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Protein C-terminal variations impact proteostasis
A vascularized liver microphysiological system captures key features of hepatic insulin resistance and monocyte infiltration
Stress-homogenized spatial architectures via entropy-driven self-assembly enabling high-performance and durable lithium extraction
The global transition to sustainable energy demands efficient lithium extraction from brines. While electrochemical lithium extraction using LiMn 2 O 4 (LMO) holds great promise, its practical application is hindered by mechanical degradation caused by anisotropic volume changes and stress accumulation during cycling. Herein, we present an entropy-driven amphiphilic self-assembly strategy that engineers stress-homogenized multilayer core–shell architectures, which innovatively mitigates stress accumulation by tuning the internal geometric structure to optimize stress–strain behavior, thereby synergistically enhancing ion distribution, transport kinetics, and electrochemical stability. This hierarchical interlayer architecture ensures uniform Li + distribution and redistributes internal stresses, mitigating localized stress concentrations and lattice expansion to preserve structural integrity throughout cycling. The optimized LMO establishes a dual benchmark for both capacity and cycling stability in hybrid capacitive deionization, achieving a remarkable lithium extraction capacity of 4.78 mmol g −1 with 96% retention over 100 cycles, outperforming both its unoptimized counterpart and other reported materials of the same type. Finite element simulations further elucidate a 48% reduction in maximum stress compared to disordered counterparts, underscoring the critical coupling between ion diffusion and stress evolution. This paradigm provides a pathway for developing advanced materials with intrinsically stable architectures for sustainable lithium extraction.
Bio-orthogonal functionalization of bacterial cellulose combining metabolic glycoengineering and click chemistry
Reply to: Comment on Room-temperature spontaneous superradiance from single diamond nanocrystals
Coordination of cell organelles to promote metabolon formation
The spatial coordination between cellular organelles and metabolic enzyme assemblies represents a fundamental mechanism for maintaining metabolic efficiency under stress. While previous work has shown that membrane-bound organelles regulate metabolic activities and that membrane-less condensates conduct metabolic reactions, the coordination between these two organizations remains unaddressed. By using a combination of proximity labeling, superresolution fluorescence microscopy, and metabolite analyses using isotopic tracing, we investigated the relationships between these metabolic hotspots. Here, we show that nutrient deficiency elongates mitochondria and transforms the ER from a tubular to sheet-like morphology, coinciding with increased mitochondrial respiration and inosine 5′-monophosphate levels. These structural changes promote the colocalization of purinosomes with these organelles, enhancing metabolic channeling. Disruption of ER sheet formation via MTM1 knockout destabilizes purinosomes, impairs substrate channeling, and reduces intracellular purine nucleotide pools without altering enzyme expression. Our findings reveal that organelle morphology and interorganelle contacts dynamically regulate the assembly and function of metabolic condensates, providing a structural basis for coordinated metabolic control in response to nutrient availability.
Prefrontal chandelier cells encode stimulus salience to influence learning in male mice
A structural model of toxic amyloid oligomers involved in type 2 diabetes
Amyloid oligomers of the human islet amyloid polypeptide (hIAPP) are a likely cytotoxic species driving β-cell death in type 2 diabetes, but their transient nature has precluded atomic-level structural characterization. We obtained a high-resolution structure of a physiologically relevant hIAPP oligomer. Using 2D IR spectroscopy, we identified three substitutions that slowed aggregation sufficiently for comprehensive 2D/3D NMR analysis while retaining the key wild-type structural features and cytotoxicity. The structural model reveals a dimeric assembly with N-terminal helices and a kink that facilitates an intermolecular β-sheet. The β-sheet spans the famous FGAILS portion of the sequence, helping to explain species-specific diabetes susceptibility and the origin of early-onset familial mutations. The integrated 2D IR/NMR strategy provides a unique approach to obtaining high-resolution structures of amyloid oligomers.
