ResearchPub Date : 2025-08-26eCollection Date: 2025-01-01DOI: 10.34133/research.0801
Chuanming Zong
{"title":"The Mathematical Foundation of Post-Quantum Cryptography.","authors":"Chuanming Zong","doi":"10.34133/research.0801","DOIUrl":"10.34133/research.0801","url":null,"abstract":"<p><p>In 1994, P. Shor discovered quantum algorithms that can break both the RSA cryptosystem and the ElGamal cryptosystem. In 2007, a Canadian company D-Wave demonstrated the first quantum computer. These events and quick further developments have brought a crisis to secret communication. In 2022, the National Institute of Standards and Technology (NIST) announced 4 candidates-CRYSTALS-Kyber, CRYSTALS-Dilithium, Falcon, and Sphincs+-for post-quantum cryptography standards. The first 3 are based on lattice theory and the last on Hash functions. In 2024, NIST announced 3 standards: FIPS 203 based on CRYSTALS-Kyber, FIPS 204 based on CRYSTALS-Dilithium, and FIPS 205 based on Sphincs+. The fourth standard based on Falcon is on the way. It is well known that the security of the lattice-based cryptosystems relies on the hardness of the shortest vector problem (SVP), the closest vector problem (CVP), and their generalizations. In fact, the SVP is a ball packing problem and the CVP is a ball covering problem. Furthermore, both SVP and CVP are equivalent to arithmetic problems for positive definite quadratic forms. There are several books and survey papers dealing with the computational complexity of the lattice-based cryptography for classical computers. However, there is no review article to demonstrate the mathematical foundation of the complexity theory. This paper will briefly introduce post-quantum cryptography and demonstrate its mathematical roots in ball packing, ball covering, and positive definite quadratic forms.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0801"},"PeriodicalIF":10.7,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12380341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of Critical States in Complex Biological Systems Using Cell-Specific Causal Network Entropy.","authors":"Jiayuan Zhong, Ziyi Huang, Jianqiang Qiu, Fei Ling, Pei Chen, Rui Liu","doi":"10.34133/research.0852","DOIUrl":"10.34133/research.0852","url":null,"abstract":"<p><p>Abrupt shifts, referred to as critical transitions, are frequently observed in complex biological systems, characterized by marked qualitative changes occurring from one stable state to another through a pre-transitional/critical state. Pinpointing such critical states, along with the signaling molecules, can provide valuable insights into the fundamental mechanisms of intricate biological processes. However, the identification and early warning of the critical state remains a challenge, particularly in model-free cases with high-dimensional single-cell data, where traditional statistical methods often prove inadequate due to the inherent sparsity, noise, and heterogeneity of the data. In this study, we propose a novel quantitative method, cell-specific causal network entropy (CCNE), to infer the specific causal network for each cell and quantify dynamic causal changes, thereby enabling the identification of critical states in complex biological processes at the single-cell level. We validated the accuracy and effectiveness of the proposed approach through numerical simulations and 5 distinct real-world single-cell datasets. Compared to existing methods for detecting critical states, the proposed CCNE exhibits enhanced effectiveness in identifying critical transition signals. Moreover, CCNE score is a computational tool for distinguishing temporal changes in cellular heterogeneity and demonstrates satisfactory performance in clustering cells over time. In addition, the reliability of CCNE is further emphasized through the functional enrichment and pathway analysis of signaling molecules.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0852"},"PeriodicalIF":10.7,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12379065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-25eCollection Date: 2025-01-01DOI: 10.34133/research.0846
Tianyu Meng, Yufei Zhang, Shoupeng Fu, Shaohua Ma
{"title":"Gpr35 Expression Mitigates Neuroinflammation and Enriches Gut <i>Lactobacillus</i> to Relieve Parkinson's Disease.","authors":"Tianyu Meng, Yufei Zhang, Shoupeng Fu, Shaohua Ma","doi":"10.34133/research.0846","DOIUrl":"10.34133/research.0846","url":null,"abstract":"<p><p>Parkinson's disease (PD) is associated with gut-brain axis and gut microbiota alterations, but the functioning mechanism remains to be elucidated. In this study, we identified G protein-coupled receptor 35 (Gpr35) as a key regulator for the gut-brain association under the PD context. It investigated the impact of Gpr35 deficiency on motor function, neuroinflammation, and dopaminergic neurodegeneration, using the Gpr35 knockout (Gpr35<sup>-/-</sup>) and wild-type (WT) mice in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD model, and Gpr35 up-/down-regulation on reverse neuroinflammation, oxidative stress, and neuronal apoptosis using Gpr35 agonist kynurenic acid (KYNA) and small interfering RNA in microglial and dopaminergic cell models. It was confirmed that Gpr35 may prevent PD by modulating neuroinflammation and gut microbiota and metabolite composition, specifically through enriching <i>Lactobacillus</i>, and substantially regulating tyrosine metabolism, neuroactive ligand-receptor interaction, and tryptophan metabolism pathways, thereby inhibiting the progression of PD. Our findings highlight the potential of targeting Gpr35 to influence both the gut microbiota and central nervous system, offering new insights into the treatment of PD.