Advanced Science最新文献

This review delineates a transformative strategy in advanced materials: the integration of Ti₃C₂T_x MXene with carbon fibers (CFs) to forge a new class of multifunctional structural composites. This integration strategy signifies a paradigm shift from simple structural components to multifunctional material systems. Moving beyond conventional interface enhancement, precise modification techniques such as self-assembly, electrophoretic deposition, chemical grafting, and blending-spinning synergistically combine the outstanding mechanical properties of CFs with the diverse electrical, thermal, and optical characteristics of Ti₃C₂T_x MXene. This synergistic coupling effectively overcomes the long-standing limitations of CFs, including surface inertness and functional singularity. The review systematically examines the resulting performance improvements across a range of frontier applications, including interface reinforcement, electromagnetic shielding, battery energy storage, smart sensing, and thermal management. However, achieving industrial applications still depends on overcoming key challenges related to Ti₃C₂T_x MXene stability, scalable processing, and multifunctional optimization. This review not only summarizes current research progress but also outlines a roadmap for future studies, emphasizing sustainable processing, interfacial nanoengineering, and the rational design of next-generation structure-function-integrated composites.

Despite remarkable advances in sequencing technologies and automated genome assembly algorithms, manual gap-filling remains indispensable for achieving telomere-to-telomere (T2T) genome assemblies, a process that can take weeks or even months. Additionally, these tasks require advanced bioinformatics expertise, thereby excluding many biologists from direct participation in T2T genome projects. This severely restricts the ability to construct T2T genomes for larger populations and a wider range of species. To overcome these challenges, we developed GapSuite, an integrated auxiliary software toolbox that includes two complementary tools, Gap-Aid and Gap-Graph, which facilitate gap-filling through sequence-extension-based and assembly-graph-based strategies, respectively. The two tools empower users with limited computational expertise to efficiently perform gap closure on personal computers with just mouse clicks, resulting in a fully assembled genome. GapSuite incorporates several technical innovations to achieve key functions and improve both time and space efficiency. Their effectiveness was validated using Arabidopsis thaliana, rice and human genomes as well as simulated diploid and polyploid genomes. As case studies, we used the tools to construct, to the best of our knowledge, the first T2T genome of rice 9311, a model variety of indica rice, and to fill part of the remaining gaps in a recently published gapless poplar genome.

Li-metal anodes (LMAs) have attracted significant interest in high-energy-density Li-metal batteries (LMBs) due to their high theoretical capacity and low electrochemical potential. Nonetheless, the instability and host-less nature of Li impede the development of stable LMBs. To address the challenge, metals and metal compounds have been demonstrated to exhibit effective lithiophilicity in guiding uniform Li deposition. Concurrently, hollow-structured nanomaterials have emerged as advanced Li hosts for LMAs. This review discusses the application of hollow Li hosts featuring metals or metal compounds in LMAs, investigates the in situ and ex situ characterizations of Li deposition behavior in hollow Li hosts, elucidates the mechanisms of regulating Li deposition by metals or metal compounds, and explores the representative instances of hollow Li hosts containing metal or metal compound sites. Finally, this review outlines some future prospects for the advancement of hollow Li hosts integrated with metals or metal compounds.

Understanding the relationship between protein sequence and function remains a longstanding challenge in bioinformatics, and to date the lion's share of related tools parse proteins at the domain or motif levels. Here, we define "protein words" as an alternative to "motif" for studying proteins and functional prediction applications. We first developed an unsupervised tool we term Protein Wordwise, which parses analyte protein sequences into protein words by analyzing attention matrices from a protein language model (PLM) through a community detection algorithm. We then developed a supervised sequence-function prediction model called Word2Function, for mapping protein words to GO terms through feature importance analysis. We compared the prediction performance of our protein word-based toolkit with a motif-based method (PROSITE) for multiple protein function datasets. We also assembled a functionally diverse data resource we term PWNet to support evaluation of protein words for predicting functional residues across 10 tasks (e.g., diverse biomolecular binding, catalysis, and ion-channel activity). Our toolkit outperforms PROSITE in all the examined datasets and tasks. By abandoning domains and instead using attention matrices from a PLM for automatic, systematic, and annotation-agnostic parsing of proteins, our toolkit both outperforms currently available tools for functional annotations at the residue and whole-protein levels and suggests innovative forms of protein analysis well-suited to the post-AlphaFold era of biochemistry.

Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for Alzheimer's disease (AD). However, it is known that other pathways independent of APOE also play a role in AD. Disentangling APOE-dependent and independent effects is instrumental for understanding the biology of AD. We conducted an APOE-stratified multi-omic analysis in multiple large datasets to identify AD-associated plasma proteins and metabolites. More than 64% of the identified proteins were not found in non-APOE stratified studies, and 17% of the proteins showed APOE-specific trends. Mitochondrial dysfunction was associated in AD independently of APOE and was accompanied by disruptions in glucose and lipid metabolism and cell death and increased in inflammatory signaling activation. Lipid upregulation was found in AD cases when compared with controls with the same APOE genotype, indicating that additional factors beyond APOE affect lipid regulation and AD risk. These findings may be informative in guiding the development of effective medications for AD.

