Structural and biochemical analyses of the nuclear IκBζ protein in complex with the NF-κB p50 homodimer.

As part of the efforts to understand nuclear IκB function in NF-κB-dependent gene expression, we report an X-ray crystal structure of the IκBζ ankyrin repeat domain in complex with the dimerization domain of the NF-κB p50 homodimer. IκBζ possesses an N-terminal α helix that conveys domain folding stability. Affinity and specificity of the complex depend on a small portion of p50 at the nuclear localization signal. The model suggests that only one p50 subunit supports binding with IκBζ, and biochemical experiments confirm that IκBζ associates with DNA-bound NF-κB p50:RelA heterodimers. Comparisons of IκBζ:p50 and p50:κB DNA complex crystallographic models indicate that structural rearrangement is necessary for ternary complex formation of IκBζ and p50 with DNA.

Symmetry-Guided Inverse Design of Self-Assembling Multiscale DNA Origami Tilings.

Recent advances enable the creation of nanoscale building blocks with complex geometries and interaction specificities for self-assembly. This nearly boundless design space necessitates design principles for defining the mutual interactions between multiple particle species to target a user-specified complex structure or pattern. In this article, we develop a symmetry-based method to generate the interaction matrices that specify the assembly of two-dimensional tilings, which we illustrate using equilateral triangles. By exploiting the allowed 2D symmetries, we develop an algorithmic approach by which any periodic 2D tiling can be generated from an arbitrarily large number of subunit species, notably addressing an unmet challenge of engineering 2D crystals with periodicities that can be arbitrarily larger than the subunit size. To demonstrate the utility of our design approach, we encode specific interactions between triangular subunits synthesized by DNA origami and show that we can guide their self-assembly into tilings with a wide variety of symmetries, using up to 12 unique species of triangles. By conjugating specific triangles with gold nanoparticles, we fabricate gold-nanoparticle supracrystals whose lattice parameter spans up to 300 nm. Finally, to generate economical design rules, we compare the design economy of various tilings. In particular, we show that (1) higher symmetries allow assembly of larger unit cells with fewer subunits and (2) linear supracrystals can be designed more economically using linear primitive unit cells. This work provides a simple algorithmic approach to designing periodic assemblies, aiding in the multiscale assembly of supracrystals of nanostructured "meta-atoms" with engineered plasmonic functions.

Economical routes to size-specific assembly of self-closing structures.

Programmable self-assembly has seen an explosion in the diversity of synthetic crystalline materials, but developing strategies that target "self-limiting" assemblies has remained a challenge. Among these, self-closing structures, in which the local curvature defines the finite global size, are prone to polymorphism due to thermal bending fluctuations, a problem that worsens with increasing target size. Here, we show that assembly complexity can be used to eliminate this source of polymorphism in the assembly of tubules. Using many distinct components, we prune the local density of off-target geometries, increasing the selectivity of the tubule width and helicity to nearly 100%. We further show that by reducing the design constraints to target either the pitch or the width alone, fewer components are needed to reach complete selectivity. Combining experiments with theory, we reveal an economical limit, which determines the minimum number of components required to create arbitrary assembly sizes with full selectivity.

Competition between Self-Assembly and Phase Separation Governs High-Temperature Condensation of a DNA Liquid.

In many biopolymer solutions, attractive interactions that stabilize finite-sized clusters at low concentrations also promote phase separation at high concentrations. Here we study a model biopolymer system that exhibits the opposite behavior, whereby self-assembly of DNA oligonucleotides into finite-sized, stoichiometric clusters tends to inhibit phase separation. We first use microfluidics-based experiments to map a novel phase transition in which the oligonucleotides condense as the temperature increases at high concentrations of divalent cations. We then show that a theoretical model of competition between self-assembly and phase separation quantitatively predicts changes in experimental phase diagrams arising from DNA sequence perturbations. Our results point to a general mechanism by which self-assembly shapes phase boundaries in complex biopolymer solutions.

A simple method to alter the binding specificity of DNA-coated colloids that crystallize.

DNA-coated colloids can crystallize into a multitude of lattices, ranging from face-centered cubic to diamond, opening avenues to producing structures with useful photonic properties. The potential design space of DNA-coated colloids is large, but its exploration is hampered by a reliance on chemically modified DNA that is slow and expensive to commercially synthesize. Here we introduce a method to controllably tailor the sequences of DNA-coated particles by covalently appending new sequence domains onto the DNA grafted to colloidal particles. The tailored particles crystallize as readily and at the same temperature as those produced via direct chemical synthesis, making them suitable for self-assembly. Moreover, we show that particles coated with a single sequence can be converted into a variety of building blocks with differing specificities by appending different DNA sequences to them. This method will make it practical to identify optimal and complex particle sequence designs and paves the way to programming the assembly kinetics of DNA-coated colloids.

