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More Than 30 000-fold Field Enhancement of Terahertz Nanoresonators Enabled by Rapid Inverse Design
The rapid development of 6G communications using terahertz (THz) electromagnetic waves has created a demand for highly sensitive THz nanoresonators capable of detecting these waves. Among the potential candidates, THz nanogap loop arrays show promising characteristics but require significant computational resources for accurate simulation. This requirement arises because their unit cells are 10 times smaller than millimeter wavelengths, with nanogap regions that are 1 000 000 times smaller. To address this challenge, we propose a rapid inverse design method using physics-informed machine learning, employing double deep Q-learning with an analytical model of the THz nanogap loop array. In ~39 h on a middle-level personal computer, our approach identifies the optimal structure through 200 000 iterations, achieving an experimental electric field enhancement of 32 000 at 0.2 THz, 300% stronger than prior results. In conclusion, our analytical model-based approach significantly reduces the amount of computational resources required, offering a practical alternative to numerical simulation-based inverse design for THz nanodevices.
Carbon-Related Quantum Emitter in Hexagonal Boron Nitride with Homogeneous Energy and 3-Fold Polarization
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200-Fold Lifetime Extension of 2,6- Dihydroxyanthraquinone Electrolyte during Flow Battery Operation
Not provided.
Nanoscale Prediction of the Thermal, Mechanical, and Transport Properties of Hydrated Clay on 10 6 - and 10 15 -Fold Larger Length and Time Scales
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Giant Enhancement of Four-Wave Mixing by Doubly Zone-Folded Nonlocal Metasurfaces
Resonant optical metasurfaces hold promise for enhancing nonlinear optical signals and manipulating their fundamental properties. However, they rarely excel at amplifying signals from nonlinear processes with two incident pump beams, such as four-wave mixing (FWM) or sum-frequency generation. Frequency-mixing experiments impose challenging requirements for metasurface design due to the need to support multiple optical resonances with compatible field profiles at specified resonant wavelengths, often across a substantial spectral separation. Here, in this work, we introduce nonlocal ‘quadromer’ metasurfaces containing four nanostructures per unit cell as the key to unlocking configurable, multiresonant metasurfaces that enhance frequency-mixing processes. As a proof of concept, we experimentally demonstrate enhanced FWM using quadromer metasurfaces made of silicon and silicon-rich silicon nitride. The results are relevant for applications such as imaging of infrared light upconverted into the visible spectrum and the generation of quantum light via spontaneous FWM.
Amorphous to Crystal Phase Change Memory Effect with Two-Fold Bandgap Difference in Semiconducting K
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Robust Hydrogen-Bonded Organic Framework with Four-Fold Interpenetration for Adsorptive Separation of C 2 H 6 /C 2 H 4 and Xe/Kr
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Surface chemistry-mediated modulation of adsorbed albumin folding state specifies nanocarrier clearance by distinct macrophage subsets
Controlling nanocarrier interactions with the immune system requires a thorough understanding of the surface properties that modulate protein adsorption in biological fluids, since the resulting protein corona redefines cellular interactions with nanocarrier surfaces. Albumin is initially one of the dominant proteins to adsorb to nanocarrier surfaces, a process that is considered benign or beneficial by minimizing opsonization or inflammation. Here, we demonstrate the surface chemistry of a model nanocarrier can be engineered to stabilize or denature the three-dimensional conformation of adsorbed albumin, which respectively promotes evasion or non-specific clearance in vivo. Interestingly, certain common chemistries that have long been considered to convey stealth properties denature albumin to promote nanocarrier recognition by macrophage class A1 scavenger receptors, providing a means for their eventual removal from systemic circulation. We establish that the surface chemistry of nanocarriers can be specified to modulate adsorbed albumin structure and thereby tune clearance by macrophage scavenger receptors.
