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Recommendation of Resource Allocation decision Based on Bipartite Graph.Network Structure

IEIE Transactions on Smart Processing and Computing 2025年第1期14卷 128-139页

作者： Pei, Wen Pan, Wen-An Huang, Jui-Chan College of Management Chung Hua University Hsinchu30012 Taiwan Ph.D Program of Management Chung Hua University Hsinchu30012 Taiwan Department of Industrial Engineering and Management National Kaohsiung University of Science and Technology Kaohsiung807618 Taiwan

In resource allocation decisions in business, fully understanding customers’ needs and preferences helps to maximise benefits. As a result, in the modern business environment, the design of customized recommendation systems has gained a lot of attention. To this end, the study designs a recommendation algorithm for resource allocation decision based on improved two-part graph.network structure. In this algorithm, an improved K-means clustering algorithm is introduced to deeply mine potential information. The calculation of similarity between users is also optimised to assist the target user to find the real neighbouring users. The findings demonstrate that, in comparison to the other algorithms, the resource allocation recommendation algorithm based on improved bipartite graph.suggested in the study has a greater hit rate. The hit rate of the suggested algorithm can reach 32.5% when the recommendation list length is 10, which is a 21.5% improvement over the collaborative filtering algorithm. The suggested algorithm’s popularity is only 39.1, which is 69.3 less than the collaborative filtering algorithm when the suggestion list length is 10. Furthermore, the suggested algorithm for resource allocation decision-making created by the research has a greater recommendation accuracy, more personalization, and diversity, as seen by the proposed algorithm’s mean Hamming distance of 0.976. Through an improved bipartite graph.network, the algorithm can fully analyze the historical preference information of users, effectively capture the complex relationship between users and products, generate personalized recommendation lists, and improve user satisfaction and purchase conversion rates. It provides an effective recommendation role for resource allocation decisions in modern business and helps to create greater economic benefits. © 2025 Institute of Electronics Engineers of Korea. All rights reserved.

关键词： Collaborative filtering

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deep-Learning Approach for An Analysis of Real-estate Prices and Transactions

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IEEE Access 2025年 13卷 89248-89265页

作者： Yang, Cheng-Hong Lee, Borcy Lin, Yu-da Tainan University of Technology Department of Information Management Tainan Taiwan National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung Taiwan Kaohsiung Medical University Ph.D. Program in Biomedical Engineering Kaohsiung Taiwan Kaohsiung Medical University School of Dentistry Kaohsiung Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Kaohsiung Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

Research on the study of houses, condominiums and buildings in Taiwan’s metropolitan areas continues to be an important area of research. In real estate forecasting and analysis, methods such as statistical analysis and questionnaire data collection are widely used. However, when multidimensional data is considered, these methods are time-consuming and inadequate. This study aimed to build a real estate forecasting model that can adapt to a changing environment. data were collected from public government databases, the collected data were standardized for accurate clustering, an appropriate data clustering algorithm was applied to the standardized data, and cross-statistical analysis was performed to verify the adopted algorithm. We used a deep learning based on autoencoder algorithm to increase the accuracy of the clustering analysis. A double-bottom map particle swarm optimization (dBM-PSO) clustering algorithm was then used to determine the optimal clustering solution. Cluster analysis and deep learning were conducted on data collected from public websites to understand the factors that led to the sustained increase in housing prices in Taiwan over the past decade. The results of this study indicate that three key factors—the number of real estate transactions, the average unit price of real estate transactions, and the building material and construction index—significantly affected real estate prices in Taiwan. Our results could help researchers and governments to focus on specific aspects of real estate development without being influenced by other related factors. In addition, the relationships between real estate trends and the aforementioned three key factors were determined to obtain valuable information that can enable the Taiwanese government to regulate the property market and prevent excessive growth. The framework proposed in this paper allows researchers and governments to focus on specific aspects of real estate development without being influenced b

关键词： Houses

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Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCd industry

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International Journal of Production Research 2025年第6期63卷 2090-2113页

