Stereodivergent photobiocatalytic radical cyclization through the repurposing and directed evolution of fatty acid photodecarboxylases

Despite their intriguing photophysical and photochemical activities, naturally occurring photoenzymes have not yet been repurposed for new-to-nature activities. Here we engineered fatty acid photodecarboxylases to catalyse unnatural photoredox radical C-C bond formation by leveraging the strongly oxidizing excited-state flavoquinone cofactor. Through genome mining, rational engineering and directed evolution, we developed a panel of radical photocyclases to facilitate decarboxylative radical cyclization with excellent chemo-, enantio- and diastereoselectivities. Our high-throughput experimental workflow allowed for the directed evolution of fatty acid photodecarboxylases. An orthogonal set of radical photocyclases was engineered to access all four possible stereoisomers of the stereochemical dyad, affording fully diastereo- and enantiodivergent biotransformations in asymmetric radical biocatalysis. Molecular dynamics simulations show that our evolved radical photocyclases allow near-attack conformations to be easily accessed, enabling chemoselective radical cyclization. The development of stereoselective radical photocyclases provides unnatural C-C-bond-forming activities in natural photoenzyme families, which can be used to tame the stereochemistry of free-radical-mediated reactions.

Large exchange-driven intrinsic circular dichroism of a chiral 2D hybrid perovskite

In two-dimensional chiral metal-halide perovskites, chiral organic spacers endow structural and optical chirality to the metal-halide sublattice, enabling exquisite control of light, charge, and electron spin. The chiroptical properties of metal-halide perovskites have been measured by transmissive circular dichroism spectroscopy, which necessitates thin-film samples. Here, by developing a reflection-based approach, we characterize the intrinsic, circular polarization-dependent complex refractive index for a prototypical two-dimensional chiral lead-bromide perovskite and report large circular dichroism for single crystals. Comparison with ab initio theory reveals the large circular dichroism arises from the inorganic sublattice rather than the chiral ligand and is an excitonic phenomenon driven by electron-hole exchange interactions, which breaks the degeneracy of transitions between Rashba-Dresselhaus-split bands, resulting in a Cotton effect. Our study suggests that previous data for spin-coated films largely underestimate the optical chirality and provides quantitative insights into the intrinsic optical properties of chiral perovskites for chiroptical and spintronic applications.

Machine learning electronic structure methods based on the one-electron reduced density matrix

The theorems of density functional theory (DFT) establish bijective maps between the local external potential of a many-body system and its electron density, wavefunction and, therefore, one-particle reduced density matrix. Building on this foundation, we show that machine learning models based on the one-electron reduced density matrix can be used to generate surrogate electronic structure methods. We generate surrogates of local and hybrid DFT, Hartree-Fock and full configuration interaction theories for systems ranging from small molecules such as water to more complex compounds like benzene and propanol. The surrogate models use the one-electron reduced density matrix as the central quantity to be learned. From the predicted density matrices, we show that either standard quantum chemistry or a second machine-learning model can be used to compute molecular observables, energies, and atomic forces. The surrogate models can generate essentially anything that a standard electronic structure method can, ranging from band gaps and Kohn-Sham orbitals to energy-conserving ab-initio molecular dynamics simulations and infrared spectra, which account for anharmonicity and thermal effects, without the need to employ computationally expensive algorithms such as self-consistent field theory. The algorithms are packaged in an efficient and easy to use Python code, QMLearn, accessible on popular platforms.

Allosteric control of olefin isomerization kinetics via remote metal binding and its mechanochemical analysis

Allosteric control of reaction thermodynamics is well understood, but the mechanisms by which changes in local geometries of receptor sites lower activation reaction barriers in electronically uncoupled, remote reaction moieties remain relatively unexplored. Here we report a molecular scaffold in which the rate of thermal E-to-Z isomerization of an alkene increases by a factor of as much as 104 in response to fast binding of a metal ion to a remote receptor site. A mechanochemical model of the olefin coupled to a compressive harmonic spring reproduces the observed acceleration quantitatively, adding the studied isomerization to the very few reactions demonstrated to be sensitive to extrinsic compressive force. The work validates experimentally the generalization of mechanochemical kinetics to compressive loads and demonstrates that the formalism of force-coupled reactivity offers a productive framework for the quantitative analysis of the molecular basis of allosteric control of reaction kinetics. Important differences in the effects of compressive vs. tensile force on the kinetic stabilities of molecules are discussed.

