RNA regulatory networks diversified through curvature of the PUF protein scaffold
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The intrinsic defects in reduced graphene oxide (rGO) formed during reduction processes can act as nanopores, making rGO a promising ultrathin-film membrane candidate for separations. To assess the potential of rGO for such applications, molecular dynamics techniques are employed to understand the defect formation in rGO and their separation performance in water desalination and natural gas purification. We establish the relationship between rGO synthesis parameters and defect sizes, resulting in a potential means to control the size of nanopores in rGO. Furthermore, our results show that rGO membranes obtained under properly chosen synthesis conditions can achieve effective separations and provide significantly higher permeate fluxes than currently available membranes.
Managing water is critical for industrial applications including CO2 capture, catalysis, bio-oil separations and energy storage. Various classes of materials have been designed for these applications, achieving specific water adsorption capacities at a given relative humidity (RH). Three water adsorption-desorption mechanisms are common to inorganic materials: (1) chemisorption, which may lead to the modification of the first coordination sphere; (2) simple adsorption, which is reversible in nature; or (3) capillary condensation, which is irreversible in nature. Regardless of sorption mechanism, all materials known today increase water adsorption capacity with increasing RH; none exhibit repeated adsorption of water at low humidity and release at high humidity. We present here a material that breaks from this convention: a new class of nitrogen containing carbon rods along with nonstoichiometric FeXSY that adsorb water at low humidity, and spontaneously expel half of the adsorbed water when the RH exceeds a 50–80% threshold. Monolayers of water form on the surfaces of the carbon rods, with the amount of water adsorbed directly linked to the aspect ratio of the rods and the available surface area. This unprecedented water expulsion is a reversible physical process. Once a complete monolayer is formed, adjacent rods in the bundles begin to adhere together via formation of a bridging monolayer, reducing the surface area available for water to adhere to. We believe the unique surface chemistry of these carbon rods can be used on other functionalized materials. Such behaviour offers a paradigm shift in water purification and separation: water could be repeatedly adsorbed from a low humidity vapour stream and then expelled into a pure water vapour stream, or humidity-responsive membranes could change their water permeance or selectivity as a function of RH.
Samarium hexaboride (SmB 6 ) is a Kondo insulator, with a narrow gap due to hybridization between localized and conduction electrons. Despite being an insulator, many samples show metal-like properties. Rare-earth purification is exceedingly difficult, and nominally pure samples may contain 2% or more of impurities. Here to determine the effects of rare-earth doping on SmB6, we synthesized and probed a series of gadolinium-doped samples. We found a relationship between specific heat and impurity moment screening which scales systematically. Consistent with this finding, our neutron scattering experiments of a high purity sample of doubly isotopic 154 Sm 11 B 6 show no intrinsic excitations below the well-established 13 meV spin-exciton. The result of introducing impurities into a Kondo insulator is incompletely understood, but it is clear from our measurements that there is a systematic relationship between rare-earth impurities and metal-like properties in SmB 6 .
Two-dimensional membranes have gained enormous interest due to their potential to deliver precision filtration of species with performance that can challenge current desalination membrane platforms. Molybdenum disulfide (MoS 2 ) laminar membranes have recently demonstrated superior stability in aqueous environment to their extensively-studied analogs graphene-based membranes; however, challenges such as low ion rejection for high salinity water, low water flux, and low stability over time delay their potential adoption as a viable technology. Here, we report composite laminate multilayer MoS 2 membranes with stacked heterodimensional one- to two-layer-thick porous nanosheets and nanodisks. These membranes have a multimodal porous network structure with tunable surface charge, pore size, and interlayer spacing. In forward osmosis, our membranes reject more than 99% of salts at high salinities and, in reverse osmosis, small-molecule organic dyes and salts are efficiently filtered. Finally, our membranes stably operate for over a month, implying their potential for use in commercial water purification applications.
A growing number of optogenetic tools have been developed to reversibly control binding between two engineered protein domains. In contrast, relatively few tools confer lightswitchable binding to a generic target protein of interest. Such a capability would offer substantial advantages, enabling photoswitchable binding to endogenous target proteins in cells or light-based protein purification in vitro. Here, we report the development of optonanobodies (OptoNBs), a versatile class of chimeric photoswitchable proteins whose binding to proteins of interest can be enhanced or inhibited upon blue light illumination. We find that OptoNBs are suitable for a range of applications including reversibly binding to endogenous intracellular targets, modulating signaling pathway activity, and controlling binding to purified protein targets in vitro. This work represents a step towards programmable photoswitchable regulation of a wide variety of target proteins.
