Research最新文献

{"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 (Cu₁/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, Cu₁/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}

{"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}

{"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}

{"title":"S²ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning.","authors":"Mingze Yin, Hanjing Zhou, Jialu Wu, Yiheng Zhu, Yuxuan Zhan, Zitai Kong, Hongxia Xu, Chang-Yu Hsieh, Jintai Chen, Tingjun Hou, Jian Wu","doi":"10.34133/research.0721","DOIUrl":"10.34133/research.0721","url":null,"abstract":"<p><p>Antibodies safeguard our health through their precise and potent binding to specific antigens, demonstrating promising therapeutic efficacy in the treatment of numerous diseases, including COVID-19. Recent advancements in biomedical language models have shown the great potential to interpret complex biological structures and functions. However, existing antibody-specific models have a notable limitation that they lack explicit consideration for antibody structural information, despite the fact that both 1-dimensional sequence and 3-dimensional structure carry unique and complementary insights into antibody behavior and functionality. This paper proposes the <b>S</b>equence-<b>S</b>tructure multi-level pre-trained <b>A</b>ntibody <b>L</b>anguage <b>M</b>odel (S²ALM), combining holistic sequential and structural information in one unified, generic antibody foundation model. We construct a hierarchical pre-training paradigm incorporated with 2 customized multi-level training objectives to facilitate the modeling of comprehensive antibody representations. S²ALM's representation space uncovers inherent functional binding mechanisms, biological evolution properties, and structural interaction patterns. Pre-trained over 75 million sequences and 11.7 million structures, S²ALM can be adopted for diverse downstream tasks: accurately predicting antigen-antibody binding affinities, precisely distinguishing B cell maturation stages, identifying antibody crucial binding positions, and specifically designing novel coronavirus-binding antibodies. Remarkably, S²ALM outperforms well-established and renowned baselines and sets new state-of-the-art performance across extensive antibody-specific understanding and generation tasks. S²ALM's ability to model comprehensive and generalized representations further positions its potential to advance real-world therapeutic antibody development, potentially addressing unmet academic, industrial, and clinical needs.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0721"},"PeriodicalIF":10.7,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364524/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966729","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":"Generative Artificial Intelligence in the Metaverse Era: A Review on Models and Applications.","authors":"Han Zhou, Xinyi Chen, Jin Li, Zichen Zhang, Yao Fu, Mailyn Pérez Liva, Dov Greenbaum, Pan Hui","doi":"10.34133/research.0804","DOIUrl":"10.34133/research.0804","url":null,"abstract":"<p><p>The Metaverse is a decentralized, immersive 3-dimensional virtual environment that merges the physical and virtual worlds, fundamentally transforming digital interaction and garnering widespread attention. However, its primary platforms face challenges such as low-quality content and underdeveloped virtual environments, leading to a subpar user experience. Artificial intelligence-generated content (AIGC) has emerged as a key driver in Metaverse development, enabling the efficient and cost-effective creation of digital content. AIGC also promotes personalized content, further enhancing the appeal of the Metaverse. Although AIGC holds great promise, comprehensive investigations into its underlying models and applications remain limited. This study begins with the core neural network architectures of generative AI and examines the relationship between the Metaverse and AIGC. It delves into the deep learning technologies that support AIGC, providing both qualitative and quantitative analyses of their advantages, limitations, and hardware constraints. We also review existing practical applications of the Metaverse, highlighting the challenges and future opportunities in key domains such as healthcare and education. The research concludes that while AIGC can markedly accelerate the development of the Metaverse, its technology must be more closely aligned with development needs to deliver a truly immersive experience. The integration of AIGC and the Metaverse represents the convergence of artificial intelligence, computer graphics, and human-computer interaction. This interdisciplinary synergy has the potential to redefine the way we create, interact with, and experience digital environments, pushing the boundaries of creativity and immersion.