Author Correction: A scope of prebiotic neat reaction conditions and the mechanism of urea-assisted phosphorylations of alcohols
Subcellular mass spectrometry reveals proteome remodeling in an asymmetrically dividing (frog) embryonic stem cell
Subcellular proteomics maps protein localization within restricted domains of a cell, complementing high-resolution imaging by expanding the number of proteins that can be profiled at once. Achieving this at depth from subcellular inputs remains challenging. Here, we advance microprobe capillary electrophoresis–mass spectrometry (CE–MS) with trapped ion mobility spectrometry and data-independent acquisition (diaPASEF) to quantify more than a thousand proteins from opposite poles of an asymmetrically dividing embryonic blastomere in live Xenopus laevis embryos. From ~200 pg of HeLa digest—approximately 80% of a cell—the technology identified 1,035 proteins with high reproducibility in quantification (coefficient of variation <15% across technical triplicates). With microprobe sampling in vivo, we quantified 808–1,022 proteins from opposite poles of the dorsal–animal (D1) blastomere before division, and we traced how these spatial distributions are retained or remodeled in the descendant D1.1 (neural-fated) and D1.2 (epidermal-destined) cells. To decouple subcellular distributions from dorsal–ventral axis cues, we perturbed patterning by ultraviolet ventralization. These results establish microprobe CE–MS for deep subcellular proteomics in intact embryos and reveal spatially distinct protein distributions during early fate specification. These spatial proteome differences appear consistent with early lineage tendencies yet precede and likely bias, rather than fix, later fate decisions that depend on gastrula-stage inductive signals.
Widespread slowdown in short-term species turnover despite accelerating climate change
Abstract When the species composition of ecological communities changes over time, environmental drivers are often invoked as the most plausible explanation. Several lines of reasoning, however, suggest that such compositional change, called temporal species turnover, can similarly result from intrinsic ecosystem dynamics, even in a constant environment. The degree to which these two drivers contribute to observed turnover remains unclear. To address this conundrum, we analyse the well-established BioTIME database of surveys. We expect either an acceleration of turnover with accelerating climate change or constant turnover if intrinsic mechanisms dominate. Surprisingly we find instead that species turnover over short time intervals (1-5 years) has decelerated in significantly more communities during the last 100 years than it has accelerated, typically by one third. The observed slowing of turnover, we argue, could be understood—when intrinsic dynamics dominate—as resulting because anthropogenic environmental degradation or declines of regional species pools reduce the number of potential colonisers driving turnover. Our results suggest that observed past changes in species composition were often manifestations of natural, intrinsic ecosystem dynamics. Although one can expect environmental drivers to dominate species turnover eventually as climate change accelerates further, for now such attribution should be done with caution.
Single-cell exon deletion profiling reveals splicing events that shape gene expression and cell state dynamics
Abstract Alternative splicing is a pervasive gene regulatory mechanism critical for diversifying the human proteome. To systematically investigate its role in cell fate determination, we develop scCHyMErA-Seq, a scalable CRISPR-based exon deletion screening platform integrated with 10x Genomics single-cell transcriptomic readouts. This tool enables efficient exon deletion while simultaneously capturing Cas9/Cas12a guides and polyadenylated transcripts at single-cell resolution. Applying scCHyMErA-Seq to high-throughput profiling of alternative cassette exons, we identify numerous exons with pronounced regulatory effects on gene expression and cell cycle progression. Analysis of the alternative NRF1 exon-7 demonstrates that its inclusion modulates NRF1’s regulatory function by influencing its recruitment to the promoters of target genes. Importantly, gene expression profiles generated using scCHyMErA-Seq accurately recapitulate findings from traditional, labor-intensive orthogonal methods, while offering enhanced scalability and efficiency. Overall, scCHyMErA-Seq represents a versatile platform for systematically unraveling the functional impact of alternative splicing by directly linking specific splicing variants to transcriptional phenotypes.
Targeted digital voter suppression efforts likely decrease voter turnout
In light of continued foreign interference in the US presidential elections, where undisclosed digital voter suppression advertising has been deployed, this study addresses the questions of who is exposed to these ads and whether and how such exposure influences voter turnout. Using a sample that resembles the US voting-age population, the study directly measures each individual’s ad exposure through a user-level real-time ad tracking tool, which is merged with the same individual’s survey responses to identify voter suppression content and its targeting patterns. By further matching individual-level exposure to voter suppression ads with the same individual’s verified voter turnout records, the study estimates the effects of voter suppression on actual turnout. The study findings from the 2016 US Presidential Election reveal clear geo-racial targeting patterns in voter suppression: non-Whites residing in the racial minority counties of battleground states were exposed to substantially more voter suppression ads than their counterparts. Moreover, exposure to voter suppression ads was associated with decreases in voter turnout at the population level, albeit small. The sharpest declines were observed among non-Whites residing in minority counties of battleground states, suggesting that the intensified turnout suppression among the targeted segments of the electorate may have played a role in shaping turnout.
