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  1. Hybrid materials that combine organic polymers and biomacromolecules offer unique opportunities for precisely controlling 3D chemical environments. Although biological or organic templates have been separately used to control the growth of inorganic nanoclusters, hybrid structures represent a relatively unexplored approach to tailoring nanocluster properties. Here, we demonstrate that a molecularly defined lysozyme–polymer resin material acts as a structural scaffold for the synthesis of copper nanoclusters (CuNCs) with well controlled size distributions. The resulting CuNCs have significantly enhanced fluorescence compared with syntheses based on polymeric or biological templates alone. The synergistic approach described here is appealing for the synthesis of biocompatible fluorescent labels with improved photostability. 
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    Free, publicly-accessible full text available May 13, 2025
  2. Abstract

    Peptide cyclization has dramatic effects on a variety of important properties, enhancing metabolic stability, limiting conformational flexibility, and altering cellular entry and intracellular localization. The hydrophilic, polyfunctional nature of peptides creates chemoselectivity challenges in macrocyclization, especially for natural sequences without biorthogonal handles. Herein, we describe a gaseous sulfonyl chloride derived reagent that achieves amine–amine, amine–phenol, and amine–aniline crosslinking through a minimalist linchpin strategy that affords macrocyclic urea or carbamate products. The cyclization reaction is metal‐mediated and involves a novel application of sulfine species that remains unexplored in aqueous or biological contexts. The aqueous method delivers unique cyclic or bicyclic topologies directly from a variety of natural bioactive peptides without the need for protecting‐group strategies.

     
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    Free, publicly-accessible full text available July 14, 2025
  3. Future adaptation to snow cover depends on standing genetic variation for winter camouflage in white-tailed jackrabbits. 
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  4. Abstract

    Seed-mediated synthesis strategies, in which small gold nanoparticle precursors are added to a growth solution to initiate heterogeneous nucleation, are among the most prevalent, simple, and productive methodologies for generating well-defined colloidal anisotropic nanostructures. However, the size, structure, and chemical properties of the seeds remain poorly understood, which partially explains the lack of mechanistic understanding of many particle growth reactions. Here, we identify the majority component in the seed solution as an atomically precise gold nanocluster, consisting of a 32-atom Au core with 8 halide ligands and 12 neutral ligands constituting a bound ion pair between a halide and the cationic surfactant: Au32X8[AQA+•X-]12(X = Cl, Br; AQA = alkyl quaternary ammonium). Ligand exchange is dynamic and versatile, occurring on the order of minutes and allowing for the formation of 48 distinct Au32clusters with AQAX (alkyl quaternary ammonium halide) ligands. Anisotropic nanoparticle syntheses seeded with solutions enriched in Au32X8[AQA+•X-]12show narrower size distributions and fewer impurity particle shapes, indicating the importance of this cluster as a precursor to the growth of well-defined nanostructures.

     
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  5. Abstract

    Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

     
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  6. Sork, Victoria (Ed.)
    Abstract When species are continuously distributed across environmental gradients, the relative strength of selection and gene flow shape spatial patterns of genetic variation, potentially leading to variable levels of differentiation across loci. Determining whether adaptive genetic variation tends to be structured differently than neutral variation along environmental gradients is an open and important question in evolutionary genetics. We performed exome-wide population genomic analysis on deer mice sampled along an elevational gradient of nearly 4000 m of vertical relief. Using a combination of selection scans, genotype-environment associations, and geographic cline analyses, we found that a large proportion of the exome has experienced a history of altitude-related selection. Elevational clines for nearly 30% of these putatively adaptive loci were shifted significantly up- or down-slope of clines for loci that did not bear similar signatures of selection. Many of these selection targets can be plausibly linked to known phenotypic differences between highland and lowland deer mice, although the vast majority of these candidates have not been reported in other studies of highland taxa. Together, these results suggest new hypotheses about the genetic basis of physiological adaptation to high-altitude, and the spatial distribution of adaptive genetic variation along environmental gradients. 
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