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Chiang, Chih-Hsiung Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan Division of Quality Control AUO Corporation Taichung Taiwan

In the thin film transistor-liquid crystal display (TFT-LCd) industry, the competition is fierce, and the external failure cost is high. To improve the quality of released products, sampling inspection under outgoing quality control (OQC) is conducted before products are released. Owing to the variety and complexity of inspection items, the task must be carried out manually while realising automation is difficult. Traditional random sampling inspection is limited by sampling quantity, manpower, and material resources. To effectively improve acceptable quality levels, this paper proposes a quality predictive monitoring framework tailored to the production and inspection characteristics of the TFT-LCd industry. This framework includes real-time automatic quality monitoring based on an optimal machine learning prediction model with two-ph.se feature creation, and it also addresses OQC inspection capacity constraints. Experimental results show the prediction performance based on proposed model is better than the traditional random sampling process. In practice, superior average outgoing quality improves by more than 70% at the same sampling level. In addition, the features of the process can be further controlled and managed based on the prediction model to monitor the key parameters in real time and respond to abnormalities quickly, thereby further improving the quality of released products. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Liquid crystal displays

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Prediction tools for assessing functional impacts of gene mutations in Clear Cell Renal Cell Carcinoma: A comparative study

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Computers in Biology and Medicine 2025年第Pt A期192卷 110187-110187页

作者： Yang, Cheng-Hong Lin, Guan-Cheng Wu, Chih-Hsien Chen, Jin-Bor Chuang, Li-Yeh Department of Information Management Tainan University of Technology Tainan Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung Taiwan Division of Nephrology Department of Internal Medicine Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Taiwan Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering I-Shou University Kaohsiung Taiwan Taiwan

Renal cell carcinoma (RCC) is a well-known malignancy characterized by specific gene mutations that elevate its occurrence. It can be categorized into clear cell RCC (ccRCC), papillary RCC, and chromoph.be RCC, which account for approximately 85 % of all primary RCC cases. The mutations typically involve single-nucleotide variants (SNVs) that lead to amino acid substitutions, which influence various biological functions, including gene expression. Therefore, predicting the functional consequences of RCC-related single-nucleotide polymorph.sms (SNPs), including substitutions, insertions, deletions, and duplications, is crucial for the effective clinical management of RCC. In recent years, the accessibility and popularity of tools for predicting SNP functional variations have grown, especially in research concerning the potential risks associated with key gene mutations in cancer. Accordingly, this study focused on commonly mutated genes in ccRCC, namely VHL, BAP1, PBRM1, and SETd2. Public data from sources such as The Cancer Genome Atlas and the National Center for Biotechnology Information were used to identify 61 gene mutation positions. Nine nonsynonymous mutation prediction tools were used for analysis, namely SIFT, Polyph.n-2, Mutation Assessor, Fathmm, MutPred, CHASM, Revel, Provean, and SNP&GO. The tools were evaluated by their statistical performance, prediction distribution, and receiver operating characteristic curves. The three tools with the highest accuracy for predicting the functional consequences of mutations in the four frequently mutated genes associated with ccRCC were SIFT (accuracy of 0.75), Provean (0.7), and Polyph.n-2 (0.69). These findings offer valuable insights into predicting ccRCC-related gene mutation effects, but further research and validation are essential to support their clinical applications. © 2025

关键词： Transcription

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Cytocompatible and antibacterial Fe-, Cu- and Zn-substituted calcium hydroxyapatite materials for skin applications

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Ceramics International 2025年第9期51卷 11286-11296页

作者： Lukaviciute, L. Lukowiak, A. Stankeviciute, Z. Junka, A. Mortimer, M. Zarkov, A. Yang, J.-C. Ganceviciene, R. Kareiva, A. Faculty of Chemistry and Geosciences Vilnius University Naugarduko st. 24 Vilnius03225 Lithuania Institute of Low Temperature and Structure Research Polish Academy of Sciences Okolna 2 Wroclaw50422 Poland Department of Pharmaceutical Microbiology and Parasitology Wroclaw Medical University Borowska 211A Wroclaw50556 Poland Laboratory of Environmental Toxicology National Institute of Chemical Physics and Biophysics Akadeemia tee 23 Tallinn12618 Estonia Graduate Institute of Nanomedicine and Medical Engineering International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Research Center of Biomedical Device Research Center of Digital Oral Science and Technology Taipei Medical University Taiwan Faculty of Medicine Vilnius University M.K. Ciurlionio st. 21 Vilnius03101 Lithuania

