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High-throughput atomistic modeling of nanocrystalline structure and mechanics of calcium aluminate silicate hydrate
Abstract Although aluminum-containing cements have gained attention as environmentally friendly construction materials, the nanocrystalline structure and mechanical behavior of their primary hydration product, calcium aluminate silicate hydrate (C-A-S-H), remain poorly understood due to its complex chemical composition and structural disorder. Here, we present a high-throughput atomistic modeling framework to systematically investigate the structural and mechanical properties of C-A-S-H across a broad range of Ca/Si (1.3–1.9) and Al/Si (0–0.15) ratios. The compositional, structural, and mechanical features of C-A-S-H are accurately captured by molecular dynamics simulations of 1600 distinct C-A-S-H structures constructed using our in-house automatic structure generation program, CASHgen. Our findings highlight the influence of Ca/Si and Al/Si ratios on key C-A-S-H characteristics, including the mean chain length (MCL), interlayer spacing, coordination number and elastic moduli. Specifically, C-A-S-H exhibits optimal mechanical performance at a Ca/Si ratio of approximately 1.5, while further increases in Ca/Si introduce disorder and reduce stiffness. In contrast, increasing the Al/Si ratio promotes chain polymerization, leading to longer MCLs and improved mechanical performance. These results provide atomic-scale insights into the structure-property relationships in C-A-S-H and offer design guidelines for high-performance, low-carbon cementitious materials.
Author Correction: Hexafluorophosphate additive enables durable seawater oxidation at ampere-level current density
TGFα controls checkpoints in CNS resident and infiltrating immune cells to promote resolution of inflammation
Abstract After acute lesions in the central nervous system (CNS), the interaction of microglia, astrocytes, and infiltrating immune cells decides over their resolution or chronification. However, this CNS-intrinsic cross-talk is poorly characterized. Analyzing cerebrospinal fluid (CSF) samples of Multiple Sclerosis (MS) patients as well as CNS samples of female mice with experimental autoimmune encephalomyelitis (EAE), the animal model of MS, we identify microglia-derived TGFα as key factor driving recovery. Through mechanistic in vitro studies, in vivo treatment paradigms, scRNA sequencing, CRISPR-Cas9 genetic perturbation models and MRI in the EAE model, we show that together with other glial and non-glial cells, microglia secrete TGFα in a highly regulated temporospatial manner in EAE. Here, TGFα contributes to recovery by decreasing infiltrating T cells, pro-inflammatory myeloid cells, oligodendrocyte loss, demyelination, axonal damage and neuron loss even at late disease stages. In a therapeutic approach in EAE, blood-brain barrier penetrating intranasal application of TGFα attenuates pro-inflammatory signaling in astrocytes and CNS infiltrating immune cells while promoting neuronal survival and lesion resolution. Together, microglia-derived TGFα is an important mediator of glial-immune crosstalk, highlighting its therapeutic potential in resolving acute CNS inflammation.
Why air-traffic controller shortages are not to blame for US airport chaos
Author Correction: No evidence of immune exhaustion after repeated SARS-CoV-2 vaccination in vulnerable and healthy populations
Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent
Abstract Over the past 50 years, Arctic sea ice has declined in all seasons, with particularly pronounced winter reductions in the Barents Sea. While temperature changes in the Atlantic Water inflow and atmospheric-driven melt have been identified as key drivers of this decline, the role of the return-flow of Atlantic Water in the northern Barents Sea Opening, linked to its recirculation back into the Nordic Seas, has remained largely unrecognized. Using a global ocean and sea ice model, we find that the volume transport of the Atlantic Water return-flow is strongly correlated with the sea ice area in the Barents Sea. In addition, we find that, over the past 40 years, the return-flow has steadily weakened without a corresponding change in inflow. Here, we show that reduced Atlantic Water removal by a weakened return-flow contributes to both interannual variability and the sustained loss of Barents Sea sea ice.
