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Abstract Oxide heterostructures exhibit a vast variety of unique physical properties. Examples are unconventional superconductivity in layered nickelates and topological polar order in (PbTiO₃)_n/(SrTiO₃)_nsuperlattices. Although it is clear that variations in oxygen content are crucial for the electronic correlation phenomena in oxides, it remains a major challenge to quantify their impact. Here, we measure the chemical composition in multiferroic (LuFeO₃)₉/(LuFe₂O₄)₁superlattices, mapping correlations between the distribution of oxygen vacancies and the electric and magnetic properties. Using atom probe tomography, we observe oxygen vacancies arranging in a layered three-dimensional structure with a local density on the order of 10¹⁴cm⁻², congruent with the formula-unit-thick ferrimagnetic LuFe₂O₄layers. The vacancy order is promoted by the locally reduced formation energy and plays a key role in stabilizing the ferroelectric domains and ferrimagnetism in the LuFeO₃and LuFe₂O₄layers, respectively. The results demonstrate pronounced interactions between oxygen vacancies and the multiferroic order in this system and establish an approach for quantifying the oxygen defects with atomic-scale precision in 3D, giving new opportunities for deterministic defect-enabled property control in oxide heterostructures. 

Voids—the nothingness—broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials. 

Sensitive, accurate, and early detection of biomarkers is essential for prompt response to medical decisions for saving lives. Some infectious diseases are deadly even in small quantities and require early detection for patients and public health. The scarcity of these biomarkers necessitates signal amplification before diagnosis. Recently, we demonstrated single-molecule-level detection of tuberculosis biomarker, lipoarabinomannan, from patient urine using silver plasmonic gratings with thin plasma-activated alumina. While powerful, biomarker binding density was limited by the surface density of plasma-activated carbonyl groups, that degraded quickly, resulting in immediate use requirement after plasma activation. Therefore, development of stable high density binding surfaces such as high binding polystyrene is essential to improving shelf-life, reducing binding protocol complexity, and expanding to a wider range of applications. However, any layers topping the plasmonic grating must be ultra-thin (<10 nm) for the plasmonic enhancement of adjacent signals. Furthermore, fabricating thin polystyrene layers over alumina is nontrivial because of poor adhesion between polystyrene and alumina. Herein, we present the development of a stable, ultra-thin polystyrene layer on the gratings, which demonstrated 63.8 times brighter fluorescence compared to commercial polystyrene wellplates. Spike protein was examined for COVID-19 demonstrating the single-molecule counting capability of the hybrid polystyrene-plasmonic gratings. 

In the presence of polyvalent cations, long double-stranded DNA (dsDNA) in dilute solution undergoes a single- molecule, first-order, phase transition (‘‘condensation’’), a phenomenon that has been documented and analyzed by many years of experimental and theoretical studies. There has been no systematic effort, however, to determine whether long single- stranded RNA (ssRNA) shows an analogous behavior. In this study, using dynamic light scattering, analytical ultracentrifugation, and gel electrophoresis, we examine the effects of increasing polyvalent cation concentrations on the effective size of long ssRNAs ranging from 3000 to 12,000 nucleotides. Our results indicate that ssRNA does not undergo a discontinuous conden- sation as does dsDNA but rather a ‘‘continuous’’ decrease in size with increasing polyvalent cation concentration. And, instead of the 10-fold decrease in size shown by long dsDNA, we document a 50% decrease, as demonstrated for a range of lengths and sequences of ssRNA. 

Capillary suspensions are three-phase mixtures containing a solid particulate phase, a continuous liquid phase, and a second immiscible liquid forming capillary bridges between particles. Capillary suspensions are encountered in a wide array of applications including 3D printing, porous materials, and food formulations, but despite recent progress, the micromechanics of particle clusters in flow is not fully understood. In this work, we study the dynamics of meniscus-bound particle clusters in planar extensional flow using a Stokes trap, which is an automated flow control technique that allows for precise manipulation of freely suspended particles or particle clusters in flow. Focusing on the case of a two-particle doublet, we use a combination of experiments and analytical modeling to understand how particle clusters rearrange, deform, and ultimately break up in extensional flow. The time required for cluster breakup is quantified as a function of capillary number Ca and meniscus volume V. Importantly, a critical capillary number Cacrit for cluster breakup is determined using a combination of experiments and modeling. Cluster relaxation experiments are also performed by deforming particle clusters in flow, followed by flow cessation prior to breakup and observing cluster relaxation dynamics under zero-flow conditions. In all cases, experiments are complemented by an analytical model that accounts for capillary forces, lubrication forces, hydrodynamic drag forces, and hydrodynamic interactions acting on the particles. Results from the analytical models are found to be in good agreement with experiments. Overall, this work provides a new quantitative understanding of the deformation dynamics of capillary clusters in extensional flow. 