Calcium hydroxyapatite (C10(PO4)6(OH)2;CHAp) and metal-substituted samples (Fe:CHAp, Cu:CHAp, and Zn:CHAp) were synthesized using a recently developed method. This method involved the wet precipitation of amorph.us calcium ph.sph.te (ACP), followed by solid-state reaction synthesis of α-tricalcium ph.sph.te (α-TCP), and finally hydrothermal synthesis of CHAp. The effect of Fe3+, Cu2+, and Zn2+ substitution on the ph.se purity and antimicrobial properties of CHAp are summarized in this study. Notably, it highlights the ph.se purity of CHAp and Zn:CHAp (in the presence of Fe3+ and Cu2+ ions, the α- and β-TCP ph.ses have formed) as well as the antimicrobial activity of Zn:CHAp and Cu:CHAp against Staph.lococcus aureus and Candida albicans. The synthesized nanosized CHAp, Fe:CHAp, Cu:CHAp, and Zn:CHAp samples were used as additives in the preparation of skin creams. In vitro biological studies of the resulting skin creams demonstrated their antimicrobial activity against Pseudomonas aeruginosa, and showed a reduction in osteoblasts cells viability of in the range of 20–40 %. The addition of zinc enhances antimicrobial efficacy but reduces biocompatibility, while copper maintains both high antimicrobial activity and biocompatibility, making it more suitable for the development of medical or cosmetic materials. dermal creams containing CHAp with copper and iron ions also show significant antimicrobial activity while preserving good cell viability. These results highlight the importance of optimizing the balance between antimicrobial effectiveness and biocompatibility in these materials. © 2024

关键词： Biocompatibility

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Chemical Characteristics of Stack Particulate Matter Emitted from Sintering Process of an Integrated Steel Mill and Resolution of Source Contributors on Boundary PM_2.5

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Aerosol and Air Quality Research 2025年第6期25卷 1-14页

作者： Shao, Cheng-Tsung Tseng, Yu-Lun Yuan, Chung-Shin Cheng, Wen-Hsi Li, Nian-Jie Zhao, Jia-Yi Institute of Environmental Engineering National Sun Yat-Sen University Kaohsiung City Taiwan Net Zero Emissions and Resource Recycling Technology Research Center National Sun Yat-Sen University Kaohsiung City Taiwan Environmental Protection Department China Steel Corporation Kaohsiung City Taiwan Ph.D. Program in Maritime Science and Technology College of Maritime National Kaohsiung University of Science and Technology Kaohsiung City Taiwan

Background: This study investigated the chemical characteristics of PM2.5 emitted from the sintering process of an integrated steel mill and assesses the contribution of emission sources to boundary PM2.5. Methods: PM... 详细信息

Background: This study investigated the chemical characteristics of PM_2.5 emitted from the sintering process of an integrated steel mill and assesses the contribution of emission sources to boundary PM_2.5. Methods: PM_2.5 samples were simultaneously collected from three stacks of the sintering process and two boundary sites located at the upstream (Site N) and downstream (Site S) of the steel mill. The chemical compositions of PM_2.5, including water-soluble ions (WSIs), metallic elements, carbonaceous matter, anhydrosugars, and organic acids, were further analyzed. The chemical mass balance (CMB) receptor model was then employed to identify emission sources and quantify their contributions. Results and discussion: Stack emissions revealed that the dominant anions (SO₄²⁻, NO₃⁻, Cl⁻) and cations (Na⁺, NH₄⁺, and Ca²⁺) were similar across TPM, FPM, and CPM fractions. Fe, Al, and Ca were the most abundant metals, while organic carbon (OC) dominated the carbonaceous content, primarily from coke oven gas and solid fuel combustion. At the boundary sites, PM_2.5 concentrations were generally higher at Site S, especially in fall and winter, due to fugitive dust from raw material handling and heavy-duty truck activities. Seasonal variation of PM_2.5 concentrations followed the order: winter > fall > spring > summer. dominant WSIs included NO₃⁻, SO₄²⁻, NH₄⁺, Cl⁻, and Na⁺, and the key metals were Fe, Ca, Mg, Al, and Zn. The OC/EC ratios ranged from 1.49–1.88 and were slightly higher at Site N. Source apportionment showed that the steel mill contributed 28.3% and 36.6% of PM_2.5 at Sites N and S, respectively, with the sintering process being the largest contributor (3.37% at Site N and 12.4% at Site S). Conclusions: The sin

