Browse Articles

Modeling network evolution by multi-agent reinforcement learning

Author Correction: Genetic background and window of exposure contribute to thyroid dysfunction promoted by low-dose exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin in mice

Transcranial focused ultrasound modulates spiking, LFP, and BOLD activity in the primate thalamus

Far-infrared therapy and vascular access flow in hemodialysis patients with arteriovenous fistula or graft: a prospective minimal detectable change analysis

Towards an enzyme cascade synthesis of the bulk chemical acrylic acid

Single-dose administration of therapeutic divalent siRNA targeting MECP2 prevents lethality in an MECP2 duplication mouse model

Abstract MECP2 duplication syndrome (MDS) is a rare X-linked neurodevelopmental disorder caused by duplications of the dosage-sensitive methyl-CpG-binding protein 2 (MECP2) gene. Developing therapies for MDS is challenging due to the variability in MECP2 expression among patients and the risk of inducing Rett syndrome through excessive pharmacological intervention. Reducing dosage to optimize silencing often compromises durability and necessitates increased dosing frequency. We present here a series of fully chemically modified small interfering RNAs (siRNAs) designed for isoform-selective and total Mecp2 silencing. Among these, we identify six lead siRNA candidates across two chemical scaffolds, achieving targeted total Mecp2 expression reductions ranging from 25% to 75%, sustained for at least four months following a single administration. The efficacy and safety of human ortholog silencing are evaluated using a mouse model with ~8-fold human Mecp2 transgene expression. In this severe duplication model, a single dose of the total isoform-silencing siRNA rescues early mortality and select behavioral impairments. Overall, this study introduces preclinical candidates for the treatment of MDS. Furthermore, it establishes a target selection strategy applicable to other dosage-sensitive gene imbalances.

Dynamic catalytic interface driven three-step synergistic mechanism for boosting ammonia and hydroxylamine synthesis

Hardware acceleration of simulated annealing for constraint satisfaction problems

Abstract Simulated annealing (SA), a metaheuristic algorithm inspired by physical annealing processes, attempts to solve combinatorial optimization problems by performing a stochastic search that iteratively explores the solution space. Probabilistic solution evaluation allows the algorithm to escape local minima and progressively converge toward a global optimum, even within complex solution landscapes. In this work, we present the hardware acceleration of SA for spatial optimization within constrained environments, specifically targeting drone placement that maximizes area coverage while avoiding no-fly zones. Stochasticity is introduced through a true random number generator (TRNG) based on two-dimensional (2D) materials. The system energy is evaluated using a 2D logic circuit and the acceptance of candidate solutions is governed by a programmable 2D circuit with tunable threshold behavior. For a representative drone placement task, our hardware-based annealing accelerator circuit modules consume 43 nJ of energy per iteration and achieve an 1800-fold search acceleration relative to brute-force exploration of the solution space. This work also underscores the potential of 2D-material-enabled stochastic and programmable hardware for real-time constrained optimization.

Analysis of 14q12 microdeletions reveals novel regulatory loci for the neurodevelopmental disorder-related gene FOXG1

Vertical Through‑Bond Co─O─Mo Bridge Enables Dual‑Site Nonradical Selective Oxidation

ABSTRACT Selective oxidation via nonradical pathways is crucial for broad‐ranged catalytic applications, yet it remains difficult to construct catalytic interfaces that efficiently activate oxidants while stabilize reactive intermediates at solid–liquid boundary for driving nonradical reactions. Conventional planar or quasi‐planar interface‐engineering strategies mainly tune local coordination environments or macroscopic phase contacts, and fail to couple two dissimilar redox centers at the atomic scale. Here, we propose the construction of asymmetric Co─O─Mo bridges at a buried interface to enable the formation of a vertical through‐bond interface that preferentially catalyze nonradical reactions. Specifically, the bridging oxygen connects a CoOOH overlayer and a defect‐rich MoS 2 substrate along the surface‐normal direction, establishing a resting‐state dipolar polarization and inducing site‐specific charge redistribution to facilitate oxidant activation and stabilization while suppress solution‐phase radical chemistry. This vertical interface spatially organizes complementary nonradical functions to favor high‐valent Co(IV)═O and singlet oxygen generation. The resulting bridged catalyst shows high reactivity for oxidation of diverse organic micropollutants, superior tolerance to complex water matrices, and compatibility with flow‐through membrane operation. More broadly, this work establishes vertical through‐bond bridges as local catalytic units to couple structural asymmetry, electron polarization, and reactive‐intermediate confinement, providing a transferable design principle for establishing selective oxidation heterogeneous catalytic system.

