Reverse engineering of biochar

This study underpins quantitative relationships that account for the combined effects that starting biomass and peak pyrolysis temperature have on physico-chemical properties of biochar. Meta-data was assembled from published data of diverse biochar samples (n = 102) to (i) obtain networks of intercorrelated properties and (ii) derive models that predict biochar properties. Assembled correlation networks provide a qualitative overview of the combinations of biochar properties likely to occur in a sample. Generalized Linear Models are constructed to account for situations of varying complexity, including: dependence of biochar properties on single or multiple predictor variables, where dependence on multiple variables can have additive and/or interactive effects; non-linear relation between the response and predictors; and non-Gaussian data distributions. The web-tool Biochar Engineering implements the derived models to maximize their utility and distribution. Provided examples illustrate the practical use of the networks, models and web-tool to engineer biochars with prescribed properties desirable for hypothetical scenarios

Enzyme self-label-bound ATTO700 in single-molecule and super-resolution microscopy

Herein, we evaluate near-infrared ATTO700 as an acceptor in SNAP- and Halo-tag protein labelling for Förster Resonance Energy Transfer (FRET) by ensemble and single molecule measurements. Microscopy of cell surface proteins in live cells is perfomed including super-resolution stimulated emission by depletion (STED) nanoscopy

BASEWECS - Influence of the Baltic Sea and its annual ice coverage on the water and energy budget of the Baltic Sea

BASEWECS is a contribution to the German Climate Research Program DEKLIM. The project started in May 2001 and lasted until December 2004. BASEWECS aimed at the investigation of the influence of the Baltic Sea and its annual ice coverage on the water and energy budget of the BALTEX are

Effect of Different Phospholipids on α-Secretase Activity in the Non-Amyloidogenic Pathway of Alzheimer’s Disease

Alzheimer’s disease (AD) is characterized by extracellular accumulation of amyloid-β peptide (Aβ), generated by proteolytic processing of the amyloid precursor protein (APP) by β- and γ-secretase. Aβ generation is inhibited when the initial ectodomain shedding is caused by α-secretase, cleaving APP within the Aβ domain. Therefore, an increase in α-secretase activity is an attractive therapeutic target for AD treatment. APP and the APP-cleaving secretases are all transmembrane proteins, thus local membrane lipid composition is proposed to influence APP processing. Although several studies have focused on γ-secretase, the effect of the membrane lipid microenvironment on α-secretase is poorly understood. In the present study, we systematically investigated the effect of fatty acid (FA) acyl chain length (10:0, 12:0, 14:0, 16:0, 18:0, 20:0, 22:0, 24:0), membrane polar lipid headgroup (phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine), saturation grade and the FA double-bond position on α-secretase activity. We found that α-secretase activity is significantly elevated in the presence of FAs with short chain length and in the presence of polyunsaturated FAs, whereas variations in the phospholipid headgroups, as well as the double-bond position, have little or no effect on α-secretase activity. Overall, our study shows that local lipid membrane composition can influence α-secretase activity and might have beneficial effects for AD

Xist and Tsix transcription dynamics is regulated by the X-to-autosome ratio and semistable transcriptional states

In female mammals, X chromosome inactivation (XCI) is a key process in the control of gene dosage compensation between Xlinked genes and autosomes. Xist and Tsix, two overlapping antisense-transcribed noncoding genes, are central elements of the X inactivation center (Xic) regulating XCI. Xist upregulation results in the coating of the entire X chromosome by Xist RNA in cis, whereas Tsix transcription acts as a negative regulator of Xist. Here, we generated Xist and Tsix reporter mouse embryonic stem (ES) cell lines to study the genetic and dynamic regulation of these genes upon differentiation. Our results revealed mutually antagonistic roles for Tsix on Xist and vice versa and indicate the presence of semistable transcriptional states of the Xic locus predicting the outcome of XCI. These transcriptional states are instructed by the X-t

Microscale spatial distribution and soil organic matter persistence in top and subsoil

The spatial distribution of organic substrates and microscale soil heterogeneity significantly influence organic matter (OM) persistence as constraints on OM accessibility to microorganisms. However, it is unclear how changes in OM spatial heterogeneity driven by factors such as soil depth affect the relative importance of substrate spatial distribution on OM persistence. This work evaluated the decomposition and persistence of 13C and 15N labeled water-extractable OM inputs over 50 days as either hotspot (i.e., pelleted in 1 – 2 mm-size pieces) or distributed (i.e., added as OM < 0.07 µm suspended in water) forms in topsoil (0-0.2 m) and subsoil (0.8-0.9 m) samples of an Andisol. We observed greater persistence of added C in the subsoil with distributed OM inputs relative to hotspot OM, indicated by a 17% reduction in cumulative mineralization of the added C and a 10% higher conversion to mineral-associated OM. A lower substrate availability potentially reduced mineralization due to OM dispersion throughout the soil. NanoSIMS (nanoscale secondary ion mass spectrometry) analysis identified organo-mineral associations on cross-sectioned aggregate interiors in the subsoil. On the other hand, in the topsoil, we did not observe significant differences in the persistence of OM, suggesting that the large amounts of particulate OM already present in the soil outweighed the influence of added OM spatial distribution. Here, we demonstrated under laboratory conditions that the spatial distribution of fresh OM input alone significantly affected the decomposition and persistence of OM inputs in the subsoil. On the other hand, spatial distribution seems to play a lower role in topsoils rich in particulate OM. The divergence in the influence of OM spatial distribution between the top and subsoil is likely driven by differences in soil mineralogy and OM composition.Microscale spatial distribution and soil organic matter persistence in top and subsoilpublishedVersio