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0846"},"PeriodicalIF":10.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12376290/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Lignin Unlocks Stealth Carbon Sinks in Cold Seeps via Microbial Enzymatic Gatekeeping.","authors":"Jialing Li, Jingchun Feng, Pandeng Wang, Mengzhuo Zhu, Yongji Huang, Ying Wu, Junning Fan, Junlin Hu, Xiyang Dong, Yingli Zhou, Xuanyu Tao, Si Zhang","doi":"10.34133/research.0848","DOIUrl":"10.34133/research.0848","url":null,"abstract":"<p><p>Cold seep ecosystems serve as critical hubs in marine carbon cycling through methane emissions and organic matter processing. While terrestrial lignin constitutes a major fraction of persistent organic carbon in cold seep sediments, its microbial transformation pathways in deep-sea cold seep environments remain unexplored. Here, we present the first comprehensive analysis of lignin distribution across sediment horizons at the Haima cold seep, coupled with a multi-omics investigation of microbial lignin metabolism. Laboratory enrichment of sediment communities employing lignin as the exclusive carbon substrate revealed substantial microbial community restructuring dominated by <i>Burkholderiales</i>, <i>Pseudomonadales</i>, and <i>Rhizobiales</i> lineages. Integrated omics resolved 2-tiered metabolic cascades: (a) enzymatic depolymerization via dyP-type peroxidases and LigEFG-mediated β-aryl ether cleavage, targeting syringyl and diarylpropane subunits; (b) funneling of aromatic intermediates through 4,5-/3,4-PDOG (protocatechuate dioxygenase) pathways into central carbon metabolism. Although direct methanogenesis was undetected, methylotrophic potential was evidenced through methane cycle gene expression patterns by lignin decomposers. Phylogenetic surveys further demonstrated the global prevalence of lignin decomposers across 12 major cold seep systems. These decomposers showed marked divergence in enzymatic repertoires compared to degraders from other ecosystems. Our findings establish 3 paradigm shifts: (a) The turnover rates of terrestrial organic carbon are likely underestimated in deep-sea ecosystems; (b) microbial consortia employ combinatorial enzymatic strategies distinct from terrestrial decomposition regimes; (c) methyl shunting from lignin breakdown primes methanogenic precursors, revealing cryptic linkages between refractory carbon cycling and greenhouse gas reservoirs.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0848"},"PeriodicalIF":10.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12377529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-25eCollection Date: 2025-01-01DOI: 10.34133/research.0837
Manyi Yang, Duo Zhang, Xinyan Wang, BoWen Li, Linfeng Zhang, Weinan E, Tong Zhu, Han Wang
{"title":"Ab Initio Accuracy Neural Network Potential for Drug-Like Molecules.","authors":"Manyi Yang, Duo Zhang, Xinyan Wang, BoWen Li, Linfeng Zhang, Weinan E, Tong Zhu, Han Wang","doi":"10.34133/research.0837","DOIUrl":"10.34133/research.0837","url":null,"abstract":"<p><p>The advent of machine learning (ML) in computational chemistry heralds a transformative approach to one of the quintessential challenges in computer-aided drug design (CADD): the accurate and cost-effective calculation of atomic interactions. By leveraging a neural network (NN) potential, we address this balance and push the boundaries of the NN potential's representational capacity. Our work details the development of a robust general-purpose NN potential, architected on the framework of DPA-2, a deep learning potential with attention, which demonstrates remarkable fidelity in replicating the interatomic potential energy surface for drug-like molecules comprising 8 critical chemical elements: H, C, N, O, F, S, Cl, and P. We employed state-of-the-art molecular dynamic (MD) techniques, including temperature acceleration and enhanced sampling, to construct a comprehensive dataset to ensure exhaustive coverage of relevant configurational spaces. Our rigorous testing protocols, including torsion scanning, structure relaxation, and high-temperature MD simulations across various organic molecules, have culminated in an NN model that achieves chemical precision commensurate with the highly regarded density functional theory model while substantially outstripping the accuracy of prevalent semi-empirical methods. This study presents a leap forward in the predictive modeling of molecular interactions, offering extensive applications in drug development and beyond.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0837"},"PeriodicalIF":10.