关键词： Chemical characteristics Particulate matter Source apportionment Spatiotemporal variation Stack and field samplings

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Umbilical cord-derived mesenchymal stem cells secretomes promote embryo development and implantation

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Life sciences 2025年 374卷 123693页

作者： Teerapong, Prompunya Yang, Yuan-Ting Bhargava Sreerangaraja Urs, dilip Liu, Jun-Jen Kao, Shu-Huei Ph. D. Program in Medical Biotechnology College of Medical Science and Technology Taipei Medical University Taipei 110 Taiwan Veterinary Research and Development Center-Lower Northern Region National Institute of Animal Health Bangkok 10900 Thailand Biomedical Department High-Tek Harness Enterprise Co. Ltd. Taipei 115 Taiwan School of Medical Laboratory Science and Biotechnology College of Medical Science and Technology Taipei Medical University Taipei 110 Taiwan Center for Reproductive Medicine Department of Obstetrics and Gynecology Taipei Medical University Hospital Taipei 110 Taiwan

Aims: Successful implantation relies on high-quality blastocysts, uterine receptivity, and effective embryo-endometrium communication. This study investigated the effects of umbilical cord-derived mesenchymal stem cells (UC-MSC) secretomes on embryo development and implantation. Main methods: Troph.blastic sph.roids and murine embryos were used to evaluate the impact of UC-MSC secretomes. Embryos obtained through superovulation were cultured in vitro and divided into five groups: a control group and four experimental groups treated with varying concentrations of UC-MSC secretomes (2.5, 5, 10, and 50 μg/mL). Embryo development competence and implantation potential were assessed in each group, and the expression levels of related genes were analyzed. Key findings: Supplementation with UC-MSC secretomes significantly enhanced troph.blast cell migration. It also stimulated endometrial cell proliferation and upregulated key implantation-related genes (LIF, LIFR, VEGFA, ITGB3, and ITGAV), improving endometrial receptivity and adhesion in troph.blastic sph.roid co-cultures. While morulation rates of murine embryos remained unchanged, UC-MSC secretomes supplement significantly increased blastulation, pluripotency gene expression, and hatching rates. Supplementation with 10 and 50 μg/mL significantly increased blastocyst diameter and blastomere number, as well as embryo adhesion, outgrowth areas, and implantation rates. Additionally, growth factor analysis showed elevated VEGF-A and PdGF-AA levels in the culture media. Significance: This study demonstrates that UC-MSC secretomes enhance both embryo development and endometrial cell function, facilitating implantation potential. These findings suggest their potential utility in supporting preimplantation embryos and improving maternal endometrial receptivity in ART. © 2025 The Authors

关键词： Embryo development Embryo implantation Secretomes Umbilical cord mesenchymal stem cells

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dual functional antibacterial nanofiber membranes: Polyhexamethylene biguanide-integrated alginate-chitosan-dye modified polyamide 56 for single-use biomedical applications

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International Journal of Biological Macromolecules 2025年 310卷 143331页