Spatial multi-omics identifies early synaptic pruning and context-specific dopaminergic vulnerability in synucleinopathies

Abstract Parkinson’s disease (PD) is characterized by degeneration of dopaminergic neurons in the substantia nigra pars compacta, but the molecular events preceding neuronal loss remain unclear. Here, we combine spatial transcriptomics, spatial proteomics, and α-synuclein (αSyn) seed amplification assays to profile post-mortem midbrain tissue from controls, incidental Lewy body disease (iLBD), PD, Alzheimer’s disease (AD), and AD with Lewy body pathology (AD + LBP). We find that αSyn seeding activity correlates with dopaminergic neuron loss in PD-spectrum cases but not in AD-associated LBP, indicating disease-context dependent relationships between αSyn pathology and neurodegeneration. In iLBD, before overt substantia nigra Lewy pathology or detectable αSyn aggregation, we detect increased expression of the complement component C1QC together with loss of inhibitory synaptic markers. These findings support early complement-associated remodeling of inhibitory synapses as a potential pathogenic event preceding overt αSyn aggregation and neuronal degeneration in PD.

Induced Molecular Orientation Transition via Organic‐Inorganic Hybrid Networks in Thin‐Film Transistor‐Based Biosensors

ABSTRACT Molecular orientation transition is a key determinant of charge transport efficiency in thin‐film transistors (TFTs). Conventional strategies to induce such transitions often result in increased molecular disorder, which leads to device performance degradation. Herein, an organic‐inorganic hybrid network was proposed to modulate the structure‐performance relationship via the incorporation of specific inorganic metal oxides (e.g., In 2 O 3 ), leading to a marked enhancement in device and sensing performance by nearly 20‐fold. This phenomenon may be associated with a triple‐condition mechanistic framework involving strong interfacial adsorption, thermodynamic driving force, and abundant oxygen vacancies. The proposed triple‐condition mechanistic framework not only transforms molecular orientation from observation into a predictable rule for selecting inorganic additives in organic‐inorganic hybrid networks, but also establishes a practical route for improving biosensing performance through molecular orientation in life and health monitoring.

Quantum adiabatic transport in a quantum anomalous Hall insulator

Abstract An exceptional trait of the quantum Hall effect is quantum adiabatic transport, dissipationless quantized edge transport that is robust to bias voltages multiple orders of magnitude larger than any known relevant energy scale. This enables stable and highly sensitive measurements in quantum metrology at temperatures above 1 K. In contrast, prior experiments have shown that an electrical bias of the same order applied to the quantum anomalous Hall edge modes in magnetic topological insulators causes a breakdown of quantization, resulting from material limitations (electric field activates bulk transport). In this paper, to mitigate the effects of this electric field and study edge transport at a large electrical bias, we utilize electrochemical potential balancing. We find that electrical transport along the edge of a quantum anomalous Hall insulator is ubiquitously of dissipationless quantum adiabatic nature. In fact, we can verify that the adiabaticity holds at least up to an applied bias voltage of some 600 mV at 4.2 K, multiple orders of magnitude larger than any known energy scale associated with the quantum anomalous Hall state. This is a level of robustness on par with the conventional quantum Hall modes used in mainstream metrology.