Van der Waals isotope heterostructures for engineering phonon polariton dispersions

Element isotopes are characterized by distinct atomic masses and nuclear spins, which can significantly influence material properties. Notably, however, isotopes in natural materials are homogenously distributed in space. Here, we propose a method to configure material properties by repositioning isotopes in engineered van der Waals (vdW) isotopic heterostructures. We showcase the properties of hexagonal boron nitride (hBN) isotopic heterostructures in engineering confined photon-lattice waves-hyperbolic phonon polaritons. By varying the composition, stacking order, and thicknesses of h10BN and h11BN building blocks, hyperbolic phonon polaritons can be engineered into a variety of energy-momentum dispersions. These confined and tailored polaritons are promising for various nanophotonic and thermal functionalities. Due to the universality and importance of isotopes, our vdW isotope heterostructuring method can be applied to engineer the properties of a broad range of materials.

Gravity-driven controls on fluid and carbonate precipitation distributions in fractures

Many challenges related to carbon-dioxide ([Formula: see text]) sequestration in subsurface rock are linked to the injection of fluids through induced or existing fracture networks and how these fluids are altered through geochemical interactions. Here, we demonstrate that fluid mixing and carbonate mineral distributions in fractures are controlled by gravity-driven chemical dynamics. Using optical imaging and numerical simulations, we show that a density contrast between two miscible fluids causes the formation of a low-density fluid runlet that increases in areal extent as the fracture inclination decreases from 90[Formula: see text] (vertical fracture plane) to 30[Formula: see text]. The runlet is sustained over time and the stability of the runlet is controlled by the gravity-driven formation of 3D vortices that arise in a laminar flow regime. When homogeneous precipitation was induced, calcium carbonate covered the entire surface for horizontal fractures (0[Formula: see text]). However, for fracture inclinations greater than 10[Formula: see text], the runlet formation limited the areal extent of the precipitation to less than 15% of the fracture surface. These insights suggest that the ability to sequester [Formula: see text] through mineralization along fractures will depend on the fracture orientation relative to gravity, with horizontal fractures more likely to seal uniformly.

MSI2 promotes translation of multiple IRES-containing oncogenes and virus to induce self-renewal of tumor initiating stem-like cells

RNA-binding protein Musashi 2 (MSI2) is elevated in several cancers and is linked to poor prognosis. Here, we tested if MSI2 promotes MYC and viral mRNA translation to induce self-renewal via an internal ribosome entry sequence (IRES). We performed RIP-seq using anti-MSI2 antibody in tumor-initiating stem-like cells (TICs). MSI2 binds the internal ribosome entry site (IRES)-containing oncogene mRNAs including MYC, JUN and VEGFA as well as HCV IRES to increase their synthesis and promote self-renewal and tumor-initiation at the post-transcriptional level. MSI2 binds a lncRNA to interfere with processing of a miRNA that reduced MYC translation in basal conditions. Deregulation of this integrated MSI2-lncRNA-MYC regulatory loop drives self-renewal and tumorigenesis through increased IRES-dependent translation of MYC mRNA. Overexpression of MSI2 in TICs promoted their self-renewal and tumor-initiation properties. Inhibition of MSI2-RNA binding reduced HCV IRES activity, viral replication and liver hyperplasia in humanized mice predisposed by virus infection and alcohol high-cholesterol high-fat diet. Together MSI2, integrating the MYC oncogenic pathway, can be employed as a therapeutic target in the treatment of HCC patients. A hypothetical model shows that MSI2 binds and activates cap-independent translation of MYC, c-JUN mRNA and HCV through MSI2-binding to Internal Ribosome Entry Sites (IRES) resulting in upregulated MYC, c-JUN and viral protein synthesis and subsequent liver oncogenesis. Inhibitor of the interaction between MYC IRES and MSI2 reduces liver hyperplasia, viral mRNA translation and tumor formation.

Freezing of few nanometers water droplets

Water-ice transformation of few nm nanodroplets plays a critical role in nature including climate change, microphysics of clouds, survival mechanism of animals in cold environments, and a broad spectrum of technologies. In most of these scenarios, water-ice transformation occurs in a heterogenous mode where nanodroplets are in contact with another medium. Despite computational efforts, experimental probing of this transformation at few nm scales remains unresolved. Here, we report direct probing of water-ice transformation down to 2 nm scale and the length-scale dependence of transformation temperature through two independent metrologies. The transformation temperature shows a sharp length dependence in nanodroplets smaller than 10 nm and for 2 nm droplet, this temperature falls below the homogenous bulk nucleation limit. Contrary to nucleation on curved rigid solid surfaces, ice formation on soft interfaces (omnipresent in nature) can deform the interface leading to suppression of ice nucleation. For soft interfaces, ice nucleation temperature depends on surface modulus. Considering the interfacial deformation, the findings are in good agreement with predictions of classical nucleation theory. This understanding contributes to a greater knowledge of natural phenomena and rational design of anti-icing systems for aviation, wind energy and infrastructures and even cryopreservation systems.

