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Analytical Framework to Understand the Origins of Methyl Side-Chain Dynamics in Protein Assemblies
No full textSide-chain motions play an important role in understanding protein structure, dynamics, protein–protein, and protein–ligand interactions. However, our understanding of protein side-chain dynamics is currently limited by the lack of analytical tools. Here, we present a novel analytical framework employing experimental nuclear magnetic resonance (NMR) relaxation measurements at atomic resolution combined with molecular dynamics (MD) simulation to characterize with a high level of detail the methyl side-chain dynamics in insoluble protein assemblies, using amyloid fibrils formed by the prion HET-s. We use MD simulation to interpret experimental results, where rotameric hops, including methyl group rotation and χ1/χ2 rotations, cannot be completely described with a single correlation time but rather sample a broad distribution of correlation times, resulting from continuously changing local structure in the fibril. Backbone motion similarly samples a broad range of correlation times, from ∼100 ps to μs, although resulting from mostly different dynamic processes; nonetheless, we find that the backbone is not fully decoupled from the side-chain motion, where changes in side-chain dynamics influence backbone motion and vice versa. While the complexity of side-chain motion in protein assemblies makes it very challenging to obtain perfect agreement between experiment and simulation, our analytical framework improves the interpretation of experimental dynamics measurements for complex protein assemblies
Hydrate-melt electrolyte design for aqueous aluminium-bromine batteries with enhanced energy-power merits
No full textAluminium-based aqueous batteries hold promises for next-generation sustainable and large-scale energy storage due to the favorable metrics of Al and water-based electrolytes. However, the performance of current aluminium-based aqueous batteries falls significantly below theoretical expectations, with a critical bottleneck of realizing cathodes with high areal capacities. Herein, we present a hydrate-melt electrolyte design utilizing cost-effective AlCl3 and organic halide salts, which enables the demonstration of aqueous Al-Br batteries with enhanced energy-power characteristics. The optimal electrolyte features suppressed water activity and loosely bound halogen anions, attributed to its unique electrolyte structure, where the majority of water molecules engage in robust ion solvation (>98% as suggested by simulations) and halogen anions reside in the outer solvation sheath of cations. These distinctive features ensure good compatibility of the electrolyte with the reversible Br−/Br0/Br+ conversion, enabling cathodes with a high areal capacity of 5 mAh cm−2. Besides, the electrolyte allows for Zn-Al alloying/de-alloying with minimal polarization (around 100 mV at 5 mA cm−2) and a smooth alloy surface. The assembled Al-Br cell delivers an energy density (267 Wh L−1, based on the volume of anode, cathode and separator) comparable to commercial Li-ion batteries and a substantial power density (1069 W L−1) approaching electrochemical capacitors
Changes in the Red Sea overturning circulation during Marine Isotope Stage 3
No full textThe oceanography of the Red Sea is controlled by the restricted exchange of water masses with the Indian Ocean and by high evaporation rates due to the arid climate of the surrounding land areas. In the northern Red Sea, the formation of oxygen-rich subsurface water ventilates the deeper parts of the basin, but little is known about the variability in this process in the past. The stable oxygen and carbon isotope records of epibenthic foraminifera from a sediment core of the central Red Sea and comparison with existing isotope records allow for the reconstruction of changes in the Red Sea overturning circulation (ROC) during Marine Isotope Stage 3. The isotope records imply millennial-scale variations in the ROC, in phase with the climate variability in the high northern latitudes. This suggests an immediate response of dense-water formation to the regional climate and hydrology of the northern Red Sea. Deep-water formation was intensified under the influence of cold and hyper-arid conditions during Heinrich stadials and was diminished during Dansgaard–Oeschger interstadials. While these changes are reflected in both stable oxygen and carbon isotope records, the latter data also exhibit changes in phase with the African–Indian monsoon system. The decoupling of the stable carbon and oxygen isotope records at the summer monsoon maximum centered around 55–60 ka may be associated with an increased inflow of nutrient-rich intermediate waters from the Arabian Sea to the central Red Sea. This process fueled local surface water productivity, resulting in enhanced remineralization of sinking organic matter and release of 12C at intermediate water depths
Decoding energy decomposition analysis: Machine-learned Insights on the impact of the density functional on the bonding analysis
No full textThe concept of chemical bonding is a crucial aspect of chemistry that aids in under-
standing the complexity and reactivity of molecules and materials. However, the
interpretation of chemical bonds can be hindered by the choice of the theoretical
approach and the specific method utilized. This study aims to investigate the effect
of choosing different density functionals on the interpretation of bonding achieved
through energy decomposition analysis (EDA). To achieve this goal, a data set was
created, representing four bonding groups and various combinations of functionals
and dispersion correction schemes. The calculations showed significant variation
among the different functionals for the EDA terms, with the dispersion correction
terms exhibiting the highest variability. More information was extracted by using
machine learning in combination with dimensionality reduction on the data set.