Human-AI teaming to improve accuracy and efficiency of eligibility criteria prescreening for oncology trials: a randomized evaluation trial using retrospective electronic health records
Probing Majorana localization of a phase-controlled three-site Kitaev chain with an additional quantum dot
Abstract Few-site implementations of the Kitaev chain offer a minimal platform to study the emergence and stability of Majorana bound states. Here, we realize two- and three-site chains in semiconducting quantum dots coupled via superconductors, and tune them to the sweet spot where zero-energy Majorana modes appear at the chain ends. We demonstrate control of the superconducting phase through both magnetic field and sweet-spot selection, and fully characterize the excitation spectrum under local and global perturbations. All spectral features are identified using the ideal Kitaev chain model. To assess Majorana localization, we couple the system to an additional quantum dot. The absence of energy splitting at the sweet spot is compatible with high-quality Majorana modes, despite the modest chain size.
Intercalated bacterial biofilms are intrinsic internal components of calcium-based kidney stones
Calcium oxalate stones comprise greater than 70% of all kidney stones. In the current conceptual framework, the initial stone nidus is thought to include the aggregation of inorganic crystallites, the formation of which is favored by elevated concentrations of dissolved constituents. Here, we show that this highly prevalent stone type comprises a form of organic–inorganic polycrystalline biocomposite with integrated bacterial biofilms. Evidence from electron microscopy and fluorescence microscopy reveal the unanticipated internal structure of kidney stones from human patients, where bacterial biofilms are intercalated between polycrystalline mineral layers, even in stones identified as “noninfectious” clinically, including those in patients without underlying urinary tract infections. We observe similar bacterial biofilm architectures on the surfaces of stone fragments obtained due to lithotripsy, suggesting that bacteria are intrinsic to the process of nephrolithiasis. Crystallites proximal to biofilm layers exhibit significantly smaller grain sizes, which indicate a larger local concentration of nucleation sites. Staining reveals that biofilm areas of these stones are enriched with bacterial DNA. That bacteria are now observed so broadly in kidney stones (including even in less prevalent struvite stones) may be conceptually salient: Based on the evidence adduced here, we propose a model in which the urine-rich environment of the kidney can impinge on bacterial calcium homeostasis and amplify bacterial production of nucleation templates such as extracellular DNA. The resultant counterion condensation intrinsic to polyelectrolytes charged beyond the Manning criterion (such as DNA) drastically enhances the probability of heterogeneous nucleation, thereby amplifying calcium oxalate stone formation.
Author Correction: Analysis of the Rehmannia chingii genome identifies RcCYP72H7 as an epoxidase in iridoid glycoside biosynthesis
Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur footprints and address long-standing debates over whether some dinosaur tracks are the oldest birds or ornithopods (duck-billed herbivores and kin) in the fossil record, or alternatively were made by nonavian theropods. Existing methods in paleontology, however, require supervision and a priori labeling of training data by researchers, which can lead to bias. We employ an unsupervised machine learning technique for recognizing inherent patterns in shape data, using a disentangled variational autoencoder network, to a database of 1,974 footprints, spanning a diversity of dinosaurs across their evolutionary history, including modern birds. Our neural network identified eight features of shape variation that most differentiate these tracks: overall load and shape (amount of ground contact area), digit spread, digit attachment, heel load, digit and heel emphasis, loading position, heel position, and left–right load. With the unsupervised process finished, we a posteriori labeled each track based on published expert judgments, plotted them into morphospace, and applied distance metrics to group means and nearest neighbors, which showed 80 to 93% agreement with expert identifications. Controversial Late Triassic-Early Jurassic bird-like tracks group with fossil and modern birds and some Middle Jurassic three-toed tracks with ornithopods, supporting an older origin for these groups than recorded by body fossils. We provide an app, DinoTracker, to make this process accessible, and source code that can be adapted to other cases where paleontologists or biologists are studying patterns of shape variation.