Lanthanide Orbital Modulation Coupled With Entropy Increase Effect for Synergistically Enhanced Interfacial Stability and Ion Transport Kinetics in Halide Electrolytes

ABSTRACT The development of solid‐state electrolytes (SSEs) integrating high ionic conductivity and a wide electrochemical window constitutes a critical challenge for all‐solid‐state lithium batteries (ASSLBs). Herein, we propose a multication mixing strategy of lanthanide elements, which introduces configurational entropy increase effect and electronic structure regulation into the Li 3 YCl 6 , achieving simultaneous enhancement of ion transport and oxidation resistance. Combined theoretical and experimental analyses verify that the entropy increase–driven local structural distortions effectively reduce the energy barrier for Li + migration and optimize ion‐transport pathways. Concurrently, the unique electronic structure regulation of rare earth elements stabilizes the chemical environment of Cl − , significantly improving the intrinsic oxidation resistance. The full battery employing this optimized electrolyte demonstrates remarkable stability at 4.5 V, maintaining a capacity retention ratio of 74.3% after 800 cycles at 1 C rate. This research provides innovative insights into designing advanced SSEs through entropy increase effect and electronic structure design.

Computational methods toward ultrastable glasses

Ultrastable glasses, amorphous solids with exceptionally low-energy states and enhanced kinetic, thermodynamic, and mechanical stability, have long been a subject of intense experimental interest. Over the past decade, their computational realization has emerged as a major goal in condensed matter physics, as numerical methods can exploit unphysical moves to access deeply supercooled and nonequilibrium glassy states far beyond the reach of conventional cooling protocols, thereby providing key insights into the nature of the glass transition and amorphous states and enabling the design of mechanically robust glassy materials. In this review, we outline the key steps underlying the most effective algorithms developed across the field. For each approach, we discuss its efficiency, limitations, and physical interpretation. We finally present a comparative analysis of the stability achieved across these methods, with the aim of equipping both newcomers and experts with an intuitive and comprehensive understanding of the field’s current state and the opportunities it presents.

Ultra‐Low‐Threshold Laser Patterning of Graphene With a Modular Sulfonium Library for Programmable Work‐Function Engineering

ABSTRACT Achieving spatially resolved chemical functionalization on graphene lattices is essential for fabricating advanced two‐dimensional (2D) architectures. However, current covalent patterning strategies struggle to simultaneously minimize energy input for lattice preservation and offer the chemical versatility required for fine‐tuning the local doping state of the 2D lattice. Here, a modular diaryl‐sulfonium platform is developed for the ultra‐low‐threshold covalent patterning of monolayer graphene, further enabling substituent‐encoded pattern of local work‐function. Driven by a highly efficient, graphene‐mediated hot‐electron single‐electron transfer (SET) mechanism, this approach lowers activation barriers, enabling non‐destructive patterning with laser powers as low as 0.10 mW and irradiation time of a few seconds—orders of magnitude lower than conventional photon‐driven processes—thereby ensuring high pattern fidelity without thermal degradation. By incorporating a library of six chemically distinct σ‐bound substituents (including phenyl, fluorophenyl, trifluoroethyl, vinyl, phenylthiophenyl, and bromoethyl) onto a unified sulfonium scaffold, precise control over local work‐function can be achieved. Kelvin Probe Force Microscopy (KPFM) reveals a continuous, chemically tunable spectrum of surface potential shifts (ΔCPD from ∼30 to ∼300 mV). Combined with exceptional ambient stability and thermal erasability, this work offers a robust, energy‐efficient paradigm for chemically encoding reconfigurable 2D electronic landscapes.

The Cahn–Hilliard residuum and its implications for critical-point wetting at solid solution surfaces

