Ultrathin BIC Metasurfaces Based on Ultra-Low-Loss SbSe Phase-Change Material.

Ultrathin and low-loss phase-change materials (PCMs) are highly valued for their fast and effective phase transitions and applications in reconfigurable photonic chips, metasurfaces, optical modulators, sensors, photonic memories, and neuromorphic computing. However, conventional PCMs mostly suffer from high intrinsic losses in the near-infrared (NIR) region, limiting their potential for high quality factor (-factor) resonant metasurfaces. Here we present the design and fabrication of tunable bound states in the continuum (BIC) metasurfaces using the ultra-low-loss PCM SbSe.

Haplotype-resolved genome assembly and resequencing provide insights into the origin and breeding of modern rose.

Modern rose (Rosa hybrida) is a recently formed interspecific hybrid and has become one of the most important and widely cultivated ornamentals. Here we report the haplotype-resolved chromosome-scale genome assembly of the tetraploid R. hybrida 'Samantha' ('JACmantha') and a genome variation map of 233 Rosa accessions involving various wild species, and old and modern cultivars.

Current computational tools for protein lysine acylation site prediction.

As a main subtype of post-translational modification (PTM), protein lysine acylations (PLAs) play crucial roles in regulating diverse functions of proteins. With recent advancements in proteomics technology, the identification of PTM is becoming a data-rich field. A large amount of experimentally verified data is urgently required to be translated into valuable biological insights.

SLAM: Structure-aware lysine β-hydroxybutyrylation prediction with protein language model.

Post-translational modifications (PTMs) diversify protein functions by adding/removing chemical groups to certain amino acid. As a newly-reported PTM, lysine β-hydroxybutyrylation (Kbhb) presents a new avenue to functional proteomics. Therefore, accurate and efficient prediction of Kbhb sites is imperative.

Multi-omics analysis reveals key regulatory defense pathways and genes involved in salt tolerance of rose plants.

Salinity stress causes serious damage to crops worldwide, limiting plant production. However, the metabolic and molecular mechanisms underlying the response to salt stress in rose ( spp.) remain poorly studied.

Beyond the lab: a nanoimprint metalens array-based augmented reality.

A see-through augmented reality prototype has been developed based on an ultrathin nanoimprint metalens array, opening up a full-colour, video-rate, and low-cost 3D near-eye display.

Optically addressable spin defects coupled to bound states in the continuum metasurfaces.

Van der Waals (vdW) materials, including hexagonal boron nitride (hBN), are layered crystalline solids with appealing properties for investigating light-matter interactions at the nanoscale. hBN has emerged as a versatile building block for nanophotonic structures, and the recent identification of native optically addressable spin defects has opened up exciting possibilities in quantum technologies. However, these defects exhibit relatively low quantum efficiencies and a broad emission spectrum, limiting potential applications.

Phthalates Induce Neurotoxicity by Disrupting the Mfn2-PERK Axis-Mediated Endoplasmic Reticulum-Mitochondria Interaction.

Di-(2-ethylhexyl) phthalate (DEHP), as the most common phthalate, has been extensively used as a plasticizer to improve the plasticity of agricultural products, which pose severe harm to human health. Mitochondrial dynamics and endoplasmic reticulum (ER) homeostasis are indispensable for maintaining mitochondria-associated ER membrane (MAM) integrity. In this study, we aimed to explore the effect of DEHP on the nervous system and its association with the ER-mitochondria interaction.

Phthalate drives splenic inflammatory response via activating HSP60/TLR4/NLRP3 signaling axis-dependent pyroptosis.

As the most produced phthalate, di-(2-ethylhexyl) phthalate (DEHP) is a widely environmental pollutant primarily used as a plasticizer, which cause the harmful effects on human health. However, the impact of DEHP on spleen and its underlying mechanisms are still unclear. Pyroptosis is a novel form of cell death induced by activating NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasomes and implicated in pathogenesis of numerous inflammatory diseases.

Nonlinear Boost of Optical Angular Momentum Selectivity by Hybrid Nanolaser Circuits.

Selective control of light is essential for optical science and technology, with numerous applications. However, optical selectivity in the angular momentum of light has been quite limited, remaining constant by increasing the incident light power on previous passive optical devices. Here, we demonstrate a nonlinear boost of optical selectivity in both the spin and orbital angular momentum of light through near-field selective excitation of single-mode nanolasers.