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12377527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Targeting the ANXA8-SP1-PPA1 Axis to Modulate TCA Cycle and Matrix Deposition in Diffuse-Type Gastric Cancer.","authors":"Yuxia Wu, Xiangyan Jiang, Huiguo Qing, Yansong Hou, Yong Ma, Tao Wang, Keshen Wang, Long Qin, Weiwen Cai, Zongrui Xing, Bin Zhao, Qichen He, Wenbo Liu, Tian Wang, Haonan Sun, Xingshuo Zhao, Zuoyi Jiao, Zeyuan Yu","doi":"10.34133/research.0838","DOIUrl":"10.34133/research.0838","url":null,"abstract":"<p><p>Diffuse-type gastric cancer (DGC) is an aggressive tumor type characterized by a dense extracellular matrix (ECM). Metabolic reprogramming, a key oncogenic factor driving tumor progression, is closely linked to ECM deposition, although the regulatory mechanisms remain poorly understood. In this study, we integrated single-cell sequencing, proteomics, metabolomics, and large-scale clinical data to identify the metabolic signature of DGC. We found that the tricarboxylic acid (TCA) cycle is suppressed in DGC, which correlates with the formation of a dense ECM. Annexin A8 (ANXA8) was identified as a critical regulator that inhibits the TCA cycle in DGC and is positively associated with matrix formation. Mechanistically, ANXA8 interacts with SP1 to promote the transcription of pyrophosphatase 1, thereby suppressing the TCA cycle, activating cancer-associated fibroblasts, and facilitating aberrant ECM deposition. Deletion of ANXA8 suppresses malignant phenotypes and shows synergistic effects with the chemotherapeutic agent 5-fluorouracil (5-FU). Large-scale clinical data further confirmed the correlation between ANXA8 expression and both gastric cancer progression and 5-FU therapeutic efficacy. High-throughput organoid screening identified UNC2025 as a selective ANXA8 inhibitor. Targeting ANXA8 with UNC2025 restores TCA cycle activity and inhibits ECM deposition in DGC, enhancing the therapeutic effects of 5-FU in patient-derived xenografts and organoids. Furthermore, a polyphenol-based UNC2025 nanodelivery system improved the efficacy of this combination therapy. In summary, this study elucidates how ANXA8-mediated suppression of the TCA cycle promotes dense ECM formation and malignant progression in DGC, highlighting the therapeutic potential of targeting ANXA8 in DGC treatment.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0838"},"PeriodicalIF":10.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12377485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-25eCollection Date: 2025-01-01DOI: 10.34133/research.0833
Yuanyuan Hu, Ning Chen, Hancheng Zhang, Yue Hou, Pengfei Liu
{"title":"RoadDiffBox: Automatic Road Distress Diagnosis through Controlled Image Generation and Semi-Supervised Learning.","authors":"Yuanyuan Hu, Ning Chen, Hancheng Zhang, Yue Hou, Pengfei Liu","doi":"10.34133/research.0833","DOIUrl":"10.34133/research.0833","url":null,"abstract":"<p><p>During the designed service life, road infrastructures will bear repeated loading conditions from vehicle weights and environmental conditions, resulting in the inevitable occurrence of road distresses including cracks, potholes, etc. The traditional inspection methods by transportation engineers are normally costly and labor-intensive. In recent years, artificial intelligence (AI)-based road distress detection methods have been widely used as convenient and automated approaches, while the AI-based methods heavily depend on a large amount of high-quality images, limiting the real engineering applications. To address the issues, this study introduces RoadDiffBox, a novel framework employing controlled image generation and semi-supervised learning. The framework addresses dataset imbalances through class control and accelerates image generation by utilizing the denoising diffusion implicit model's reverse process sampling method, while employing knowledge distillation techniques optimized for resource-constrained mobile devices. It generates diverse and high-quality road distress images with automatic bounding box annotations, substantially reducing manual labeling requirements. Test results show that RoadDiffBox demonstrates strong generalizability across geographic regions (Germany, China, and India) and shows cross-domain potential in medical imaging applications. Performance evaluations demonstrate RoadDiffBox's effectiveness, with classification models achieving an F1-score of 0.95 and detection models reaching a mean average precision (mAP@50) of 0.95 and an F1-score of 0.91 in controlled settings, while maintaining robust performance (an F1-score of 0.86 and a mAP@50 of 0.91) during on-site testing in real-world conditions. On server-class hardware, the model achieves generation times as low as 0.18 s per image. It is discovered that RoadDiffBox can serve as a scalable and efficient solution for real-time road maintenance with limited datasets.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0833"},"PeriodicalIF":10.7,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12376291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-21eCollection Date: 2025-01-01DOI: 10.34133/research.0841
Yuening Wang, Xiangyu Meng, Wenxiong Shi, Yujiao Xie, Aochi Liu, Lei Xu, Lin Qiu, Xiaoyu Song, Mingjian Zhang, Jiahao Zhang, Jian Yu, Aiguo Wu, Xiaotian Wang, Jie Lin