As part of their seminal 1958 analysis of nonuniform solutions, Cahn and Hilliard [J. Chem. Phys. 28, 258–267 (1958)] identified the Laplacian of the composition field as the key contribution to the excess free energy in solids with a conserved network of discrete atomic sites. Integration by parts converted to the now familiar gradient-square form underlying phase-field simulations and studies of critical-point wetting. The residuum from the integration by parts has since been ignored. Here, we examine its implications using critical-point wetting at the surface of an Ising-type solid solution for a representative case. As a benchmark, atomistic Monte Carlo simulation shows a continuous increase in wetting-layer thickness up to the bulk critical temperature. In contrast, the classical gradient-square continuum model predicts a first-order wetting transition. A more realistic Laplacian-based continuum formulation does not readily admit physically meaningful minimization by standard variational methods. As a discrete approach, a plane-by-plane model with an excess energy based on a second-difference (curvature) operator yields solutions consistent with the benchmark. Summation by parts transforms this operator into a first-difference- (gradient-) square form, and neglect of the residual term again leads to an incorrect first-order transition. Thus, the choice between curvature and gradient-square formulations alters the predicted character—first-order transition or continuous evolution in layer thickness—of the wetting, underscoring the fundamental importance of this choice.

Benchmarking semiempirical quantum chemical methods on liquid water

Stimulated by the renewed interest and recent developments in semiempirical quantum chemical (SQC) methods for noncovalent interactions, we examine the properties of liquid water under ambient conditions by means of molecular dynamics (MD) simulations, both with the conventional neglect of diatomic differential overlap-type methods, e.g., AM1 and PM6, and with DFTB-type (density-functional tight-binding) methods, e.g., DFTB2 and GFN-xTB (Geometry-Frequency-Noncovalent eXtended Tight-Binding). Besides the original parameter sets, some specifically reparameterized SQC methods (denoted as AM1-W, PM6-fm, and DFTB2-iBi) targeting various smaller water systems ranging from molecular clusters to bulk are considered as well. The quality of these different SQC methods for describing liquid water properties under ambient conditions is assessed by comparison with well-established experimental data and also with BLYP-D3 density functional theory-based ab initio MD simulations. Our analyses reveal that static and dynamic properties of bulk water are poorly described by all considered SQC methods with the original parameters, regardless of the underlying theoretical models, with most of the methods suffering from too weak hydrogen bonds and hence predicting a far too fluid water with highly distorted hydrogen bond kinetics. Meanwhile, the reparameterized force-matched PM6-fm method is shown to be able to quantitatively reproduce the static and dynamic features of liquid water and thus can be used as a computationally efficient alternative to electronic structure-based MD simulations for liquid water that requires extended length and time scales. DFTB2-iBi predicts a slightly overstructured water with reduced fluidity, whereas AM1-W gives an amorphous ice-like structure for water under ambient conditions.

Can Elastomers Combine Stiffness, Toughness and Fatigue Resistance?

ABSTRACT Have you ever tried to wrap a stack of cards with a new rubber band and then repeated the same task with an old one? While new rubber bands are elastic and can easily encircle the stack, older rubber bands tend to lose elasticity, become brittle, and ultimately rupture. Rubber is a sub‐class of elastomers, which are solvent‐free polymeric networks. Above their glass transition temperature, T g , elastomers are characterized by a high stretchability. Yet, many homogeneous single network elastomers display a low mechanical strength and limited durability. Given their significance, for example for protective sport equipment, damping systems, and in soft robotics, extensive efforts have been dedicated to developing elastomers that combine stiffness, toughness, and durability. The ideal elastomer for soft robotics, wearables, and biomedical applications would possess spatially variable mechanical properties, enabling controlled deformation, sustaining considerable loads, efficiently damp energy, and be fatigue resistant. However, current elastomer formulations cannot simultaneously achieve all of these attributes. This review summarizes the current understanding of the structure‐mechanical property relationship of elastomers and highlights recent strategies that overcome certain trade‐offs of the mechanical properties of elastomers by locally varying their composition.

Phase fluctuations in a confined fluid

Fluid phase equilibrium depends on the external constraints imposed on a system. In a closed system with fixed volume, depending on the average density, a vapor bubble may be stable, metastable, or unstable, with respect to the homogeneous liquid phase. In the case where the bubble is metastable, we study its lifetime, i.e., the average waiting time needed to observe bubble collapse, and the corresponding lifetime of the homogeneous liquid. For the smallest systems, we predict the possibility to observe phase flipping, when the fluid oscillates between states with and without bubble. We provide an example of phase flipping in a simulation of a Lennard-Jones fluid.