signal, corresponding to a significance of 7.3σ when compared to 4.92 ± 0.55 expected background events. In the PMNS mixing model, the electron neutrino appearance signal depends on several parameters including three mixing angles θ12, θ23, θ13, a mass difference Δm232 and a CP violating phase δCP. In this neutrino oscillation scenario, assuming |Δm232|=2.4×10−3 eV2, sin2θ23=0.5, δCP=0, and Δm232>0 (Δm232<0), a best-fit value of sin22θ13 = 0.140+0.038−0.032 (0.170+0.045−0.037) is obtained.