Inverse-designed multi-directional remote cloak.

Invisibility as a superior self-protection tactic has long captivated the popular interest in both academia and industry. However, state-of-the-art invisibility cloaks typically need to completely wrap or shield a hidden object, leading to a hidden object that cannot interact with the environment outside. This study develops a precise and efficient de-homogenization optimized-architecture to produce high-performance, simple-parameter, and fabricable remote cloak without constraints on geometry.

Progress on intelligent metasurfaces for signal relay, transmitter, and processor.

Pursuing higher data rate with limited spectral resources is a longstanding topic that has triggered the fast growth of modern wireless communication techniques. However, the massive deployment of active nodes to compensate for propagation loss necessitates high hardware expenditure, energy consumption, and maintenance cost, as well as complicated network interference issues. Intelligent metasurfaces, composed of a number of subwavelength passive or active meta-atoms, have recently found to be a new paradigm to actively reshape wireless communication environment in a green way, distinct from conventional works that passively adapt to the surrounding.

Causal relationship between B vitamins and neuropsychiatric disorders: A systematic review and meta-analysis.

Recently, there has been an increasing interest in how diet and nutrition influence both physical and mental health. Numerous studies have highlighted the potential role of B vitamins in neuropsychiatric disorders (NPDs), yet the exact causal relationship between these nutrients and NPDs remains unclear. In our Mendelian randomization (MR) meta-analysis, we examined the links between B vitamins (VB6, VB12, and folate) and NPDs, utilizing data from previous MR studies, the UK Biobank, and FinnGen databases.

Structure-Activity Relationship Studies of DNA Methyltransferase 1 Monovalent Degraders.

DNA methyltransferase 1 (DNMT1), which catalyzes maintenance methylation of hemimethylated DNA during DNA replication, is overexpressed in cancer. Recently, the first-in-class DNMT1-selective noncovalent small-molecule inhibitors, GSK3484862 and GSK3685032, were discovered. These inhibitors were also reported to degrade DNMT1.

A guidance to intelligent metamaterials and metamaterials intelligence.

The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing.

Configurable Multi-Layer Perceptron-Based Soft Sensors on Embedded Field Programmable Gate Arrays: Targeting Diverse Deployment Goals in Fluid Flow Estimation.

This study presents a comprehensive workflow for developing and deploying Multi-Layer Perceptron (MLP)-based soft sensors on embedded FPGAs, addressing diverse deployment objectives. The proposed workflow extends our prior research by introducing greater model adaptability. It supports various configurations-spanning layer counts, neuron counts, and quantization bitwidths-to accommodate the constraints and capabilities of different FPGA platforms.

Regulating the production distribution in Ni-Cu nanoparticle mediated nitrile hydrogenation.

The selective hydrogenation of nitrile compounds represents a pivotal area of research within both industrial and academic catalysis. In this study, we prepared Ni-Cu bimetallic catalysts through a co-deposition-crystallization sequence, aimed at the efficient production of primary and secondary amines. The enhanced selectivity for primary amines is attributed to the downshift of the d-band center of NiCu, which weakens the adsorption of key imine intermediates.

DLGAP3 suppresses malignant behaviors of glioma cells via inhibiting RGS12-mediated MAPK/ERK signaling.

Background: Glioma is the most common malignant tumor of the central nervous system, and is characterized by high recurrence, poor prognosis and especially complex pathogenesis. The synaptic plasticity-related protein DLGAP3 is mainly involved in the assembly and function of postsynaptic density complex. It's widely known that DLGAP3 participating in the occurrence of various neuropsychiatric diseases, but its role in glioma tumorigenesis remains largely unclear.

Toward the Rational Design of an OsM Center for Methane Activation: Gas-Phase Result-Derived Neural Network Model.

Gas-phase reactions of [OsB] ( = 1-4) with methane at ambient temperature have been studied by using quadrupole-ion trap mass spectrometry combined with quantum chemical calculations. The [OsB] ( = 1-4) cluster ions can undergo dehydrogenation reactions with methane. Comprehensive analysis of the [OsB]/CH ( = 1-4) system with Os-complexes ([OsC] ( = 1-3) and [OsO] ( = 1-3)) shows that the large polarity of the cluster and the high sum of the pair energies between Os and the ligand in the ETS-NOCV combine to promote the ability of the cluster to activate methane.

Targeted Degradation of Receptor-Interacting Protein Kinase 1 to Modulate the Necroptosis Pathway.

Necroptosis is a highly regulated form of necrotic cell death that plays an essential role in pathogen defense and tissue homeostasis. Abnormal regulation of the necroptotic pathway has been implicated in the pathogenesis of various human diseases, including cancer, inflammatory, and neurodegenerative diseases. Receptor-interacting protein kinase 1 (RIPK1) serves as a crucial regulator of the necroptotic signaling pathway and has been identified as a potential therapeutic target.

Risk Factors for Multidrug-Resistant Bacterial Infection in Diabetic Foot Ulcers.

Background: This study aimed to analyze the distribution of multidrug-resistant (MDR) organisms (MDROs) in patients with diabetic foot ulcers (DFUs) and to identify risk factors for MDRO infections.

Methods: Patients hospitalized with DFUs were enrolled, and ulcer swabs were cultured for bacterial identification and antibiotic susceptibility testing. Hematology and blood biochemistry were also assessed.

Holographic multiplexing metasurface with twisted diffractive neural network.

As the cornerstone of AI generated content, data drives human-machine interaction and is essential for developing sophisticated deep learning agents. Nevertheless, the associated data storage poses a formidable challenge from conventional energy-intensive planar storage, high maintenance cost, and the susceptibility to electromagnetic interference. In this work, we introduce the concept of metasurface disk, meta-disk, to expand the capacity limits of optical holographic storage by leveraging uncorrelated structural twist.

