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Plants and microorganisms, besides the climate, drive nitrogen (N) cycling in ecosystems. Our objective was to investigate N losses and N acquisition strategies along a unique ecosystem-sequence (ecosequence) ranging from arid shrubland through Mediterranean woodland to temperate rainforest. These ecosystems differ in mean annual precipitation, mean annual temperate, and vegetation cover, but developed on similar granitoid soil parent material, were addressed using a combination of molecular biology and soil biogeochemical tools. Soil N and carbon (C) contents, δ15N signatures, activities of N acquiring extracellular enzymes as well as the abundance of soil bacteria and fungi, and diazotrophs in bulk topsoil and rhizosphere were determined. Relative fungal abundance in the rhizosphere was higher under woodland and forest than under shrubland. This indicates toward plants' higher C investment into fungi in the Mediterranean and temperate rainforest sites than in the arid site. Fungi are likely to decompose lignified forest litter for efficient recycling of litter-derived N and further nutrients. Rhizosphere—a hotspot for the N fixation—was enriched in diazotrophs (factor 8 to 16 in comparison to bulk topsoil) emphasizing the general importance of root/microbe association in N cycle. These results show that the temperate rainforest is an N acquiring ecosystem, whereas N in the arid shrubland is strongly recycled. Simultaneously, the strongest 15N enrichment with decreasing N content with depth was detected in the Mediterranean woodland, indicating that N mineralization and loss is highest (and likely the fastest) in the woodland across the continental transect. Higher relative aminopeptidase activities in the woodland than in the forest enabled a fast N mineralization. Relative aminopeptidase activities were highest in the arid shrubland. The highest absolute chitinase activities were observed in the forest. This likely demonstrates that (a) plants and microorganisms in the arid shrubland invest largely into mobilization and reutilization of organically bound N by exoenzymes, and (b) that the ecosystem N nutrition shifts from a peptide-based N in the arid shrubland to a peptide- and chitin-based N nutrition in the temperate rainforest, where the high N demand is complemented by intensive N fixation in the rhizosphere.
The main obstacle to bottom ash (BA) being used as a recycling aggregate is the content of salts and potential toxic elements (PTEs), concentrated in a layer that coats BA particles. This work presents a dry treatment for the removal of salts and PTEs from BA particles. Two pilotscale abrasion units (with/without the removal of the fine particles) were fed with different BA samples. The performance of the abrasion tests was assessed through the analyses of particle size and moisture, and that of the column leaching tests at solid-to-liquid ratios between 0.3 and 4. The results were: the particle-size distribution of the treated materials was homogeneous (25 wt % had dimensions <6.3 mm) and their moisture halved, as well as the electrical conductivity of the leachates. A significant decrease was observed in the leachates of the treated BA for sulphates (44%),
chlorides (26%), and PTEs (53% Cr, 60% Cu and 8% Mo). The statistical analysis revealed good correlations between chloride and sulphate concentrations in the leachates with Ba, Cu, Mo, and Sr, illustrating the consistent behavior of the major and minor components of the layer surrounding BA particles. In conclusion, the tested process could be considered as promising for the improvement of BA valorization.
The Infrastar training school provides lectures and hands-on training to Master and PhD students, early-stage researchers and (young) professionals on all aspects of asset management of civil infrastructures with respect to fatigue of materials. It is organized yearly since 2019 and up to 20 profiles are selected to attend the 3.5-day training.
A team of 7 teachers provides insight in multi-disciplinary and intersectoral basic concepts in three core fields, ranging from the design to the dismantling of the structures (bridges and wind turbines):
1. Monitoring and auscultation,
2. Structural and action models,
3. Reliability, risk and decision analyses.
Each year, a recognized expert is invited to deliver a keynote lecture to raise interest in a specific aspect of one of the fields covered. The presentation is recorded and published on the training school website.
Phosphotyrosine residues are essential functional switches in health and disease. Thus, phosphotyrosine biomimetics are crucial for the development of chemical tools and drug molecules. We report here the discovery and investigation of pentafluorophosphato amino acids as novel phosphotyrosine biomimetics. A mild acidic pentafluorination protocol was developed and two PF5-amino acids were prepared and employed in peptide synthesis. Their structures, reactivities, and fluorine-specific interactions were studied by NMR and IR spectroscopy, X-ray diffraction, and in bioactivity assays. The mono-anionic PF5 motif displayed an amphiphilic character binding to hydrophobic surfaces, to water molecules, and to protein-binding sites, exploiting charge and H−F-bonding interactions. The novel motifs bind 25- to 30-fold stronger to the phosphotyrosine binding site of the protein tyrosine phosphatase PTP1B than the best current biomimetics, as rationalized by computational methods, including molecular dynamics simulations.