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0804"},"PeriodicalIF":10.7,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966793","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":"An Explainable Two-Stage Machine Learning Model for Predicting the Post-Thrombolysis Complications in Stroke Patients: A Multi-Center Study.","authors":"Hongling Zhu, Qing Ye, Shurui Wang, Hongsen Cai, Mairihaba Maimaiti, Jinsheng Lai, Chuan Qin, Ping Zhang, Yanyan Chen, Qiushi Luo, Hong Wu, Danyang Chen, Shiling Chen, Shudan Zhu, Yuting Lv, Yanxiang Xu, Jian Zhang, Benshan Hu, Yuanxiang Yin, Yan Xie, Dongmei Zhu, Xiaoxing Ming, Zhouping Tang, Hesong Zeng","doi":"10.34133/research.0817","DOIUrl":"10.34133/research.0817","url":null,"abstract":"<p><p>Current tools for predicting the thrombolysis risk in patients after stroke exhibit limited event prediction in early post-thrombolysis hemorrhagic events. This highlights an unmet medical need to improve the tools for stroke management. We developed an explainable 2-stage machine learning model for stroke risk stratification to predict the risk of bleeding, composite complications, and all-cause death in patients before and after thrombolysis therapy. The model integrated LightGBM, XGBoost, random forest model (RF), decision tree model (DT), and logistic regression model (LR), and was trained on data from 5,333 patients from Tongji Hospital, achieving improved predictive accuracy in the post-thrombolysis stage compared to the pre-thrombolysis stage. The model exhibited increased area under the curve (AUC) of 0.7581 [95% confidence interval (CI), 0.6955 to 0.8177] and 0.7234 (0.6527 to 0.7909) (bleeding), 0.7625 (0.7324 to 0.7936) and 0.7035 (0.6685 to 0.7392) (composite complications), and 0.9264 (0.8736 to 0.9660) and 0.845 (0.7454 to 0.9375) (death) in post-thrombolysis stage than in pre-thrombolysis stage. External validation using data of 526 patients across 2 different hospitals confirmed the robustness of the model. Key predictors such as temperature, vital signs, and demographic factors were identified. A prototype embedding the best-performing model was constructed. This model enhances thrombolysis risk prediction and supports personalized patient care management, demonstrating its potential for clinical decision support system integration into stroke management strategies.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0817"},"PeriodicalIF":10.7,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364525/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966823","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":"Emerging Roles of GDF15 in Metabolic and Cardiovascular Diseases.","authors":"Tian Tian, Monan Liu, Peter J Little, Hans Strijdom, Jianping Weng, Suowen Xu","doi":"10.34133/research.0832","DOIUrl":"10.34133/research.0832","url":null,"abstract":"<p><p>Growth differentiation factor 15 (GDF15), a TGF-β superfamily member and stress-responsive cytokine, plays a critical role in metabolism and regulation of inflammation. This review summarizes the expression, distribution, structure, processing, and secretion of GDF15. We also discuss multilayered regulatory networks governing GDF15 expression, including ATF4/CHOP, AMPK, EGR1, EZH2, PPARγ, NRF2, ERRγ, and p53, as well as posttranscriptional regulator CNOT6L. The GFRAL receptor is central to its function, mediating the anorexigenic and metabolic effects of GDF15. This review synthesizes evidence linking GDF15 to obesity, diabetes, cardiovascular diseases, metabolic liver disorders, cachexia, sarcopenia, and aging while exploring its interactions with key metabolic factors including FGF21, GLP-1, leptin, and glucocorticoids. Lifestyle interventions such as ketogenic, high-fat diets, and exercise modulate GDF15 levels, underscoring its role in pan-metabolic health. Pharmacologically, various agents-including anti-hyperglycemic agents and natural compounds-induce GDF15 expression, implicating their therapeutic potential in cardiometabolic diseases. We comprehensively evaluate current advances in GDF15-targeted drug development, including monoclonal antibodies, fusion proteins, and small-molecule drugs, to provide a scientific foundation for innovative therapies. Finally, we outline unresolved issues in GDF15 biology and therapeutics, such as the exploration of peripheral receptors, contradictory findings in studies of cardiometabolic diseases, and the persistent challenges in developing GDF15-targeted therapeutics.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0832"},"PeriodicalIF":10.7,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12361751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966833","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":"Decoding Mitotic Chromosome Assembly: Three Rules Governing Condensin-Cohesin Engagement.","authors":"Haiyan Yan, Xinyu Zhou, Fangwei Wang","doi":"10.34133/research.0812","DOIUrl":"10.34133/research.0812","url":null,"abstract":"<p><p>Mitotic chromosome formation depends on coordinated SMC complex activities, yet how condensin engages cohesin during this process remains unclear. Samejima et al. combined synchronized mitotic entry, auxin-inducible degrons, high-resolution Hi-C, live-cell imaging, quantitative proteomics, and polymer simulations to dissect condensin I, condensin II, and cohesin interplay in vertebrate cells. They showed that condensins actively displace extrusive cohesin to dismantle interphase chromatin and build nested mitotic loops. Condensin II generates large, helical loops, and condensin I forms finer loops, together yielding the canonical rodlike mitotic chromosome. Cohesin, while preserving sister-chromatid cohesion, relocates to loop tips without blocking condensin. The study also reports the first in vivo measurements of condensin loop-extrusion speed. This work establishes a mechanistic, quantitative framework for mitotic chromosome architecture and offers predictive models for future genome-organization- and SMC-related pathology studies.