Macroscopic photonic single crystals via seeded growth of DNA-coated colloids.

Photonic crystals-a class of materials whose optical properties derive from their structure in addition to their composition-can be created by self-assembling particles whose sizes are comparable to the wavelengths of visible light. Proof-of-principle studies have shown that DNA can be used to guide the self-assembly of micrometer-sized colloidal particles into fully programmable crystal structures with photonic properties in the visible spectrum. However, the extremely temperature-sensitive kinetics of micrometer-sized DNA-functionalized particles has frustrated attempts to grow large, monodisperse crystals that are required for photonic metamaterial applications. Here we describe a robust two-step protocol for self-assembling single-domain crystals that contain millions of optical-scale DNA-functionalized particles: Monodisperse crystals are initially assembled in monodisperse droplets made by microfluidics, after which they are grown to macroscopic dimensions via seeded diffusion-limited growth. We demonstrate the generality of our approach by assembling different macroscopic single-domain photonic crystals with metamaterial properties, like structural coloration, that depend on the underlying crystal structure. By circumventing the fundamental kinetic traps intrinsic to crystallization of optical-scale DNA-coated colloids, we eliminate a key barrier to engineering photonic devices from DNA-programmed materials.

Towards texture accurate slice interpolation of medical images using PixelMiner.

Quantitative image analysis models are used for medical imaging tasks such as registration, classification, object detection, and segmentation. For these models to be capable of making accurate predictions, they need valid and precise information. We propose PixelMiner, a convolution-based deep-learning model for interpolating computed tomography (CT) imaging slices. PixelMiner was designed to produce texture-accurate slice interpolations by trading off pixel accuracy for texture accuracy. PixelMiner was trained on a dataset of 7829 CT scans and validated using an external dataset. We demonstrated the model's effectiveness by using the structural similarity index (SSIM), peak signal to noise ratio (PSNR), and the root mean squared error (RMSE) of extracted texture features. Additionally, we developed and used a new metric, the mean squared mapped feature error (MSMFE). The performance of PixelMiner was compared to four other interpolation methods: (tri-)linear, (tri-)cubic, windowed sinc (WS), and nearest neighbor (NN). PixelMiner produced texture with a significantly lowest average texture error compared to all other methods with a normalized root mean squared error (NRMSE) of 0.11 (p < .01), and the significantly highest reproducibility with a concordance correlation coefficient (CCC) ≥ 0.85 (p < .01). PixelMiner was not only shown to better preserve features but was also validated using an ablation study by removing auto-regression from the model and was shown to improve segmentations on interpolated slices.

Updated guidelines for gene nomenclature in wheat.

KEY MESSAGE: Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.

Interplay between self-assembly and phase separation in a polymer-complex model.

We present a theoretical model for predicting the phase behavior of polymer solutions in which phase separation competes with oligomerization. Specifically, we consider scenarios in which the assembly of polymer chains into stoichiometric complexes prevents the chains from phase-separating via attractive polymer-polymer interactions. Combining statistical associating fluid theory with a two-state description of self-assembly, we find that this model exhibits rich phase behavior, including reentrance, and we show how system-specific phase diagrams can be derived graphically. Importantly, we discuss why these phase diagrams can resemble-and yet are qualitatively distinct from-phase diagrams of polymer solutions with lower critical solution temperatures.

Geometrically programmed self-limited assembly of tubules using DNA origami colloids.

Self-assembly is one of the most promising strategies for making functional materials at the nanoscale, yet new design principles for making self-limiting architectures, rather than spatially unlimited periodic lattice structures, are needed. To address this challenge, we explore the tradeoffs between addressable assembly and self-closing assembly of a specific class of self-limiting structures: cylindrical tubules. We make triangular subunits using DNA origami that have specific, valence-limited interactions and designed binding angles, and we study their assembly into tubules that have a self-limited width that is much larger than the size of an individual subunit. In the simplest case, the tubules are assembled from a single component by geometrically programming the dihedral angles between neighboring subunits. We show that the tubules can reach many micrometers in length and that their average width can be prescribed through the dihedral angles. We find that there is a distribution in the width and the chirality of the tubules, which we rationalize by developing a model that considers the finite bending rigidity of the assembled structure as well as the mechanism of self-closure. Finally, we demonstrate that the distributions of tubules can be further sculpted by increasing the number of subunit species, thereby increasing the assembly complexity, and demonstrate that using two subunit species successfully reduces the number of available end states by half. These results help to shed light on the roles of assembly complexity and geometry in self-limited assembly and could be extended to other self-limiting architectures, such as shells, toroids, or triply periodic frameworks.