Results indicate that, despite the differences in the EDA terms obtained from differ-
ent functionals, the functional has the least significant impact, suggesting minimal
influence on the bonding interpretation
Decreased long-range temporal correlations in the resting- state functional magnetic resonance imaging blood-oxygen- level-dependent signal reflect motor sequence learning up to 2 weeks following training
No full textDecreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity
Tätigkeitsbericht ... / Staatliche Betriebsgesellschaft für Umwelt und Landwirtschaft, Freistaat Sachsen
No full text„Es ist die Freiheit, an der sie wächst“. Sarah Rappeports Kibbuzroman „Die Jüdin von Cherut“
No full textDresdner Nachbarschaften: sichtbar, vernetzt, engagiert
No full textHallo zusammen, wir möchten Euch mitnehmen auf eine
kleine Reise durch unsere wunderbare Stadt. Wir haben
uns auf den Weg gemacht, um mal genauer hinzuschauen,
wie es sich so in Dresden lebt. Was so alles passiert in der
Nachbarschaft.
Zwischen Hochhäusern und Villen, zwischen Parks und Gärten,
auf dem Asphalt der Straßen und auf den Trampelfaden durch
den Kiez sind wir unterwegs gewesen und haben unglaublich
viele Menschen getroffen, die sich engagieren, um das Zusammenleben
in der Nachbarschaft zu gestalten.
Wir wollten wissen: Wer sind diese Menschen?
Es gab die Einzelkämpfer:innen, die ein Hinterhoffest organisiert
haben, große Vereine, die langfristige Projekte anstoßen
und ganze Stadtteilhäuser entstehen lassen, aber auch die
kleinen Initiativen, welche sich mehr Zulauf wünschen und
trotzdem Großes tun.
Wir haben Menschen kennengelernt, die nach vielen Jahren
des Engagements den Staffelstab an Jüngere abgeben. Und
wir haben junge Menschen getroffen, die voller Enthusiasmus Projekte starten. Und auch die, die noch nicht so lange hier leben, gestalten
fleißig mit. Vom Café Halva bis zur ukrainischen Nähcaférunde
könnt ihr links und rechts der Elbe spannende Projekte
entdecken.
All diese Gestalter:innen unserer Stadt zeigen, was lebendige
Nachbarschaft und gelebte Demokratie verbindet: Das eigene
Handeln zum Gestalten der Gesellschaft einzusetzen.
Apropos gestalten: Wir haben nachgefragt, wie die optimale
Stadt oder das Traumhaus denn aussehen würde, welche
Nachbarschaft man sich wünscht. In Workshops und bei
Straßen- und Stadtteilfesten war jeder herzlich eingeladen,
seine Vision im Kleinen umzusetzen.
Mit Schere, Leim und bunter Farbe ist so eine unglaublich
kreative Stadtansicht entstanden. Dem einen war es wichtig,
der Elbe mehr Raum zu geben, ein kleines Kopenhagen wäre
schön, dem anderen gibt es zu wenig Schwimmbäder. Ein
Mehrgenerationenhaus ist entstanden und andere wünschten
sich mehr Spielplätze. Aber seht selbst.
Es gab Orte, die wir schon im letzten Jahr besucht haben, und
die gewachsen sind. Die Stadt tut viel, um Stadtteilzentren zu
fördern, aber Geld allein reicht nicht. Jeder von uns ist gefragt,
sich einzubringen und seine Nachbarschaft zu gestalten. Es
gibt so viele Orte, die spannend sind und entdeckt werden
müssen.
Kommt mit auf einen Spaziergang durch unsere Nachbarschaften.
Laufzeit: Mai bis Dezember 202
Global high-resolution drought indices for 1981–2022
No full textDroughts are among the most complex and devastating natural hazards globally. High-resolution
datasets of drought metrics are essential for monitoring and quantifying the severity, duration, frequency, and
spatial extent of droughts at regional and particularly local scales. However, current global drought indices are
available only at a coarser spatial resolution ( > 50 km). To fill this gap, we developed four high-resolution
(5 km) gridded drought records based on the standardized precipitation evaporation index (SPEI) covering the
period 1981–2022. These multi-scale (1–48 months) SPEI indices are computed based on monthly precipita-
tion (P ) from the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS, version 2) and
Multi-Source Weighted-Ensemble Precipitation (MSWEP, version 2.8), and potential evapotranspiration (PET)
from the Global Land Evaporation Amsterdam Model (GLEAM, version 3.7a) and hourly Potential Evap-
otranspiration (hPET). We generated four SPEI records based on all possible combinations of P and PET
datasets: CHIRPS_GLEAM, CHIRPS_hPET, MSWEP_GLEAM, and MSWEP_hPET. These drought records
were evaluated globally and exhibited excellent agreement with observation-based estimates of SPEI, root zone
soil moisture, and vegetation health indices. The newly developed high-resolution datasets provide more de-
tailed local information and can be used to assess drought severity for particular periods and regions and
to determine global, regional, and local trends, thereby supporting the development of site-specific adapta-
tion measures. These datasets are publicly available at the Centre for Environmental Data Analysis (CEDA;
https://doi.org/10.5285/ac43da11867243a1bb414e1637802dec) (Gebrechorkos et al., 2023)