Birth of protein folds and functions in the virome
The rapid evolution of viruses generates proteins that are essential for infectivity and replication but with unknown functions, due to extreme sequence divergence. Here, using a database of 67,715 newly predicted protein structures from 4,463 eukaryotic viral species, we found that 62% of viral proteins are structurally distinct and lack homologues in the AlphaFold database. Among the remaining 38% of viral proteins, many have non-viral structural analogues that revealed surprising similarities between human pathogens and their eukaryotic hosts. Structural comparisons suggested putative functions for up to 25% of unannotated viral proteins, including those with roles in the evasion of innate immunity. In particular, RNA ligase T-like phosphodiesterases were found to resemble phage-encoded proteins that hydrolyse the host immune-activating cyclic dinucleotides 3',3'- and 2',3'-cyclic GMP-AMP (cGAMP). Experimental analysis showed that RNA ligase T homologues encoded by avian poxviruses similarly hydrolyse cGAMP, showing that RNA ligase T-mediated targeting of cGAMP is an evolutionarily conserved mechanism of immune evasion that is present in both bacteriophage and eukaryotic viruses. Together, the viral protein structural database and analyses presented here afford new opportunities to identify mechanisms of virus–host interactions that are common across the virome.
Author Correction: Birth of protein folds and functions in the virome
This article provides a correction to: Nature https://doi.org/10.1038/s41586-024-07809-y Published online 26 August 2024.
The fluorescent aptamer Squash extensively repurposes the adenine riboswitch fold
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Structures of AAA protein translocase Bcs1 suggest translocation mechanism of a folded protein
Abstract not provided
AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
Protein-ligand docking is a computational method for identifying drug leads. The method is capable of narrowing a vast library of compounds down to a tractable size for downstream simulation or experimental testing and is widely used in drug discovery. While there has been progress in accelerating scoring of compounds with artificial intelligence, few works have bridged these successes back to the virtual screening community in terms of utility and forward-looking development. We demonstrate the power of high-speed ML models by scoring 1 billion molecules in under a day (50 k predictions per GPU seconds). We showcase a workflow for docking utilizing surrogate AI-based models as a pre-filter to a standard docking workflow. Our workflow is ten times faster at screening a library of compounds than the standard technique, with an error rate less than 0.01% of detecting the underlying best scoring 0.1% of compounds. Our analysis of the speedup explains that another order of magnitude speedup must come from model accuracy rather than computing speed. In order to drive another order of magnitude of acceleration, we share a benchmark dataset consisting of 200 million 3D complex structures and 2D structure scores across a consistent set of 13 million “in-stock” molecules over 15 receptors, or binding sites, across the SARS-CoV-2 proteome. We believe this is strong evidence for the community to begin focusing on improving the accuracy of surrogate models to improve the ability to screen massive compound libraries 100 × or even 1000 × faster than current techniques and reduce missing top hits. The technique outlined aims to be a fast drop-in replacement for docking for screening billion-scale molecular libraries.
Cryo-EM confirms a common fibril fold in the heart of four patients with ATTRwt amyloidosis
ATTR amyloidosis results from the conversion of transthyretin into amyloid fibrils that deposit in tissues causing organ failure and death. This conversion is facilitated by mutations in ATTRv amyloidosis, or aging in ATTRwt amyloidosis. ATTRv amyloidosis exhibits extreme phenotypic variability, whereas ATTRwt amyloidosis presentation is consistent and predictable. Previously, we found unique structural variabilities in cardiac amyloid fibrils from polyneuropathic ATTRv-I84S patients. In contrast, cardiac fibrils from five genotypically different patients with cardiomyopathy or mixed phenotypes are structurally homogeneous. To understand fibril structure’s impact on phenotype, it is necessary to study the fibrils from multiple patients sharing genotype and phenotype. Here we show the cryo-electron microscopy structures of fibrils extracted from four cardiomyopathic ATTRwt amyloidosis patients. Our study confirms that they share identical conformations with minimal structural variability, consistent with their homogenous clinical presentation. Our study contributes to the understanding of ATTR amyloidosis biopathology and calls for further studies.