A systematic study has been carried out to investigate the neutron transmission signal as a function of sample temperature. In particular, the experimentally determined wavelength-dependent neutron attenuation spectra for a martensitic steel at temperatures ranging from 21 to 700°C are compared with simulated data. A theoretical description that includes the Debye–Waller factor in order to describe the temperature influence on the neutron cross sections was implemented in the nxsPlotter software and used for the simulations. The analysis of the attenuation coefficients at varying temperatures shows that the missing contributions due to elastic and inelastic scattering can be clearly distinguished: while the elastically scattered intensities decrease with higher temperatures, the inelastically scattered intensities increase, and the two can be separated from each other by analysing unique sharp features in the form of Bragg edges. This study presents the first systematic approach to quantify this effect and can serve as a basis , for example, to correct measurements taken during in situ heat treatments, in many cases being a prerequisite for obtaining quantifiable results.
The application of characterization methods with high spatial resolution to the analysis of buried coating/metal interfaces requires the design and use of model systems. Herein, an epoxy-like thin film is used as a model coating resembling the epoxy-based coatings and adhesives widely used in technical applications. Spin coating is used for the deposition of a 30 nm-thin bilayer (BL) composed of poly-(ethylenimine) (PEI) and poly[(o-cresyl glycidyl ether)-co-formaldehyde] (CNER). Fourier-transform infrared spectroscopy (FTIR) results confirm that the exposure of coated AA2024-T3 (AA) samples to the corrosive electrolyte solution does not cause the degradation of the polymer layer. In situ atomic force microscopy (AFM) studies are performed to monitor local corrosion processes at the buried interface of the epoxy-like film and the AA2024-T3 aluminum alloy surface in an aqueous electrolyte solution. Hydrogen evolution due to the reduction of water as the cathodic corrosion reaction leads to local blister formation. Based on the results of the complementary energy-dispersive X-ray spectroscopy (EDX) analysis performed at the same region of interest, most of the hydrogen evolved originates at the vicinity of Mg-containing intermetallic particles.
Mass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of living cells on a molecular level. Currently, only a few deep learning approaches exist that involve peptide fragmentation spectra, which represent partial sequence information of proteins. Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge. Here, to elevate unrestricted learning from spectra, we introduce ‘ad hoc learning of fragmentation’ (AHLF), a deep learning model that is end-to-end trained on 19.2 million spectra from several phosphoproteomic datasets. AHLF is interpretable, and we show that peak-level feature importance values and pairwise interactions between peaks are in line with corresponding peptide fragments. We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared with the current state of the art on this task. Furthermore, use of AHLF in rescoring search results increases the number of phosphopeptide identifications by a margin of up to 15.1% at a constant false discovery rate. To show the broad applicability of AHLF, we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%.
In this study, 19 experiments were conducted with 25 pouch cells of NMC cathode to investigate thermal runaway and the release of gases from lithium-ion batteries (LIBs). Single cells, double cells, and a four-cell battery stack were forced to undergo thermal runaway inside an air-tight reactor vessel with a volume of 100 dm3 . The study involved two series of tests with two types of ignition sources. In the Series 1 tests, a heating plug was used to initiate thermal runaway in LIBs in the ranges of 80–89% and 90–100% SOC. In the Series 2 tests, a heating plate was used to trigger thermal runaway in LIBs in the ranges of 30–50%, 80–89%, and 90–100% SOC. Thermal runaway started at an onset temperature of 344 ± 5 K and 345 K for the Series 1 tests and from 393 ± 36 K to 487 ± 10 K for the Series 2 tests. Peak reaction temperatures ranged between 642 K and 1184 K, while the maximum pressures observed were between 1.2 bar and 7.28 bar. Thermal runaway induced explosion of the cells and lead to a rate of temperature increase greater than 10 K/s. The amounts of gases released from the LIBs were calculated from pressures and temperatures measured in the reactor.
