Powdery mildew poses a major threat to black currant production, yet some cultivars naturally withstand infection far better than others. This study reveals that resistant black currants deploy a multilayered defense system involving physical structures, specialized metabolites, and the assembly of protective microbial communities on leaf surfaces. By integrating metabolomics and phyllosphere microbiome profiling, the research identifies key leaf metabolites—such as salicylic acid, trans-zeatin, and griseofulvin—that help recruit beneficial bacteria and fungi linked to disease suppression. These metabolites also directly reduce pathogen growth. Together, these processes explain how resistant cultivars mount a coordinated defense that limits pathogen invasion and maintains plant health.

Tomato fruit size, a trait that strongly influences market value and yield, is governed by intricate developmental processes. This study uncovers a previously unknown translational regulatory pathway mediated by the RNA-binding protein SlRBP1. Through fruit-specific gene manipulation, researchers show that SlRBP1 is essential for normal cell division and expansion within the tomato pericarp. The findings reveal that SlFBA7 and SlGPIMT are direct downstream gene targets whose translation is controlled by SlRBP1, and silencing either gene produces small fruits similar to SlRBP1-suppressed plants. This work highlights translational regulation as a key but underexplored mechanism for improving fruit size and overall productivity.

This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in peaches. Using whole-genome resequencing data from an F1 progeny of two distant peach cultivars, the researchers constructed an ultra-high-density genetic map, identifying key quantitative trait loci (QTLs) for traits such as fruit shape, color, and maturity. Notably, the study introduces machine learning models for more accurate phenotyping of fruit color, revealing two previously undetectable QTLs for peach flesh color variation. These innovations provide a new framework for precision breeding, enhancing peach quality and other complex traits through improved mapping and phenotyping strategies.

Composite solid electrolytes (CSEs) are promising for solid-state Li metal batteries but suffer from inferior room-temperature ionic conductivity due to sluggish ion transport and high cost due to expensive active ceramic fillers. Here, a host–guest inversion engineering strategy is proposed to develop superionic CSEs using cost-effective SiO₂ nanoparticles as passive ceramic hosts and poly(vinylidene fluoride-hexafluoropropylene) (PVH) microspheres as polymer guests, forming an unprecedented “polymer guest-in-ceramic host” (i.e., PVH-in-SiO₂) architecture differing from the traditional “ceramic guest-in-polymer host”. The PVH-in-SiO₂ exhibits excellent Li-salt dissociation, achieving high-concentration free Li⁺. Owing to the low diffusion energy barriers and high diffusion coefficient, the free Li⁺ is thermodynamically and kinetically favorable to migrate to and transport at the SiO₂/PVH interfaces. Consequently, the PVH-in-SiO₂ delivers an exceptional ionic conductivity of 1.32 × 10⁻³ S cm⁻¹ at 25 °C (vs. typically 10⁻⁵–10⁻⁴ S cm⁻¹ using high-cost active ceramics), achieved under an ultralow residual solvent content of 2.9 wt% (vs. 8–15 wt% in other CSEs). Additionally, PVH-in-SiO₂ is electrochemically stable with Li anode and various cathodes. Therefore, the PVH-in-SiO₂ demonstrates excellent high-rate cyclability in LiFePO₄|Li full cells (92.9% capacity-retention at 3C after 300 cycles under 25 °C) and outstanding stability with high-mass-loading LiFePO₄ (9.2 mg cm⁻¹) and high-voltage NCM622 (147.1 mAh g⁻¹). Furthermore, we verify the versatility of the host–guest inversion engineering strategy by fabricating Na-ion and K-ion-based PVH-in-SiO₂ CSEs with similarly excellent promotions in ionic conductivity. Our strategy offers a simple, low-cost approach to fabricating superionic CSEs for large-scale application of solid-state Li metal batteries and beyond.

Emerging two-dimensional (2D) semiconductors are among the most promising materials for ultra-scaled transistors due to their intrinsic atomic-level thickness. As the stacking process advances, the complexity and cost of nanosheet field-effect transistors (NSFETs) and complementary FET (CFET) continue to rise. The 1 nm technology node is going to be based on Si-CFET process according to international roadmap for devices and systems (IRDS) (2022, https://irds.ieee.org/), but not publicly confirmed, indicating that more possibilities still exist. The miniaturization advantage of 2D semiconductors motivates us to explore their potential for reducing process costs while matching the performance of next-generation nodes in terms of area, power consumption and speed. In this study, a comprehensive framework is built. A set of MoS₂ NSFETs were designed and fabricated to extract the key parameters and performances. And then for benchmarking, the sizes of 2D-NSFET are scaled to a extent that both of the Si-CFET and 2D-NSFET have the same average device footprint. Under these conditions, the frequency of ultra-scaled 2D-NSFET is found to improve by 36% at a fixed power consumption. This work verifies the feasibility of replacing silicon-based CFETs of 1 nm node with 2D-NSFETs and proposes a 2D technology solution for 1 nm nodes, i.e., “2D eq 1 nm” nodes. At the same time, thanks to the lower characteristic length of 2D semiconductors, the miniaturized 2D-NSFET achieves a 28% frequency increase at a fixed power consumption. Further, developing a standard cell library, these devices obtain a similar trend in 16-bit RISC-V CPUs. This work quantifies and highlights the advantages of 2D semiconductors in advanced nodes, offering new possibilities for the application of 2D semiconductors in high-speed and low-power integrated circuits.

Understanding the genetic resistance to biotic stresses in peach (Prunus persica) and apricot (Prunus armeniaca) is crucial for sustainable fruit production. A comprehensive study was conducted using Genome-Wide Association Studies (GWAS) across multiple environments, identifying key genetic markers associated with resistance to seven major pests and diseases. This study uncovered genotype-by-environment interactions (G × E), highlighting the complexity of breeding for disease resistance in these crops. The results provide valuable insights into the genetic architecture of resistance, offering a solid foundation for marker-assisted selection (MAS) in future fruit tree breeding programs aimed at improving pest and disease tolerance.

Researchers have developed a novel computational imaging system that integrates optical compression and deep learning to achieve high-speed video capture using only 5% of the data required by conventional cameras. The system successfully visualized Leidenfrost droplet dynamics at 1,200 frames per second, delivering performance comparable to commercial high-speed cameras while significantly reducing cost and storage requirements.