Alcohol use disorder (AUD) leads to cognitive impairment dependent on prefrontal cortex (PFC) dysfunction, yet the underlying cellular and molecular mechanisms, particularly the role of microglia, remain poorly understood. Through re-analysis of single-cell RNA sequencing data from AUD patients, we identified aberrant activation of lipid metabolic pathways in microglia and pinpointed acyl-CoA synthetase long-chain family member 1 (ACSL1) as a central regulator. In animal and cellular models, chronic ethanol exposure induced ACSL1 upregulation, triggering lipid droplet accumulation, neuroinflammatory activation, and aberrant microglia-neuron interactions mediated via PTPRM signaling. Pharmacological inhibition of ACSL1 reversed these pathological phenotypes. We further developed a dual-targeted lipid nanoparticle system for microglia-specific ACSL1 silencing, which effectively ameliorated ethanol-induced cognitive deficits in mice. Our study unveils ACSL1-mediated lipoimmunity reprogramming of microglia as a core mechanism underlying cognitive impairment in AUD and proposes a novel targeted therapeutic strategy.

Functional structures that combine thermal protection with load-bearing capabilities represent an effective solution to hypersonic thermal-protection challenges. Here, we propose a Janus-like bio-inspired strategy for integrally 3D-printed bimetallic metamaterials. Inspired by shell bilayers, a heat-resistant AlSiFeMnNiMg alloy and a SiC-reinforced AlSi10Mg are arranged as an architected pair and fabricated via dual-hopper selective laser melting, with SiC volume fractions of 0, 4, and 8 vol%. In situ SEM tensile tests at 25°C and 250°C show that damage is confined to a narrow transition zone. Once one side softens, the bimetallic architecture redirects load to the other, forming non-percolating high-stress paths and stabilizing the plateau response. Quasi-static compression of Gyroid TPMS lattices with different SiC contents maps the composition-temperature space. Across temperatures, structures with 4 vol% SiC improve specific energy absorption by 11.72% and 18.67% in room temperature and by 10.28% and 18.8% in 250°C, achieving synergistic mechanical improvement and a stable energy-absorbing plateau under extreme environments. Relative to 0 and 8 vol%, where modulus mismatch precipitates premature localized collapse, 4 vol% SiC promotes a distributed shear-band network that delays failure and elevates load capacity. This work provides a practical pathway toward thermally protective and load-bearing integrated components for aerospace applications.

The broadband electromagnetic wave absorption (EWA) of soft magnetic alloys (SMAs) is severely constrained by the rapid decay of their magnetic loss at gigahertz frequencies. To address this issue, an intergranular coupling strategy guided by the magnetic exchange length (L_ex) is proposed in this study. Doping with Cu systematically increases L_ex in SMAs from 12.7 nm to 19.1 nm, thereby enhancing the collective precession of magnetic moments over a larger spatial range. This Cu doping concurrently reduces the effective magnetic anisotropy (K_eff) from 9.2 to 8.6 kJ m^-3 and increases the magnetic exchange strength by 25%. These coordinated changes effectively shift the resonance peak to 12.0 GHz and amplify the magnetic loss. As a result, the optimized alloy achieves an effective absorption bandwidth (EAB) of 8.1 GHz at a minimal thickness of 1.8 mm, representing a 47.1% improvement over its Cu-free counterpart. This work pioneers the use of L_ex-driven mechanisms for regulating magnetic loss and establishes a fundamental framework for enhancing the broadband EWA performance of SMAs through targeted resonance modulation.

Magnetoelectric materials, which generate electric fields in response to alternating magnetic stimulation, are increasingly recognized for their applications in neuromodulation, tissue engineering, wireless drug delivery, and cancer treatment. This study addresses the cytotoxicity concerns associated with heavy metals in traditional magnetoelectric composites by introducing a heat-mediated magnetoelectric approach utilizing biocompatible iron oxide nanoparticles and pyroelectric polymers, thereby enhancing biomedical safety. The nanoparticles were synthesized with controlled size and shape via thermal decomposition of iron oleate, employing an in situ temperature labeling technique that simplifies the synthesis process and ensures uniform particle formation. These nanoparticles, optimized for high heating efficiency, were combined with the pyroelectric polymer P(VDF-TrFE) to create composite films that exhibit a heat-mediated magnetoelectric effect. This effect involves an alternating magnetic field heating the nanoparticles, leading to reversible material depolarization and the generation of a pyroelectric current. We explored the magnetopyroelectric effect on cell differentiation, demonstrating excellent biocompatibility with neural progenitor cells and significant enhancement in neuronal differentiation, attributed to the synergistic effects of heat and electricity. The pro-differentiation mechanism of magnetopyroelectric stimulation involves phosphatidylinositol 3 kinase AKT pathway and calcium signaling. This heat-mediated magnetoelectric approach not only presents a potential for applications such as neuronal repair and targeted drug delivery but also provides a safer and more versatile alternative to conventional magnetoelectric materials.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two severe diseases sharing similar genetic, pathological, and clinical features, including TDP-43 pathology. However, differences in molecular changes between ALS and FTD remain elusive. Here, integrating large sets of bulk and single-nucleus RNA-seq from ALS/FTD patients revealed expression and splicing changes indicating more severe oligodendrocyte damage in ALS than FTD, and more significant neuron loss in FTD. Specifically, we identified 31 oligodendrocyte-specific and 507 neuron-specific aberrant splicing junctions as potential biomarkers with robust classification performance, and experimentally validated a novel target in patient tissues. Moreover, we found that abnormally spliced transcripts produced de novo peptides in patients' cerebrospinal fluids. Importantly, we further identified the targets of TDP-43 in glial cells and decoded the differential RNA-binding protein (RBP) contexts of TDP-43-regulated aberrant splicing. These findings uncover that ALS and FTD patients have distinct dysfunctional cell populations harboring specific aberrant splicing signatures, suggesting varying cellular impacts and providing potential biomarkers and insights into molecular mechanisms underlying ALS/FTD.