Then, the gas composition was analyzed using a Fourier transform infrared (FTIR) spectrometer. The highest gaseous production was achieved at a range of 90–100% SOC and higher battery capacities 72 L, 1.8 L/Ah (Series 1, battery stack) and 103 L, 3.2 L/Ah (Series 2, 32 Ah cell)). Among the gases analyzed, the concentration of gaseous emissions such as C2H4 , CH4 , and C2H6 increased at a higher cell capacity in both series of tests. The study results revealed characteristic variations of thermal behavior with respect to the type of ignition source used.
Objectives: Using a murine model of multiple sclerosis, we previously showed that repeated administration of gadopentetate dimeglumine led to retention of gadolinium (Gd) within cerebellar structures and that this process was enhanced with inflammation. This study aimed to compare the kinetics and retention profiles of Gd in inflamed and healthy brains after application of the macrocyclic Gd-based contrast agent (GBCA) gadobutrol or the linear GBCA gadopentetate. Moreover, potential Gd-induced neurotoxicity was investigated in living hippocampal slices ex vivo.
Materials and Methods: Mice at peak of experimental autoimmune encephalomyelitis (EAE; n = 29) and healthy control mice (HC; n = 24) were exposed to a cumulative dose of 20 mmol/kg bodyweight of either gadopentetate dimeglumine or gadobutrol (8 injections of 2.5 mmol/kg over 10 days). Magnetic resonance imaging (7 T) was performed at baseline as well as at day 1, 10, and 40 post final injection (pfi) of GBCAs. Mice were sacrificed after magnetic resonance imaging and brain and blood Gd content was assessed by laser ablation-inductively coupled plasma (ICP)-mass spectrometry (MS) and ICP-MS, respectively. In addition, using chronic organotypic hippocampal slice cultures, Gd-induced neurotoxicity was addressed in living brain tissue ex vivo, both under control or inflammatory (tumor necrosis factor α [TNF-α] at 50 ng/μL) conditions.
Results: Neuroinflammation promoted a significant decrease in T1 relaxation times after multiple injections of both GBCAs as shown by quantitative T1 mapping of EAE brains compared with HC. This corresponded to higher Gd retention within the EAE brains at 1, 10, and 40 days pfi as determined by laser ablation-ICP-MS. In inflamed cerebellum, in particular in the deep cerebellar nuclei (CN), elevated Gd retention was observed until day 40 after last gadopentetate application (CN: EAE vs HC, 55.06 ± 0.16 μM vs 30.44 ± 4.43 μM). In contrast, gadobutrol application led to a rather diffuse Gd content in the inflamed brains, which strongly diminished until day 40 (CN: EAE vs HC, 0.38 ± 0.08 μM vs 0.17 ± 0.03 μM). The analysis of cytotoxic effects of both GBCAs using living brain tissue revealed an elevated cell death rate after incubation with gadopentetate but not gadobutrol at 50 mM. The cytotoxic effect due to gadopentetate increased in the presence of the inflammatory mediator TNF-α (with vs without TNF-α, 3.15% ± 1.18% vs 2.17% ± 1.14%; P = 0.0345).
Conclusions: In the EAE model, neuroinflammation promoted increased Gd retention in the brain for both GBCAs. Whereas in the inflamed brains, efficient clearance of macrocyclic gadobutrol during the investigated time period was observed, the Gd retention after application of linear gadopentetate persisted over the entire observational period. Gadopentetate but not gadubutrol appeared to be neurotoxic in an ex vivo paradigm of neuronal inflammation.
Iron-based catalysts are employed in CO2-FTS due to their ability to convert CO2 into CO in a first step and their selectivity towards higher hydrocarbons in a second CO hydrogenation step. According to the literature, iron carbides represent the active phase for hydrocarbon formation and are claimed to emerge in the presence of CO. We propose nanostructured FeOx films as model systems to assess information about the complex phase transformations during CO2-FTS. Mesoporous hematite, ferrihydrite, maghemite, maghemite/magnetite films were exposed to CO2-FTS atmospheres at 20 bar and 300°C. Up to three distinct phases were observed depending on the timeon-stream (TOS): a sintered maghemite/magnetite phase, a carbidic core-shell structure, and a low-crystalline, needle-type oxide phase. Our findings indicate that the formation of an intermediary maghemite/magnetite phase, predominant after short TOS (30 h), precedes the evolution of the carbide phase.
Yet, even after prolonged TOS (185 h), no full conversion into a bulk carbide is observed.