Abstract Monobodies are synthetic non-immunoglobulin customizable protein binders invaluable to basic and applied research, and of considerable potential as future therapeutics and diagnostic tools. The ability to reversibly control their binding activity to their targets on demand would significantly expand their applications in biotechnology, medicine, and research. Here we present, as proof-of-principle, the development of a light-controlled monobody (OptoMB) that works in vitro and in cells and whose affinity for its SH2-domain target exhibits a 330-fold shift in binding affinity upon illumination. We demonstrate that our αSH2-OptoMB can be used to purify SH2-tagged proteins directly from crude E. coli extract, achieving 99.8% purity and over 40% yield in a single purification step. By virtue of their ability to be designed to bind any protein of interest, OptoMBs have the potential to find new powerful applications as light-switchable binders of untagged proteins with the temporal and spatial precision afforded by light.
The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability.
Abstract Solar steam water purification and fog collection are two independent processes that could enable abundant fresh water generation. We developed a hydrogel membrane that contains hierarchical three-dimensional microstructures with high surface area that combines both functions and serves as an all-day fresh water harvester. At night, the hydrogel membrane efficiently captures fog droplets and directionally transports them to a storage vessel. During the daytime, it acts as an interfacial solar steam generator and achieves a high evaporation rate of 3.64 kg m −2 h −1 under 1 sun enabled by improved thermal/vapor flow management. With a homemade rooftop water harvesting system, this hydrogel membrane can produce fresh water with a daily yield of ~34 L m −2 in an outdoor test, which demonstrates its potential for global water scarcity relief.
Abstract Precious metal recovery from electronic waste, termed urban mining, is important for a circular economy. Present methods for urban mining, mainly smelting and leaching, suffer from lengthy purification processes and negative environmental impacts. Here, a solvent-free and sustainable process by flash Joule heating is disclosed to recover precious metals and remove hazardous heavy metals in electronic waste within one second. The sample temperature ramps to ~3400 K in milliseconds by the ultrafast electrical thermal process. Such a high temperature enables the evaporative separation of precious metals from the supporting matrices, with the recovery yields >80% for Rh, Pd, Ag, and >60% for Au. The heavy metals in electronic waste, some of which are highly toxic including Cr, As, Cd, Hg, and Pb, are also removed, leaving a final waste with minimal metal content, acceptable even for agriculture soil levels. Urban mining by flash Joule heating would be 80× to 500× less energy consumptive than using traditional smelting furnaces for metal-component recovery and more environmentally friendly.
Organic electrochemical transistors are a promising technology for bioelectronic devices, with applications in neuromorphic computing and healthcare. The active component enabling an organic electrochemical transistor is the organic mixed ionic-electronic conductor whose optimization is critical for realizing high-performing devices. In this study, the influence of purity and molecular weight is examined for a p-type polythiophene and an n-type naphthalene diimide-based polymer in improving the performance and safety of organic electrochemical transistors. Our preparative GPC purification reduced the Pd content in the polymers and improved their organic electrochemical transistor mobility by ~60% and 80% for the p- and n-type materials, respectively. These findings demonstrate the paramount importance of removing residual Pd, which was concluded to be more critical than optimization of a polymer’s molecular weight, to improve organic electrochemical transistor performance and that there is readily available improvement in performance and stability of many of the reported organic mixed ionic-electronic conductors.
Open quantum systems have been shown to host a plethora of exotic dynamical phases. Measurement-induced entanglement phase transitions in monitored quantum systems are a striking example of this phenomena. However, naive realizations of such phase transitions requires an exponential number of repetitions of the experiment which is practically unfeasible on large systems. Recently, it has been proposed that these phase transitions can be probed locally via entangling reference qubits and studying their purification dynamics. In this work, we leverage modern machine learning tools to devise a neural network decoder to determine the state of the reference qubits conditioned on the measurement outcomes. We show that the entanglement phase transition manifests itself as a stark change in the learnability of the decoder function. We study the complexity and scalability of this approach in both Clifford and Haar random circuits and discuss how it can be utilized to detect entanglement phase transitions in generic experiments.
Many eukaryotic transcription factors (TF) form homodimer or heterodimer complexes to regulate gene expression. Dimerization of BASIC LEUCINE ZIPPER (bZIP) TFs are critical for their functions, but the molecular mechanism underlying the DNA binding and functional specificity of homo- versus heterodimers remains elusive. To address this gap, we present the double DNA Affinity Purification-sequencing (dDAP-seq) technique that maps heterodimer binding sites on endogenous genomic DNA. Using dDAP-seq we profile twenty pairs of C/S1 bZIP heterodimers and S1 homodimers in Arabidopsis and show that heterodimerization significantly expands the DNA binding preferences of these TFs. Analysis of dDAP-seq binding sites reveals the function of bZIP9 in abscisic acid response and the role of bZIP53 heterodimer-specific binding in seed maturation. The C/S1 heterodimers show distinct preferences for the ACGT elements recognized by plant bZIPs and motifs resembling the yeast GCN4 cis -elements. This study demonstrates the potential of dDAP-seq in deciphering the DNA binding specificities of interacting TFs that are key for combinatorial gene regulation.
Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.
Vertically-aligned carbon nanotube (VaCNT) membranes allow water to conduct rapidly at low pressures and open up the possibility for water purification and desalination, although the ultralow viscous stress in hydrophobic and low-tortuosity nanopores prevents surface interactions with contaminants. In this experimental investigation, steroid hormone micropollutant adsorption by VaCNT membranes is quantified and explained via the interplay of the hydrodynamic drag and friction forces acting on the hormone, and the adhesive and repulsive forces between the hormone and the inner carbon nanotube wall. It is concluded that a drag force above 2.2 × 10 —3 pN overcomes the friction force resulting in insignificant adsorption, whereas lowering the drag force from 2.2 × 10 —3 to 4.3 × 10 —4 pN increases the adsorbed mass of hormones from zero to 0.4 ng cm —2 . At a low drag force of 1.6 × 10 —3 pN, the adsorbed mass of four hormones is correlated with the hormone–wall adhesive (van der Waals) force. These findings explain micropollutant adsorption in nanopores via the forces acting on the micropollutant along and perpendicular to the flow, which can be exploited for selectivity.
Abstract Despite their highly anisotropic complex-oxidic nature, certain delafossite compounds ( e.g ., PdCoO 2 , PtCoO 2 ) are the most conductive oxides known, for reasons that remain poorly understood. Their room-temperature conductivity can exceed that of Au, while their low-temperature electronic mean-free-paths reach an astonishing 20 μm. It is widely accepted that these materials must be ultrapure to achieve this, although the methods for their growth (which produce only small crystals) are not typically capable of such. Here, we report a different approach to PdCoO 2 crystal growth, using chemical vapor transport methods to achieve order-of-magnitude gains in size, the highest structural qualities yet reported, and record residual resistivity ratios ( > 440). Nevertheless, detailed mass spectrometry measurements on these materials reveal that they are not ultrapure in a general sense, typically harboring 100s-of-parts-per-million impurity levels. Through quantitative crystal-chemical analyses, we resolve this apparent dichotomy, showing that the vast majority of impurities are forced to reside in the Co-O octahedral layers, leaving the conductive Pd sheets highly pure (∼1 ppm impurity concentrations). These purities are shown to be in quantitative agreement with measured residual resistivities. We thus conclude that a sublattice purification mechanism is essential to the ultrahigh low-temperature conductivity and mean-free-path of metallic delafossites.
A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimer’s medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from the low-yielding daffodil Narcissus pseudonarcissus. Here, we propose an efficient biosensor-machine learning technology stack for biocatalyst development, which we apply to engineer an Amaryllidaceae enzyme in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC 50 = 20 μM) and specific biosensor for the key Amaryllidaceae alkaloid branchpoint 4’-O-methylnorbelladine. A structure-based residual neural network (MutComputeX) is subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which are rapidly screened with the biosensor. Functional enzyme variants are identified that yield a 60% improvement in product titer, 2-fold higher catalytic activity, and 3-fold lower off-product regioisomer formation. A solved crystal structure elucidates the mechanism behind key beneficial mutations.
Abstract The separation and purification of C6 cyclic hydrocarbons (benzene, cyclohexene, cyclohexane) represent a critically important but energy intensive process. Developing adsorptive separation technique to replace thermally driven distillation processes holds great promise to significantly reduce energy consumption. Here we report a flexible one-dimensional coordination polymer as an efficient adsorbent to discriminate ternary C6 cyclic hydrocarbons via an ideal molecular sieving mechanism. The compound undergoes fully reversible structural transformation associated with removal/re-coordination of water molecules and between activated and hydrocarbon-loaded forms. It exhibits distinct temperature- and adsorbate-dependent adsorption behavior which facilitates the complete separation of benzene, cyclohexene and cyclohexane from their binary and ternary mixtures, with the record-high uptake ratios for C 6 H 6 /C 6 H 12 and C 6 H 10 /C 6 H 12 in vapor phase and highest binary and ternary selectivities in liquid phase. In situ infrared spectroscopic analysis and ab initio calculations provide insight into the host-guest interactions and their effect on the preferential adsorption and structural transformation.