It is clear from modern analogue studies that O2-deficient conditions favor preservation of organic matter (OM) in fine-grained sedimentary rocks (black shales). It is also clear that appreciable productivity and OM flux to the sediment are required to establish and maintain these conditions. However, debates regarding redox controls on OM accumulation in black shales have mainly focused on oxic versus anoxic conditions, and the implications of different anoxic redox states remain unexplored. Here, we present detailed multi-proxy sedimentary geochemical studies of major Paleozoic and Mesozoic North American black shale units to elucidate their depositional redox conditions. This is the first broad-scale study to use a consistent geochemical methodology and to incorporate data from Fe-speciation – presently the only redox proxy able to clearly distinguish anoxic depositional conditions as ferruginous (H2S-limited) or euxinic (H2S-replete, Fe-limited). These data are coupled with total organic carbon (TOC), programmed pyrolysis, and redox-sensitive trace element proxies, with almost all measurements analyzed using the same geochemical methodology. Consistent with expectations based on previous geochemical and paleontological/ichnological studies, these analyses demonstrate that the study units were almost exclusively deposited under anoxic bottom waters. These analyses also demonstrate that there is wide variance in the prevalence of euxinic versus ferruginous conditions, with many North American black shale units deposited under predominantly ferruginous or oscillatory conditions. TOC is significantly higher under euxinic bottom waters in analyses of both preserved (present day) TOC and reconstructed initial TOC values, although sediments deposited under both redox states do have economically viable TOC content. While this correlation does not reveal the mechanism behind higher organic enrichment in euxinic environments, which may be different in different basins, it does open new research avenues regarding resource exploration and the biogeochemistry of ancient reducing environments. 

Candida albicans is a commensal fungus that can cause epithelial infections and life-threatening invasive candidiasis. The fungus secretes candidalysin (CL), a peptide that causes cell damage and immune activation by permeation of epithelial membranes. The mechanism of CL action involves strong peptide assembly into polymers in solution. The free ends of linear CL polymers can join, forming loops that become pores upon binding to membranes. CL polymers constitute a therapeutic target for candidiasis, but little is known about CL self-assembly in solution. Here, we examine the assembly mechanism of CL in the absence of membranes using complementary biophysical tools, including a new fluorescence polymerization assay, mass photometry, and atomic force microscopy. We observed that CL assembly is slow, as tracked with the fluorescent marker C-laurdan. Single-molecule methods showed that CL polymerization involves a convolution of four processes. Self-assembly begins with the formation of a basic subunit, thought to be a CL octamer that is the polymer seed. Polymerization proceeds via the addition of octamers, and as polymers grow they can curve and form loops. Alternatively, secondary polymerization can occur and cause branching. Interplay between the different rates determines the distribution of CL particle types, indicating a kinetic control mechanism. This work elucidates key physical attributes underlying CL self-assembly which may eventually evoke pharmaceutical development. 

The dramatic effectiveness of recent mRNA (mRNA)-based COVID vaccines delivered in lipid nanoparticles has highlighted the promise of mRNA therapeutics in general. In this report, we extend our earlier work on self-amplifying mRNAs delivered in spherical in vitro reconstituted virus-like particles(VLPs), and on drug delivery using cylindrical virus particles. In particular, we carry out separate in vitro assemblies of a self-amplifying mRNA gene in two different virus-like particles: one spherical, formed with the capsid protein of cowpea chloroticmottle virus (CCMV), and the other cylindrical, formed from the capsid protein of tobacco mosaic virus (TMV). The mRNA gene is rendered self-amplifying by genetically fusing it to the RNA-dependent RNA polymerase (RdRp) of Nodamura virus, and the relative efficacies of cell uptake and downstream protein expression resulting from their CCMV- and TMV-packaged forms are compared directly. This comparison is carried out by their transfections into cells in culture: expressions of two self-amplifying genes, enhanced yellow fluorescent protein (EYFP) and Renilla luciferase (Luc), packaged alternately in CCMV and TMV VLPs, are quantified by fluorescence and chemiluminescence levels, respectively, and relative numbers of the delivered mRNAs are measured by quantitative real-time PCR. The cellular uptake of both forms of these VLPs is further confirmed by confocal microscopy of transfected cells. Finally, VLP-mediated delivery of the self-amplifying- mRNA in mice following footpad injection is shown by in vivo fluorescence imaging to result in robust expression of EYFP in the draining lymph nodes, suggesting the potential of these plant virus-like particles as a promising mRNA gene and vaccine delivery modality. These results establish that both CCMV and TMV VLPs can deliver their in vitro packaged mRNA genes to immune cells and that their self-amplifying forms significantly enhance in situ expression. Choice of one VLP (CCMV or TMV) over the other will depend on which geometry of nucleocapsid is self-assembled more efficiently for a given length and sequence of RNA, and suggests that these plant VLP gene delivery systems will prove useful in a wide variety of medical applications, both preventive and therapeutic. 

High intratumoral heterogeneity is thought to be a poor prognostic indicator. However, the source of heterogeneity may also be important, as genomic heterogeneity is not always reflected in histologic or ‘visual’ heterogeneity. We aimed to develop a predictor of histologic heterogeneity and evaluate its association with outcomes and molecular heterogeneity. We used VGG16 to train an image classifier to identify unique, patient-specific visual features in 1655 breast tumors (5907 core images) from the Carolina Breast Cancer Study (CBCS). Extracted features for images, as well as the epithelial and stromal image components, were hierarchically clustered, and visual heterogeneity was defined as a greater distance between images from the same patient. We assessed the association between visual heterogeneity, clinical features, and DNA-based molecular heterogeneity using generalized linear models, and we used Cox models to estimate the association between visual heterogeneity and tumor recurrence. Basal-like and ER-negative tumors were more likely to have low visual heterogeneity, as were the tumors from younger and Black women. Less heterogeneous tumors had a higher risk of recurrence (hazard ratio = 1.62, 95% confidence interval = 1.22–2.16), and were more likely to come from patients whose tumors were comprised of only one subclone or had a TP53 mutation. Associations were similar regardless of whether the image was based on stroma, epithelium, or both. Histologic heterogeneity adds complementary information to commonly used molecular indicators, with low heterogeneity predicting worse outcomes. Future work integrating multiple sources of heterogeneity may provide a more comprehensive understanding of tumor progression.