Group Contribution Method Supervised Neural Network for Precise Design of Organic Nonlinear Optical Materials.

To rationalize the design of D-π-A type organic small-molecule nonlinear optical materials, a theory guided machine learning framework is constructed. Such an approach is based on the recognition that the optical property of the molecule is predictable upon accumulating the contribution of each component, which is in line with the concept of group contribution method in thermodynamics. To realize this, a Lewis-mode group contribution method (LGC) has been developed in this work, which is combined with the multistage Bayesian neural network and the evolutionary algorithm to constitute an interactive framework (LGC-msBNN-EA).

A Universal Framework for General Prediction of Physicochemical Properties: The Natural Growth Model.

To precisely and reasonably describe the contribution of interatomic and intermolecular interactions to the physicochemical properties of complex systems, a chemical message passing strategy as driven by graph neural network is proposed. Thus, by distinguishing inherent and environmental features of atoms, as well as proper delivering of these messages upon growth of systems from atoms to bulk level, the evolution of system features affords eventually the target properties like the adsorption wavelength, emission wavelength, solubility, photoluminescence quantum yield, ionization energy, and lipophilicity. Considering that such a model combines chemical principles and natural behavior of atom aggregation crossing multiple scales, most likely, it will be proven to be rational and efficient for more general aims in dealing with complex systems.

Negative Conductivity Induced Reconfigurable Gain Metasurfaces and Their Nonlinearity.

The past decades have witnessed the rapid development of metamaterials and metasurfaces. However, loss is still a challenging problem limiting numerous practical applications, including long-range wireless communications, superscattering, and non-Hermitian physics. Recently, great effort has been made to minimize the loss, however, they are too complicated for practical implementation and still restricted by the theoretical limit.

One-Pot, Solvent Free Synthesis of 2,5-Furandicarboxylic Acid from Deep Eutectic Mixtures of Sugars as Mediated by Bifunctional Catalyst.

Currently one-pot conversion of sugars to 2,5-furandicarboxylic acid (FDCA) is of significant interest due to the attainability of sugars as a feedstock and the enormous potential of FDCA as a bioplastic monomer. However, it remains challenging to construct efficient catalysts for this process. In this study, CoO species were anchored to a sulfonated covalent organic framework thus affording a bifunctional catalyst (CoO@COF-SOH).

Zirconia specimens printed by vat photopolymerization: Mechanical properties, fatigue properties, and fractography analysis.

Purpose: The mechanical and fatigue properties of zirconia specimens printed by vat photopolymerization (VPP) were evaluated and compared with those of zirconia specimens milled by computer numerical control (CNC).

Materials And Methods: Bar-shaped specimens were printed by stereolithography (SL) and digital light processing (DLP). CNC-milled specimens were used as control samples.

Reducing the uncertainty in estimating soil microbial-derived carbon storage.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and plays a crucial role in mitigating climate change and enhancing soil productivity. Microbial-derived carbon (MDC) is the main component of the persistent SOC pool. However, current formulas used to estimate the proportional contribution of MDC are plagued by uncertainties due to limited sample sizes and the neglect of bacterial group composition effects.

The First-In-Class Deubiquitinase-Targeting Chimera Stabilizes and Activates cGAS.

Deubiquitinase-targeting chimera (DUBTAC) is a promising technology for inducing targeted protein stabilization (TPS). Despite its therapeutic potential, very few proteins have been stabilized by DUBTACs to date. The limited applicability of this technology is likely due to the modest DUBTAC-induced protein stabilization effect, and the scarcity of effective deubiquitinase ligands that can be harnessed for DUBTAC development.

Harnessing the Missing Spectral Correlation for Metasurface Inverse Design.

A long-held tenet in computer science asserts that the training of deep learning is analogous to an alchemical furnace, and its "black box" signature brings forth inexplicability. For electromagnetic metasurfaces, the related intelligent applications also get stuck into such a dilemma. Although the past 5 years have witnessed a proliferation of deep learning-based works across complex photonic scenarios, they neglect the already existing but untapped physical laws.

Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology.

Tumor microenvironment-regulated drug delivery system combined with sonodynamic therapy for the synergistic treatment of breast cancer.

Co-loading of sonosensitizers and chemotherapeutic drugs into nanocarriers can improve the biocompatibilities, stabilities, and targeting of drugs and reduce the adverse reactions of drugs, providing a robust platform to orchestrate the synergistic interplay between chemotherapy and sonodynamic therapy (SDT) in cancer treatment. In this regard, biodegradable manganese dioxide (MnO) has attracted widespread attention because of its unique properties in the tumor microenvironment (TME). Accordingly, herein, MnO nanoshells with hollow mesoporous structures (H-MnO) were etched to co-load hematoporphyrin monomethyl ether (HMME) and doxorubicin (DOX), and DOX/HMME-HMnO@bovine serum albumin (BSA) obtained after simple BSA modification of DOX/HMME-HMnO exhibited excellent hydrophilicity and dispersibility.

Non-Invasive Self-Adaptive Information States' Acquisition inside Dynamic Scattering Spaces.

Pushing the information states' acquisition efficiency has been a long-held goal to reach the measurement precision limit inside scattering spaces. Recent studies have indicated that maximal information states can be attained through engineered modes; however, partial intrusion is generally required. While non-invasive designs have been substantially explored across diverse physical scenarios, the non-invasive acquisition of information states inside dynamic scattering spaces remains challenging due to the intractable non-unique mapping problem, particularly in the context of multi-target scenarios.