On the effects of fault alignment on slip stability
Combined emergent constraints on future extreme precipitation changes
A neural mechanism for learning from delayed postingestive feedback
Abstract Animals learn the value of foods on the basis of their postingestive effects and thereby develop aversions to foods that are toxic 1–10 and preferences to those that are nutritious 11–13 . However, it remains unclear how the brain is able to assign credit to flavours experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here we reveal an unexpected role for the postingestive reactivation of neural flavour representations in this temporal credit-assignment process. To begin, we leverage the fact that mice learn to associate novel 14,15 , but not familiar, flavours with delayed gastrointestinal malaise signals to investigate how the brain represents flavours that support aversive postingestive learning. Analyses of brain-wide activation patterns reveal that a network of amygdala regions is unique in being preferentially activated by novel flavours across every stage of learning (consumption, delayed malaise and memory retrieval). By combining high-density recordings in the amygdala with optogenetic stimulation of malaise-coding hindbrain neurons, we show that delayed malaise signals selectively reactivate flavour representations in the amygdala from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts the strengthening of flavour responses upon memory retrieval, which in turn leads to stabilization of the population-level representation of the recently consumed flavour. By contrast, flavour representations in the amygdala degrade in the absence of unexpected postingestive consequences. Thus, we demonstrate that postingestive reactivation and plasticity of neural flavour representations may support learning from delayed feedback.
Is a monster web of ocean currents headed for collapse? The race is on to find out
Reply to: On the effects of fault alignment on slip stability
Low overlap of transcription factor DNA binding and regulatory targets
Structure of the ATP-driven methyl-coenzyme M reductase activation complex
Abstract Methyl-coenzyme M reductase (MCR) is the enzyme responsible for nearly all biologically generated methane1. Its active site comprises coenzyme F430, a porphyrin-based cofactor with a central nickel ion that is active exclusively in the Ni(I) state2,3. How methanogenic archaea perform the reductive activation of F430 represents a major gap in our understanding of one of the most ancient bioenergetic systems in nature. Here we purified and characterized the MCR activation complex from Methanococcus maripaludis. McrC, a small subunit encoded in the mcr operon, co-purifies with the methanogenic marker proteins Mmp7, Mmp17, Mmp3 and the A2 component. We demonstrated that this complex can activate MCR in vitro in a strictly ATP-dependent manner, enabling the formation of methane. In addition, we determined the cryo-electron microscopy structure of the MCR activation complex exhibiting different functional states with local resolutions reaching 1.8–2.1 Å. Our data revealed three complex iron–sulfur clusters that formed an electron transfer pathway towards F430. Topology and electron paramagnetic resonance spectroscopy analyses indicate that these clusters are similar to the [8Fe-9S-C] cluster, a maturation intermediate of the catalytic cofactor in nitrogenase. Altogether, our findings offer insights into the activation mechanism of MCR and prospects on the early evolution of nitrogenase.
Vertically stacked monolithic perovskite colour photodetectors
Abstract Modern colour image sensors face challenges in further improving sensitivity and image quality because of inherent limitations in light utilization efficiency 1 . A major factor contributing to these limitations is the use of passive optical filters, which absorb and dissipate a substantial amount of light, thereby reducing the efficiency of light capture 2 . On the contrary, active optical filtering in Foveon-type vertically stacked architectures still struggles to deliver optimal performance owing to their lack of colour selectivity, making them inefficient for precise colour imaging 3 . Here we introduce an innovative architecture for colour sensor arrays that uses multilayer monolithically stacked lead halide perovskite thin-film photodetectors. Perovskite bandgap tunability 4 is utilized to selectively absorb the visible light spectrum’s red, green and blue regions, eliminating the need for colour filters. External quantum efficiencies of 50%, 47% and 53% are demonstrated for the red, green and blue channels, respectively, as well as a colour accuracy of 3.8% in Δ E Lab outperforming the state-of-the-art colour-filter array and Foveon-type photosensors. The image sensor design improves light utilization in colour sensors and paves the way for the next generation of highly sensitive, artefact-free images with enhanced colour fidelity.