Qiao-Zhi Li

Osteoporosis occurs due to the synergistic effect of increased bone resorption and decreased bone formation. However, a therapeutic approach that can simultaneously inhibit osteoclastic resorption and promote osteogenic activity directly is still lacking. Growing evidence demonstrates the I-kappaB kinase beta (IKKβ)-mediated NF-κB activation is a common crucial regulator in differentiation of both osteoclasts and osteoblasts. Herein, we screened a peptide-coated gold nanocluster (GA) and further disclosed that the optimized GA works like an antibody to block IKKβ activation well. The GA can simultaneously inhibit IKKβ-mediated osteoclastogenesis and enhances osteoblastic mineralization in vitro and effectively ameliorates osteoporosis in a preclinical model in a safe manner. Compared with first-line antiresorptive alendronate (ALN, suppress bone resorption only), GA significantly promotes bone formation and improves the quality of bone microarchitecture in vivo. These data suggest that antibody-like GAs hold great potential in osteoporosis therapy.

The century‐old challenge of isotope separation might be addressed by conductive metal–organic framework (cMOF) thin films featuring ordered nanopores, designable charge‐transport pathways, and potential flexibility. However, resolving and amplifying the microscopic kinetic differences between water isotopologues within such confined spaces remains nontrivial. In this work, proton‐ and electron‐coupled two‐dimensional π‐conjugated cMOF thin films (Cu ₁ TPB _0.1 − x C) are fabricated through controllable layer‐by‐layer growth with oriented narrow pores and flexibility. Correlating electrical‐ and mass‐transduced gas‐sensor technologies, the subtle differences in the interactions of H ₂ O and D ₂ O with the framework were identified, revealing a complex multistage mass transport. Comparison of cMOFs with different pore sizes shows that this identification originates from distinct conduction mechanisms. Notably, the Cu ₁ TPB _0.1 − x C thin film with a strong space‐confined effect exhibits a complex multistage electrical response due to its unique proton–electron‐coupled conduction characteristics, thereby enabling further differentiation of the transport processes of H ₂ O and D ₂ O on the outer surface and within the confined spaces. The oriented cMOF films therefore provide a real‐time platform for resolving and amplifying subtle isotope‐dependent transport dynamics in confined pores, offering mechanistic guidance for the design of porous materials with controlled water‐isotopologue transport.

The century‐old challenge of isotope separation might be addressed by conductive metal–organic framework (cMOF) thin films featuring ordered nanopores, designable charge‐transport pathways, and potential flexibility. However, resolving and amplifying the microscopic kinetic differences between water isotopologues within such confined spaces remains nontrivial. In this work, proton‐ and electron‐coupled two‐dimensional π‐conjugated cMOF thin films (Cu ₁ TPB _0.1 − x C) are fabricated through controllable layer‐by‐layer growth with oriented narrow pores and flexibility. Correlating electrical‐ and mass‐transduced gas‐sensor technologies, the subtle differences in the interactions of H ₂ O and D ₂ O with the framework were identified, revealing a complex multistage mass transport. Comparison of cMOFs with different pore sizes shows that this identification originates from distinct conduction mechanisms. Notably, the Cu ₁ TPB _0.1 − x C thin film with a strong space‐confined effect exhibits a complex multistage electrical response due to its unique proton–electron‐coupled conduction characteristics, thereby enabling further differentiation of the transport processes of H ₂ O and D ₂ O on the outer surface and within the confined spaces. The oriented cMOF films therefore provide a real‐time platform for resolving and amplifying subtle isotope‐dependent transport dynamics in confined pores, offering mechanistic guidance for the design of porous materials with controlled water‐isotopologue transport.