{"title":"Single-Atom Cu Anchored on a UiO-66 Surface-Enhanced Raman Scattering Sensor for Trace and Rapid Detection of Volatile Organic Compounds.","authors":"Yuening Wang, Xiangyu Meng, Wenxiong Shi, Yujiao Xie, Aochi Liu, Lei Xu, Lin Qiu, Xiaoyu Song, Mingjian Zhang, Jiahao Zhang, Jian Yu, Aiguo Wu, Xiaotian Wang, Jie Lin","doi":"10.34133/research.0841","DOIUrl":"10.34133/research.0841","url":null,"abstract":"<p><p>Volatile organic compounds (VOCs) serve as critical biomarkers in exhaled breath for early-stage cancer patients, and their rapid, trace-level detection holds marked implications for cancer screening. Surface-enhanced Raman scattering (SERS) technology demonstrates strong potential for trace VOC gas detection due to its ultra-high sensitivity and immunity to water interference. However, while surface plasmon resonance (SPR)-free semiconductor substrates offer superior spectral stability and selectivity, their sensitivity toward VOC detection remains suboptimal. This study introduces a novel semiconductor-based SERS substrate composed of copper single atoms anchored on UiO-66 (Cu<sub>1</sub>/UiO-66), achieving a record-low detection limit of 10 parts per billion for VOC gases with a rapid 2-min response time, thereby elevating the gas-sensing performance of SPR-free substrates to unprecedented levels. The exceptional SERS activity originates from the highly delocalized electron properties of single-atomic copper, which effectively facilitates single-atom charge transfer processes. Concurrently, the incorporation of copper single atoms modulates the band structure of UiO-66, substantially enhancing the coupling resonance between the substrate and target molecules. In simulated breath tests mimicking lung cancer patients' exhalations, Cu<sub>1</sub>/UiO-66 exhibits remarkable VOC recognition capability and robust anti-interference performance. This work pioneers a new paradigm for ultra-sensitive, rapid detection of trace VOCs in exhaled breath, holding substantial promise for early cancer diagnostics and clinical translation.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0841"},"PeriodicalIF":10.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12368966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-21eCollection Date: 2025-01-01DOI: 10.34133/research.0845
Rui Wang, Wenguo Cui, Xinliang Chen
{"title":"DNA Photofluids: An Innovative Breakthrough in Mimicking Cellular Life Behaviors.","authors":"Rui Wang, Wenguo Cui, Xinliang Chen","doi":"10.34133/research.0845","DOIUrl":"10.34133/research.0845","url":null,"abstract":"<p><p>Current molecular machines face substantial challenges in coordinating their actions in space and time to generate cell-like macroscopic motions. A recent study in <i>Nature Materials</i> introduced a light-responsive artificial DNA nanomachine based on liquid-liquid phase separation technology-photofluids. By applying different light stimuli for spatiotemporal control, this nanomachine system successfully mimics typical cellular behaviors such as division, deformation, pseudopod extension, and rotation at the macroscopic scale for the first time. This study represents an innovative pathway from energy conversion at the molecular level to cell-like motion at the macroscopic level.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0845"},"PeriodicalIF":10.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370175/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ResearchPub Date : 2025-08-21eCollection Date: 2025-01-01DOI: 10.34133/research.0853
Yaran Wang, Fan Wu, Yijin Ren, Yong Liu, Henny C Mei
{"title":"Metal Nanomaterials: A Strategy to Combat Drug-Resistant Bacterial Infections.","authors":"Yaran Wang, Fan Wu, Yijin Ren, Yong Liu, Henny C Mei","doi":"10.34133/research.0853","DOIUrl":"10.34133/research.0853","url":null,"abstract":"<p><p>Bacterial infections pose a major challenge today due to the rise of drug resistance in pathogenic bacteria, creating an urgent need for the development of nonantibiotic therapies. Metal nanomaterials are increasingly recognized as promising antibacterial agents due to their unique physical and chemical properties, which offer strong antibacterial capabilities and broad-spectrum activity against drug-resistant bacteria. Unlike traditional antibacterial therapies, metal nanomaterials rarely induce drug resistance because of their diverse antibacterial mechanisms, which destroy bacteria by directly damaging bacterial cells or generating oxidative stress. Metal nanomaterials have proven effective in treating various drug-resistant bacterial infections. This perspective highlights recent advances in metal nanomaterials for antimicrobial applications. Firstly, bacterial infections and the current dilemma are introduced. Next, recent progress in the antibacterial activity of metal nanomaterials against drug-resistant bacteria is summarized, along with the challenges in their antimicrobial applications. Finally, future prospects and remaining challenges associated with the use of metal nanomaterials to treat drug-resistant bacteria are discussed.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0853"},"PeriodicalIF":10.7,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12368965/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}