Polymorphic self-assembly of helical tubules is kinetically controlled.

In contrast to most self-assembling synthetic materials, which undergo unbounded growth, many biological self-assembly processes are self-limited. That is, the assembled structures have one or more finite dimensions that are much larger than the size scale of the individual monomers. In many such cases, the finite dimension is selected by a preferred curvature of the monomers, which leads to self-closure of the assembly. In this article, we study an example class of self-closing assemblies: cylindrical tubules that assemble from triangular monomers. By combining kinetic Monte Carlo simulations, free energy calculations, and simple theoretical models, we show that a range of programmable size scales can be targeted by controlling the intricate balance between the preferred curvature of the monomers and their interaction strengths. However, their assembly is kinetically controlled-the tubule morphology is essentially fixed shortly after closure, resulting in a distribution of tubule widths that is significantly broader than the equilibrium distribution. We develop a simple kinetic model based on this observation and the underlying free-energy landscape of assembling tubules that quantitatively describes the distributions. Our results are consistent with recent experimental observations of tubule assembly from triangular DNA origami monomers. The modeling framework elucidates design principles for assembling self-limited structures from synthetic components, such as artificial microtubules that have a desired width and chirality.

Programming Directed Motion with DNA-Grafted Particles.

Colloidal particles can be programmed to interact in complex ways by functionalizing them with DNA oligonucleotides. Adding DNA strand-displacement reactions to the system allows these interparticle interactions to respond to specific changes in temperature. We present the requirements for thermally driven directed motion of colloidal particles, and we explore how these conditions can be realized experimentally using strand-displacement reactions. To evaluate the concept, we build and test a colloidal "dancer": a single particle that can be driven to move through a programmed sequence of steps along a one-dimensional track composed of other particles. The results of these tests reveal the capabilities and limitations of using DNA-mediated interactions for applications in dynamic systems. Specifically, we discuss how to design the substrate to limit complexity while permitting full control of the motile component, how to ratchet the interactions to move over many substrate positions with a limited regime of control parameters, and how to use technological developments to reduce the probability of detachment without sacrificing speed.

Tiling a tubule: how increasing complexity improves the yield of self-limited assembly.

The ability to design and synthesize ever more complicated colloidal particles opens the possibility of self-assembling a zoo of complex structures, including those with one or more self-limited length scales. An undesirable feature of systems with self-limited length scales is that thermal fluctuations can lead to the assembly of nearby, off-target states. We investigate strategies for limiting off-target assembly by using multiple types of subunits. Using simulations and energetics calculations, we explore this concept by considering the assembly of tubules built from triangular subunits that bind edge to edge. While in principle, a single type of triangle can assemble into tubules with a monodisperse width distribution, in practice, the finite bending rigidity of the binding sites leads to the formation of off-target structures. To increase the assembly specificity, we introduce tiling rules for assembling tubules from multiple species of triangles. We show that the selectivity of the target structure can be dramatically improved by using multiple species of subunits, and provide a prescription for choosing the minimum number of subunit species required for near-perfect yield. Our approach of increasing the system's complexity to reduce the accessibility of neighboring structures should be generalizable to other systems beyond the self-assembly of tubules.

Self-assembly of photonic crystals by controlling the nucleation and growth of DNA-coated colloids.

DNA-coated colloids can self-assemble into an incredible diversity of crystal structures, but their applications have been limited by poor understanding and control over the crystallization dynamics. To address this challenge, we use microfluidics to quantify the kinetics of DNA-programmed self-assembly along the entire crystallization pathway, from thermally activated nucleation through reaction-limited and diffusion-limited phases of crystal growth. Our detailed measurements of the temperature and concentration dependence of the kinetics at all stages of crystallization provide a stringent test of classical theories of nucleation and growth. After accounting for the finite rolling and sliding rates of micrometer-sized DNA-coated colloids, we show that modified versions of these classical theories predict the absolute nucleation and growth rates with quantitative accuracy. We conclude by applying our model to design and demonstrate protocols for assembling large single crystals with pronounced structural coloration, an essential step in creating next-generation optical metamaterials from colloids.

