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ABSTRACT Virus-induced gene silencing (VIGS) allows for the rapid targeting of gene expression and has been instrumental in characterizing plant genes. However, foreign sequences inserted into VIGS vectors are rarely maintained for unknown reasons. Citrus yellow vein-associated umbravirus-like virus (CY1) with its solved secondary structure was converted into a VIGS vector to determine why simple hairpins inserted into non-functional, single-stranded locations are not maintained. When CY1 contained foreign hairpins with thermodynamic properties (positional entropy and/or ΔG) differing from those of natural CY1 hairpins, deletions arose within a few weeks of infectingNicotiana benthamiana. In contrast, duplication and insertion of four natural CY1 hairpins (up to 200 nt) into the same locations were retained until plant senescence. Hairpins containing similar conformations and thermodynamic properties as natural hairpins were also retained, as were hairpins that shared thermodynamic properties but were conformationally distinct. By predicting and modulating these thermodynamic properties, a hairpin was retained by CY1 for at least 30 months in citrus. These findings strongly suggest that RNA viruses have evolved to contain substructures with specific thermodynamic properties, and hairpins containing these properties are stable when inserted into non-functional regions of the genome, opening up VIGS for long-lived trees and vines. IMPORTANCEPlus-strand RNA plant viruses are used as tools to introduce small interfering RNAs (siRNAs) into laboratory plants to target and silence genes. However, virus-induced gene silencing (VIGS) vectors engineered to contain foreign hairpins or other sequences for siRNA generation are not stable, and the foreign sequences are rapidly lost. We found that foreign sequences are not maintained in an umbravirus-like VIGS vector (CY1) because their physical properties conflict with the innate properties of the CY1 genome’s substructures (i.e., hairpins). When natural CY1 hairpins were duplicated and inserted into locations where previous inserts were rapidly lost, the hairpins were now stable as were unrelated hairpins with the same physical properties. By mimicking the physical properties of the viral genome, one insert was stable for over 30 months. These results suggest that RNA viral genomes have evolved to have specific physical properties, and these properties appear to be similar for other plus-strand RNA viruses. 

During our study of the synthesis of metal nanoparticles via chemical reduction methods, we found that some colloidal solutions of silver nanoparticles displayed dichroic effect. The dichroic effect is a phenomenon where a material displays two different colors in transmitted light and reflected light. In this study, dichroic silver nanoparticles were obtained via a simple chemical reduction method under ambient conditions. Ascorbic acid was used as the reducing agent and trisodium citrate was used as the stabilizing agent. A colloidal solution of synthesized silver nanoparticles showed an opaque gray color in reflected light and a translucent pink color in transmitted light. Another colloidal solution prepared in the presence of copper (II) sulphate displayed a new combination of dichroic colors: opaque blue and translucent green. To understand the formation of dichroic effect, Transmission electron microscopy (TEM) and UV-Vis spectroscopy were used to characterize and study the silver nanoparticles in these colloids. TEM study showed that silver nanoparticles with different sizes and shapes were present in the solutions that displayed dichroic effect. By comparing the morphology of dichroic silver nanoparticles with that of the silver nanoparticles that exhibited no dichroic effect, we concluded that both the sizes and the shapes of nanoparticles play important roles in the formation of dichroic effect. The small particles are responsible for the absorbance of light, which results in the color in transmitted light. While large particles account for the scattering of light and lead to the color in reflected light. Different combinations of nanoparticles with different sizes and shapes lead to different colors for the dichroic effects. 

The scattering transform is a multilayered wavelet-based architecture that acts as a model of convolutional neural networks. Recently, several works have generalized the scattering transform to graph-structured data. Our work builds on these constructions by introducing windowed and nonwindowed geometric scattering transforms for graphs based on two very general classes wavelets, which are in most cases based on asymmetric matrices. We show that these transforms have many of the same theoretical guarantees as their symmetric counterparts. As a result, the proposed construction unifies and extends known theoretical results for many of the existing graph scattering architectures. Therefore, it helps bridge the gap between geometric scattering and other graph neural networks by introducing a large family of networks with provable stability and invariance guarantees. These results lay the groundwork for future deep learning architectures for graph-structured data that have learned filters and also provably have desirable theoretical properties. 

Abstract Metal halide perovskites show promise for next-generation light-emitting diodes, particularly in the near-infrared range, where they outperform organic and quantum-dot counterparts. However, they still fall short of costly III-V semiconductor devices, which achieve external quantum efficiencies above 30% with high brightness. Among several factors, controlling grain growth and nanoscale morphology is crucial for further enhancing device performance. This study presents a grain engineering methodology that combines solvent engineering and heterostructure construction to improve light outcoupling efficiency and defect passivation. Solvent engineering enables precise control over grain size and distribution, increasing light outcoupling to ~40%. Constructing 2D/3D heterostructures with a conjugated cation reduces defect densities and accelerates radiative recombination. The resulting near-infrared perovskite light-emitting diodes achieve a peak external quantum efficiency of 31.4% and demonstrate a maximum brightness of 929 W sr⁻¹m⁻². These findings indicate that perovskite light-emitting diodes have potential as cost-effective, high-performance near-infrared light sources for practical applications.