Micro/nanodevices for assessment and treatment in stomatology and ophthalmology

Micro/nanodevices have been widely applied for the real-time monitoring of intracellular activities and the delivery of exogenous substances in the past few years. This review focuses on miniaturized micro/nanodevices for assessment and treatment in stomatology and ophthalmology. We first summarize the recent progress in this field by examining the available materials and fabrication techniques, device design principles, mechanisms, and biosafety aspects of micro/nanodevices. Following a discussion of biochemical sensing technology from the cellular level to the tissue level for disease assessment, we then summarize the use of microneedles and other micro/nanodevices in the treatment of oral and ocular diseases and conditions, including oral cancer, eye wrinkles, keratitis, and infections. Along with the identified key challenges, this review concludes with future directions as a small fraction of vast opportunities, calling for joint efforts between clinicians and engineers with diverse backgrounds to help facilitate the rapid development of this burgeoning field in stomatology and ophthalmology.

Learning molecular dynamics with simple language model built upon long short-term memory neural network

Recurrent neural networks have led to breakthroughs in natural language processing and speech recognition. Here we show that recurrent networks, specifically long short-term memory networks can also capture the temporal evolution of chemical/biophysical trajectories. Our character-level language model learns a probabilistic model of 1-dimensional stochastic trajectories generated from higher-dimensional dynamics. The model captures Boltzmann statistics and also reproduces kinetics across a spectrum of timescales. We demonstrate how training the long short-term memory network is equivalent to learning a path entropy, and that its embedding layer, instead of representing contextual meaning of characters, here exhibits a nontrivial connectivity between different metastable states in the underlying physical system. We demonstrate our model's reliability through different benchmark systems and a force spectroscopy trajectory for multi-state riboswitch. We anticipate that our work represents a stepping stone in the understanding and use of recurrent neural networks for understanding the dynamics of complex stochastic molecular systems.

Phonon-exciton Interactions in WSe2 under a quantizing magnetic field

Strong many-body interaction in two-dimensional transitional metal dichalcogenides provides a unique platform to study the interplay between different quasiparticles, such as prominent phonon replica emission and modified valley-selection rules. A large out-of-plane magnetic field is expected to modify the exciton-phonon interactions by quantizing excitons into discrete Landau levels, which is largely unexplored. Here, we observe the Landau levels originating from phonon-exciton complexes and directly probe exciton-phonon interaction under a quantizing magnetic field. Phonon-exciton interaction lifts the inter-Landau-level transition selection rules for dark trions, manifested by a distinctively different Landau fan pattern compared to bright trions. This allows us to experimentally extract the effective mass of both holes and electrons. The onset of Landau quantization coincides with a significant increase of the valley-Zeeman shift, suggesting strong many-body effects on the phonon-exciton interaction. Our work demonstrates monolayer WSe2 as an intriguing playground to study phonon-exciton interactions and their interplay with charge, spin, and valley.

Geochemical Evidence for the Control of Fire by Middle Palaeolithic Hominins

The use of fire played an important role in the social and technological development of the genus Homo. Most archaeologists agree that this was a multi-stage process, beginning with the exploitation of natural fires and ending with the ability to create fire from scratch. Some have argued that in the Middle Palaeolithic (MP) hominin fire use was limited by the availability of fire in the landscape. Here, we present a record of the abundance of polycyclic aromatic hydrocarbons (PAHs), organic compounds that are produced during the combustion of organic material, from Lusakert Cave, a MP site in Armenia. We find no correlation between the abundance of light PAHs (3-4 rings), which are a major component of wildfire PAH emissions and are shown to disperse widely during fire events, and heavy PAHs (5-6 rings), which are a major component of particulate emissions of burned wood. Instead, we find heavy PAHs correlate with MP artifact density at the site. Given that hPAH abundance correlates with occupation intensity rather than lPAH abundance, we argue that MP hominins were able to control fire and utilize it regardless of the variability of fires in the environment. Together with other studies on MP fire use, these results suggest that the ability of hominins to manipulate fire independent of exploitation of wildfires was spatially variable in the MP and may have developed multiple times in the genus Homo.

Colloidal gel elasticity arises from the packing of locally glassy clusters

Colloidal gels formed by arrested phase separation are found widely in agriculture, biotechnology, and advanced manufacturing; yet, the emergence of elasticity and the nature of the arrested state in these abundant materials remains unresolved. Here, the quantitative agreement between integrated experimental, computational, and graph theoretic approaches are used to understand the arrested state and the origins of the gel elastic response. The micro-structural source of elasticity is identified by the l-balanced graph partition of the gels into minimally interconnected clusters that act as rigid, load bearing units. The number density of cluster-cluster connections grows with increasing attraction, and explains the emergence of elasticity in the network through the classic Cauchy-Born theory. Clusters are amorphous and iso-static. The internal cluster concentration maps onto the known attractive glass line of sticky colloids at low attraction strengths and extends it to higher strengths and lower particle volume fractions.