Evidence for Validity and Reliability, and Development of Performance Standards and Cut-Scores for Job-Related Tests of Physical Aptitude for Structural Firefighters.

OBJECTIVE: This multi-part study aimed to revise an existing battery of physical aptitude tests for firefighter applicants. Test validity and reliability were evaluated and performance thresholds were determined. METHODS: In Part I, 49 structural firefighters rated the similarity between the physical demands of the tests and corresponding work activities. In Part II, 23 participants completed the tests on 3 separate days. In Part III, cut-scores were determined using the Bookmark method by an expert panel of 25 firefighter supervisors. RESULTS: Analysis revealed high levels of validity and reliability. The expert panel provided invaluable direction through a combination of independent and group work, leading to consensus on acceptable completion times. CONCLUSION: Rigorous processes established scientific credibility for the revised battery of tests. Expert knowledge from firefighter supervisors contributed to determining cut-scores following established scientific methods.

Avidity and surface mobility in multivalent ligand-receptor binding.

Targeted drug delivery relies on two physical processes: the selective binding of a therapeutic particle to receptors on a specific cell membrane, followed by transport of the particle across the membrane. In this article, we address some of the challenges in controlling the thermodynamics and dynamics of these two processes by combining a simple experimental system with a statistical mechanical model. Specifically, we characterize and model multivalent ligand-receptor binding between colloidal particles and fluid lipid bilayers, as well as the surface mobility of membrane-bound particles. We show that the mobility of the receptors within the fluid membrane is key to both the thermodynamics and dynamics of binding. First, we find that the particle-membrane binding free energy-or avidity-is a strongly nonlinear function of the ligand-receptor affinity. We attribute the nonlinearity to a combination of multivalency and recruitment of fluid receptors to the binding site. Our results also suggest that partial wrapping of the bound particles by the membrane enhances avidity further. Second, we demonstrate that the lateral mobility of membrane-bound particles is also strongly influenced by the recruitment of receptors. Specifically, we find that the lateral diffusion coefficient of a membrane-bound particle is dominated by the hydrodynamic drag against the aggregate of receptors within the membrane. These results provide one of the first direct validations of the working theoretical framework for multivalent interactions. They also highlight that the fluidity and elasticity of the membrane are as important as the ligand-receptor affinity in determining the binding and transport of small particles attached to membranes.

Immediate preoperative hyperglycemia correlates with complications in non-cardiac surgical cases.

STUDY OBJECTIVE: Assess for a relationship between immediate preoperative glucose concentrations and postoperative complications. DESIGN: Retrospective cohort study. SETTING: Single large, tertiary care academic medical center. PATIENTS: A five-year registry of all patients at our hospital who had a glucose concentration (plasma, serum, or venous/capillary/arterial whole blood) measured up to 6 h prior to a non-emergent surgery. INTERVENTIONS: The glucose registry was cross-referenced with a database from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). We applied an outcomes review to the subset of patients for whom we had data from both registries (n = 1774). MEASUREMENTS: Preoperative glucose concentration in the full population as well as the subgroups of patients with or without diabetes were correlated with adverse postsurgical outcomes using 1) univariable analysis and 2) full multivariable analysis correcting for 27 clinical factors available from the ACS NSQIP database. Logistic regression analysis was performed using glucose level either as a continuous variable or as a categorical variable according to the following classifications: mild (≥140 mg/dL; ≥7.8 mmol/L), moderate (≥180 mg/dL; ≥10 mmol/L), or severe (≥250 mg/dL; ≥13.9 mmol/L) hyperglycemia. A third analysis was performed correcting for 7 clinically important factors (age, BMI, predicted duration of procedure, sex, CKD stage, hypoalbuminemia, and diabetic status) identified by anesthesiologists and surgeons as immediately available and important for decision making. MAIN RESULTS: Univariable analysis of all patients and the subgroups of patients without diabetes or with diabetes showed that immediate preoperative mild or moderate hyperglycemia correlates with postoperative complications. Statistical significance was lost in most groups using full multivariable analysis, but not when correcting for the 7 factors available immediately preoperatively. However, for all patients with diabetes, moderate hyperglycemia (≥180 mg/dL; ≥10 mmol/L) continued to significantly correlate with complications even in the full multivariable analysis [odds ratio (OR) 1.79; 95% Confidence Intervals (CI) 1.10, 2.92], and with readmission/reoperation within 30 days [OR 1.93; 95% CI 1.18, 3.13]. CONCLUSIONS: Preoperative hyperglycemia within 6 h of surgery is a marker of adverse postoperative outcomes. Among patients with diabetes in our study, a preoperative glucose level ≥ 180 mg/dL (≥10 mmol/L) independently correlates with risk of postoperative complications and readmission/reoperation. These results should encourage future work to determine whether addressing immediate preoperative hyperglycemia can improve complication rates, or simply serves as a marker of higher risk.

