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In an epoch dominated by escalating concerns over climate change and looming energy crises, the imperative to design highly efficient catalysts that can facilitate the sequestration and transformation of carbon dioxide (CO2) into beneficial chemicals is paramount. This research presents the successful synthesis of nanofiber catalysts, incorporating monometallic nickel (Ni) and cobalt (Co) and their bimetallic blend, NiCo, via a facile electrospinning technique, with precise control over the Ni/Co molar ratios. Application of an array of advanced analytical methods, including SEM, TGA–DSC, FTIR-ATR, XRD, Raman, XRF, and ICP-MS, validated the effective integration and homogeneous distribution of active Ni/Co catalysts within the nanofibers. The catalytic performance of these mono- and bimetallic Ni/Co nanofiber catalysts was systematically examined under ambient pressure conditions for CO2 hydrogenation reactions. The bimetallic NiCo nanofiber catalysts, specifically with a Ni/Co molar ratio of 1:2, and thermally treated at 1050 °C, demonstrated a high CO selectivity (98.5%) and a marked increase in CO2 conversion rate—up to 16.7 times that of monometallic Ni nanofiber catalyst and 10.8 times that of the monometallic Co nanofiber catalyst. This significant enhancement in catalytic performance is attributed to the improved accessibility of active sites, minimized particle size, and the strong Ni–Co–C interactions within these nanofiber structures. These nanofiber catalysts offer a unique model system that illuminates the fundamental aspects of supported catalysis and accentuates its crucial role in addressing pressing environmental challenges. 

Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15 N spin relaxation, without the need for reweighting. Further inspection revealed that 10–20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function. 

Copper is an essential trace metal serving as a cofactor in innate immunity, metabolism, and iron transport. We hypothesize that copper deficiency may influence survival in patients with cirrhosis through these pathways.

We performed a retrospective cohort study involving 183 consecutive patients with cirrhosis or portal hypertension. Copper from blood and liver tissues was measured using inductively coupled plasma mass spectrometry. Polar metabolites were measured using nuclear magnetic resonance spectroscopy. Copper deficiency was defined by serum or plasma copper below 80 µg/dL for women or 70 µg/dL for men.

The prevalence of copper deficiency was 17% (N=31). Copper deficiency was associated with younger age, race, zinc and selenium deficiency, and higher infection rates (42% vs. 20%,p=0.01). Serum copper correlated positively with albumin, ceruloplasmin, hepatic copper, and negatively with IL-1β. Levels of polar metabolites involved in amino acids catabolism, mitochondrial transport of fatty acids, and gut microbial metabolism differed significantly according to copper deficiency status. During a median follow-up of 396 days, mortality was 22.6% in patients with copper deficiency compared with 10.5% in patients without. Liver transplantation rates were similar (32% vs. 30%). Cause-specific competing risk analysis showed that copper deficiency was associated with a significantly higher risk of death before transplantation after adjusting for age, sex, MELD-Na, and Karnofsky score (HR: 3.40, 95% CI, 1.18–9.82,p=0.023).

In advanced cirrhosis, copper deficiency is relatively common and is associated with an increased infection risk, a distinctive metabolic profile, and an increased risk of death before transplantation.

 

A lithium-air battery based on lithium oxide (Li₂O) formation can theoretically deliver an energy density that is comparable to that of gasoline. Lithium oxide formation involves a four-electron reaction that is more difficult to achieve than the one- and two-electron reaction processes that result in lithium superoxide (LiO₂) and lithium peroxide (Li₂O₂), respectively. By using a composite polymer electrolyte based on Li₁₀GeP₂S₁₂nanoparticles embedded in a modified polyethylene oxide polymer matrix, we found that Li₂O is the main product in a room temperature solid-state lithium-air battery. The battery is rechargeable for 1000 cycles with a low polarization gap and can operate at high rates. The four-electron reaction is enabled by a mixed ion–electron-conducting discharge product and its interface with air.

 

Serving deep learning models from relational databases brings significant benefits. First, features extracted from databases do not need to be transferred to any decoupled deep learning systems for inferences, and thus the system management overhead can be significantly reduced. Second, in a relational database, data management along the storage hierarchy is fully integrated with query processing, and thus it can continue model serving even if the working set size exceeds the available memory. Applying model deduplication can greatly reduce the storage space, memory footprint, cache misses, and inference latency. However, existing data deduplication techniques are not applicable to the deep learning model serving applications in relational databases. They do not consider the impacts on model inference accuracy as well as the inconsistency between tensor blocks and database pages. This work proposed synergistic storage optimization techniques for duplication detection, page packing, and caching, to enhance database systems for model serving. Evaluation results show that our proposed techniques significantly improved the storage efficiency and the model inference latency, and outperformed existing deep learning frameworks in targeting scenarios. 

Currents are unique drivers of oceanic phylogeography and thus determine the distribution of marine coastal species, along with past glaciations and sea-level changes. Here we reconstruct the worldwide colonization history of eelgrass (Zostera marinaL.), the most widely distributed marine flowering plant or seagrass from its origin in the Northwest Pacific, based on nuclear and chloroplast genomes. We identified two divergent Pacific clades with evidence for admixture along the East Pacific coast. Two west-to-east (trans-Pacific) colonization events support the key role of the North Pacific Current. Time-calibrated nuclear and chloroplast phylogenies yielded concordant estimates of the arrival ofZ. marinain the Atlantic through the Canadian Arctic, suggesting that eelgrass-based ecosystems, hotspots of biodiversity and carbon sequestration, have only been present there for ~243 ky (thousand years). Mediterranean populations were founded ~44 kya, while extant distributions along western and eastern Atlantic shores were founded at the end of the Last Glacial Maximum (~19 kya), with at least one major refuge being the North Carolina region. The recent colonization and five- to sevenfold lower genomic diversity of the Atlantic compared to the Pacific populations raises concern and opportunity about how Atlantic eelgrass might respond to rapidly warming coastal oceans.