The widespread adoption of aramid dielectric paper as core insulation in advanced motor systems is undermined by its intrinsically low thermal conductivity (λ), which promotes localized hotspot formation and precipitates insulation failure under severe thermoelectrical coupling stresses. However, current mainstream solutions face a restrictive trade-off between λ and other essential properties, presenting a persistent challenge for the design of thermoconductive aramid papers. Herein, we report a multifunctional aramid composite dielectric paper constructed from one-dimensional (1D) aramid nanofibers (ANFs) as the structural scaffold, synergistically integrated with hydroxyl-functionalized 1D boron nitride nanotubes (BNNTs) and 2D boron nitride nanosheets (BNNSs) as thermally conductive fillers. The composite paper features a hierarchically ordered self-assembled architecture that establishes an unobstructed 3D phonon transport network, wherein BNNTs serve as spatial bridges interconnecting isolated BNNSs. This structural synergy, coupled with robust interfacial bonding between ANFs and BNNTs as well as BNNSs, concurrently elevates the in-plane λ to 15.71 W·m–1·K–1 and the tensile strength to 283.36 MPa for the composite paper, representing 9.64-fold and 1.32-fold improvements over pristine ANF paper, respectively. Moreover, the nacre-inspired microstructure endows the composite paper with an ultrahigh breakdown strength of 349.06 kV/mm, wherein the abundant deep traps at the ANF-filler interfaces critically suppress charge carrier migration and prevent premature electrical breakdown. These multidimensional blocks design strategy offers a promising avenue for multifunctional dielectric materials tailored to the insulation systems of next-generation electrical and power equipment.

Nanozymes, defined as nanomaterials exhibiting intrinsic enzyme-like catalytic properties, represent a rapidly expanding interdisciplinary frontier. Since the initial discovery of peroxidase-like nanozymes, a wide variety of nanomaterials have demonstrated diverse enzyme-like activities. In recent years, oxidase (OXD)-like nanozymes have demonstrated considerable potential, particularly in applications such as cancer therapy, biosensing, environmental monitoring, antibacterial activity, food safety, industrial catalysis, energy storage, and so on. This Perspective systematically summarizes recent progress in OXD-like nanozymes, including metals, metal oxides, carbon materials, metal-organic frameworks, and single/double-atom catalysts. Following the introduction of the characteristics, advantages, and applications of OXD-like nanozymes, this review discusses the catalytic mechanisms underlying OXD-like activity, specifically the four-electron (4e^-) and two-electron (2e^-) pathways for several important substrates, including 3,3',5,5'-tetramethylbenzidine (TMB), glucose (Glu), ascorbic acid (AA), nicotinamide adenine dinucleotide (NADH), uric acid (UA), and glutathione (GSH). It further examines the application of first-principles calculations and machine learning (ML) in predicting nanozyme activity and guiding rational design. Current challenges in mechanistic elucidation and computational model optimization are also addressed, along with future research perspectives. By integrating experimental findings and theoretical studies, this review aims to provide guidelines for the future development and application of OXD-like nanozymes.

Nanoparticles (NPs) such as engineered inorganic NPs (metals, metal oxides, carbon materials, etc.) can induce cytotoxicity in normal biological systems when used for disease treatment or when exposed to the environment, which has raised widespread concerns about their safety in biomedicine, environmental chemistry, and other application fields. Therefore, developing efficient strategies for the hazard and risk assessment of NPs is extremely important to ensure their safety and sustainable development in above applications. Herein, we provide a systematic and comprehensive review that includes the following sections: (i) mechanisms and influencing factors of nanotoxicity, (ii) the classical statistical cytotoxicity prediction models such as nano-quantitative structure–activity relationship (nanoQSAR), physiologically based pharmacokinetic (PBPK), and meta-analysis (MA) models, (iii) the ML-accelerated development of the above three types of models, and (iv) some important nanotoxicity databases. The ML-accelerated nanoQSAR, PBPK, and MA models are mainly focused, in which the ML algorithms, advantages, and schemes for model development are described, and also the prediction performance and key features that influence the cytotoxicity for the developed models are discussed in detail. In addition, future opportunities and challenges in promoting the development of highly efficient, robust, and interpretable ML models for predicting the cytotoxicity of NPs are also highlighted.