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0812"},"PeriodicalIF":10.7,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364523/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966840","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":"Fabric-Based Flexible Pressure Sensor Arrays with Ultra-Wide Pressure Range for Lower Limb Motion Capture System.","authors":"Xiaohua Wu, Yuxuan Liang, Longsheng Lu, Shu Yang, Zhanbo Liang, Feilong Liu, Xiaoyu Lu, Bowen Xiao, Yilin Zhong, Yingxi Xie","doi":"10.34133/research.0835","DOIUrl":"10.34133/research.0835","url":null,"abstract":"<p><p>The lower limb motion capture technology has garnered significant attention as a pivotal enabler in extended reality, sports science, film production, and medical rehabilitation. However, existing mature systems face critical challenges, including restricted operational environments, interference with natural activities, and cumbersome wearability. Here, a flexible insole pressure sensor array with an ultra-wide sensing range is developed using dip coating, laser cutting, and hot pressing, enabling lower limb motion capture. The developed fabric-based flexible pressure sensor exhibited an ultra-wide pressure range (3,770.9 kPa), high sensitivity (2.68 kPa^-1), rapid response, recovery times (17.2 ms/3.5 ms), and high work life (>4 million loading/unloading cycles). The insole-shaped flexible pressure sensor array accurately measures pressure in different postures, achieving 95.5% classification accuracy across 10 dynamic and static poses. More importantly, the system achieved a joint position prediction accuracy of 7.8 pixels (~3.6 cm) in lower limb pose estimation. This high-precision lower limb motion capture system represents an ideal terminal for future extended reality applications, offering seamless integration, comfortable use, easily wearable design, and broad accessibility.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0835"},"PeriodicalIF":10.7,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12358749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883526","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":"Mechanical Cell Reprogramming on Tissue-Mimicking Hydrogels for Cancer Cell Transdifferentiation.","authors":"Xueqing Ren, Yachao Wang, Mengcheng Lei, Yi Zou, Pengjie Li, Fukang Qi, Jinyun Shi, Han Xie, Mingyu Zhang, Wenhui Wang, Lian Xue, Peng Chen, Bi-Feng Liu, Yiwei Li","doi":"10.34133/research.0810","DOIUrl":"10.34133/research.0810","url":null,"abstract":"<p><p>Disrupted matrix mechanics have been found to be highly associated with increased risks of many diseases, including neurodegenerative diseases and cancers. For centuries, the aged tissue matrix has been found to lose its mechanical integrity and exhibit altered biophysical properties. Whether the mechanical properties of matrix serve as a regulator for maintaining the health and function of cells remains unknown. Here, we propose that cells cultured within a tissue-mimicking mechanical microenvironment exhibit reprogrammed cellular behaviors. We first construct a tissue-mimicking hydrogel by combining both viscoelastic and nonlinear elastic components, on which fibroblasts crowd together to form mesenchymal aggregates instead of individually spreading out. The mesenchymal aggregates not only obtain the elevated expression of stemness genes but also exhibit enhanced bidirectional differentiation potentials. The formation of mesenchymal aggregates happens through the reorganization of the collagen network induced by the enhanced cell contraction. Compromising the cell contraction not only prevents the formation of mesenchymal aggregates but also eliminates cell reprogramming. Additionally, this mechanical reprogramming with tissue-mimicking hydrogels has been applied to non-small-lung cancer cells and promotes their adipogenic transdifferentiation, which eventually reverses their epithelial-to-mesenchymal transition genes and suppresses the expression of oncogenes/pro-oncogenes. Thus, our study paves the way for both regenerative medicine and cancer treatments with an approach termed mechanical reprogramming on tissue-mimicking hydrogels.</p>","PeriodicalId":21120,"journal":{"name":"Research","volume":"8 ","pages":"0810"},"PeriodicalIF":10.7,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12358751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883527","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}