A mean-field model of linker-mediated colloidal interactions.

Programmable self-assembly is one of the most promising strategies for making ensembles of nanostructures from synthetic components. Yet, predicting the phase behavior that emerges from a complex mixture of many interacting species is difficult, and designing such a system to exhibit a prescribed behavior is even more challenging. In this article, I develop a mean-field model for predicting linker-mediated interactions between DNA-coated colloids, in which the interactions are encoded in DNA molecules dispersed in solution instead of in molecules grafted to particles' surfaces. As I show, encoding interactions in the sequences of free DNA oligomers leads to new behavior, such as a re-entrant melting transition and a temperature-independent binding free energy per kBT. This unique phase behavior results from a per-bridge binding free energy that is a nonlinear function of the temperature and a nonmonotonic function of the linker concentration, owing to subtle entropic contributions. To facilitate the design of experiments, I also develop two scaling limits of the full model that can be used to select the DNA sequences and linker concentrations needed to program a specific behavior or favor the formation of a prescribed target structure. These results could ultimately enable the programming and tuning of hundreds of mutual interactions by designing cocktails of linker sequences, thus pushing the field toward the original goal of programmable self-assembly: these user-prescribed structures can be assembled from complex mixtures of building blocks through the rational design of their interactions.

Two-step crystallization and solid-solid transitions in binary colloidal mixtures.

Crystallization is fundamental to materials science and is central to a variety of applications, ranging from the fabrication of silicon wafers for microelectronics to the determination of protein structures. The basic picture is that a crystal nucleates from a homogeneous fluid by a spontaneous fluctuation that kicks the system over a single free-energy barrier. However, it is becoming apparent that nucleation is often more complicated than this simple picture and, instead, can proceed via multiple transformations of metastable structures along the pathway to the thermodynamic minimum. In this article, we observe, characterize, and model crystallization pathways using DNA-coated colloids. We use optical microscopy to investigate the crystallization of a binary colloidal mixture with single-particle resolution. We observe classical one-step pathways and nonclassical two-step pathways that proceed via a solid-solid transformation of a crystal intermediate. We also use enhanced sampling to compute the free-energy landscapes corresponding to our experiments and show that both one- and two-step pathways are driven by thermodynamics alone. Specifically, the two-step solid-solid transition is governed by a competition between two different crystal phases with free energies that depend on the crystal size. These results extend our understanding of available pathways to crystallization, by showing that size-dependent thermodynamic forces can produce pathways with multiple crystal phases that interconvert without free-energy barriers and could provide approaches to controlling the self-assembly of materials made from colloids.

Effects of patient-level noise abatement orders on sound levels experienced by critically ill subarachnoid hemorrhage patients: an observational study.

BACKGROUND/OBJECTIVE: Patients with aneurysmal subarachnoid hemorrhage (aSAH) may be at risk for complications related to excessive environmental noise. Our ICU utilizes a variety of universal interventions to minimize ambient noise levels, but patients with aSAH additionally have specific orders intended to further minimize physiologic stress and noise exposure. It is unknown whether such orders can have a supplementary reductive effect on noise exposure. METHODS: Sound levels were measured for at least three consecutive days in the rooms of 17 patients with aSAH and implemented 'subarachnoid precautions' orders. Sound levels were similarly recorded in the rooms of 11 geographically-proximate, critically-ill control patients without aSAH. RESULTS: Linear mixed models were used to assess the difference in measurements between groups. Observations were combined into fifteen-minute windows, then group means and their differences were calculated and plotted to help identify what times of the day had significant differences. aSAH patients consistently experienced lower sound levels than control patients, with a statistically significant difference (p < 0.05) in mean sound levels at 62 of 96 intervals throughout the day. Overall, the mean sound level for aSAH patients was always between 62-63dBA, while the mean sound level experienced by control patients ranged between 64-66dBA. CONCLUSIONS: Implementation of patient-specific orders can have a supplementary reductive effect on noise exposure for aSAH patients in an intensive care unit that already utilizes universal noise abatement interventions.