Unraveling the Chirality Transfer from Circularly Polarized Light to Single Plasmonic Nanoparticles.

Due to their broken symmetry, chiral plasmonic nanostructures have unique optical properties and numerous applications. However, there is still a lack of comprehension regarding how chirality transfer occurs between circularly polarized light (CPL) and these structures. Here, we thoroughly investigate the plasmon-assisted growth of chiral nanoparticles from achiral Au nanocubes (AuNCs) via CPL without the involvement of any chiral molecule stimulators.

Metafiber transforming arbitrarily structured light.

Structured light has proven useful for numerous photonic applications. However, the current use of structured light in optical fiber science and technology is severely limited by mode mixing or by the lack of optical elements that can be integrated onto fiber end-faces for wavefront engineering, and hence generation of structured light is still handled outside the fiber via bulky optics in free space. We report a metafiber platform capable of creating arbitrarily structured light on the hybrid-order Poincaré sphere.

ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning.

Lysine 2-hydroxyisobutylation (Khib), which was first reported in 2014, has been shown to play vital roles in a myriad of biological processes including gene transcription, regulation of chromatin functions, purine metabolism, pentose phosphate pathway and glycolysis/gluconeogenesis. Identification of Khib sites in protein substrates represents an initial but crucial step in elucidating the molecular mechanisms underlying protein 2-hydroxyisobutylation. Experimental identification of Khib sites mainly depends on the combination of liquid chromatography and mass spectrometry.

Disorder-Induced Topological State Transition in the Optical Skyrmion Family.

Skyrmions endowed with topological protection have been extensively investigated in various platforms including magnetics, ferroelectrics, and liquid crystals, stimulating applications such as memories, logic devices, and neuromorphic computing. While the optical counterpart has been proposed and realized recently, the study of optical skyrmions is still in its infancy. Among the unexplored questions, the investigation of the topology induced robustness against disorder is of substantial importance on both fundamental and practical sides but remains elusive.

Automatic Time Picking for Weak Seismic Phase in the Strong Noise and Interference Environment: An Hybrid Method Based on Array Similarity.

The extraction of travel-time curve of seismic phase is very important for the subsequent inference of the structural properties of underground media in seismology. In recent years, with the increase in the amount of data, manual processing is facing significant challenges, and automatic signal processing has gradually become the mainstream. According to the similarity of array signals and considering the elimination of outliers, we propose an improved multi-channel cross-correlation method using the L1 norm measure to obtain preliminary results, which builds on a new controllable measurement mode.

Plasmonic bound states in the continuum to tailor light-matter coupling.

Plasmon resonances play a pivotal role in enhancing light-matter interactions in nanophotonics, but their low-quality factors have hindered applications demanding high spectral selectivity. Here, we demonstrate the design and 3D laser nanoprinting of plasmonic nanofin metasurfaces, which support symmetry-protected bound states in the continuum up to the fourth order. By breaking the nanofins' out-of-plane symmetry in parameter space, we achieve high-quality factor (up to 180) modes under normal incidence.

Trimethyltin induces apoptosis and necroptosis of mouse liver by oxidative stress through YAP phosphorylation.

Trimethyltin (TMT) is widely used as a major component of plastic stabilizers in agriculture and industry, and can accumulate in large quantities in the liver. To investigate the relationship between liver tissue damage induced by TMT exposure and YAP phosphorylation in mice, we gave the mice drinking water containing 0.01 mg/mL TMT for 14 days to establish an in vivo experimental model, and continuously treated AML12 cells with 20 μM TMT for 24 h to establish an in vitro experimental model.

Deblurring of Sound Source Orientation Recognition Based on Deep Neural Network.

Underwater target detection and identification technology are currently two of the most important research directions in the information disciplines. Traditionally, underwater target detection technology has struggled to meet the needs of current engineering. However, due to the large manifold error of the underwater sonar array and the complexity of ensuring long-term signal stability, traditional high-resolution array signal processing methods are not ideal for practical underwater applications.

Seismic Facies Analysis Using the Multiattribute SOM-K-Means Clustering.

An accurate seismic facies analysis (SFA) can provide insight into the subsurface sedimentary facies and has guiding significance for geological exploration. Many machine learning algorithms, including unsupervised, supervised, and deep learning algorithms, have been developed successfully for SFA over the past decades. However, SFA and facies classification are still challenging tasks due to the complex characteristics of geological and seismic data.