作者： Liao, Ting-Cjia Le, Quang-Vinh Hanh, Nguyen The duc Liu, Bing-Lan Srinoph.kun, Penjit Prapainainar, Paweena Chiu, Chen-Yaw Wang, Chi-Yun Ng, I-Son Chen, Kuei-Hsiang Chang, Yu-Kaung of Biochemical Engineering Ming Chi University of Technology New Taipei City243303 Taiwan Center for Environmental Sustainability and Human Health Ming Chi University of Technology Taishan New Taipei City243303 Taiwan Department of Applied Chemistry Chaoyang University of Technology Taichung413310 Taiwan National Center of Excellence for Petroleum Petrochemicals and Advance Material Department of Chemical Engineering Faculty of Engineering Kasetsart University Chatuchak Bangkok10900 Thailand Center for Advanced Studies in Nanotechnology for Chemical Food and Agricultural Industries Kasetsart University Chatuchak Bangkok10900 Thailand Department of Chemical Engineering Ming Chi University of Technology New Taipei City243303 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City243303 Taiwan Departmental of Chemical Engineering National Cheng Kung University Tainan70101 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Zhongli Dist. Taoyuan City320315 Taiwan

Polyamide 56 (PA56) nanofiber membranes were functionalized with alginate (AG), chitosan (CS), reactive dyes (RG19, RR141), and poly(hexamethylene biguanide) (ph.B) to develop multifunctional antimicrobial membranes for single-use applications. The resulting membranes, PA56-AG-CS-RG19-ph.B and PA56-AG-CS-RR141-ph.B, achieved high antibacterial efficiencies of 97.12 % and 90.65 %, respectively, against Escherichia coli, demonstrating potent bacterial inhibition. The antimicrobial performance results from a synergistic dual mechanism. Chitosan disrupts bacterial adhesion and biofilm formation through electrostatic interactions, while ph.B compromises membrane integrity and interferes with intracellular processes. This combined action enhances bactericidal efficacy. The functionalization strategy also maintained excellent biocompatibility, with minimal cytotoxicity observed in L929 fibroblasts. Optimized concentrations of AG and CS were systematically evaluated to ensure balanced antibacterial performance and mechanical stability. These membranes, designed for single-use, exhibited significantly reduced antibacterial activity upon reuse, supporting their intended application. Overall, the integration of chemical and ph.sical antimicrobial strategies within a nanofiber matrix presents a novel and effective approach. This strategy enables the development of next-generation materials suitable for real-world single-use biomedical applications, including wound dressings, food packaging, and protective textiles. © 2025 Elsevier B.V.

关键词： Escherichia coli

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dextran-integrated polypyrrole-Cu2O composite for improved electrochemical quantification of melatonin in biological samples

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International Journal of Biological Macromolecules 2025年第Pt 2期310卷 143247页

作者： Aiswarya, B. Gopika, M.G. Saraswathyamma, Beena Kuo, Chih-Yu Jeridi, Mouna Alshahrani, Thamraa Govindasamy, Mani International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Department of Polymer Science Central Institute of Petrochemical Engineering and Technology Kochi Eloor Udyogamandal P O Kochi683501 India Department of Chemistry Amrita Vishwa Vidyapeetham Amritapuri campus Clappana P O Kerala Kollam690525 India Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei10608 Taiwan High-Value Biomaterials Research and Commercialization Center National Taipei University of Technology Taipei106 Taiwan Biology Department College of Science King Khalid University Abha61413 Saudi Arabia Department of Physics College of Science Princess Nourah bint Abdulrahman University P. O. Box 84428 Riyadh11671 Saudi Arabia Research Center for Intelligent Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai602105 India

Monitoring the level of melatonin (MEL), a neurohormone that plays a vital role in governing the body's circadian rhythms and sleep cycles, is critical due to its ph.siological importance and potential adverse side effects during overexposure. This research deals with the design and development of a novel electrochemical sensor by modifying a glassy carbon electrode (GCE) with a composite of poly(vinyl alcohol) (PVA), dextran (dex), polypyrrole (PPy) and copper oxide particles (Cu2O) forming the PdPC composite. The synthesized composite was analyzed using both structural and morph.logical characterization methods. Additionally, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were conducted to examine electrochemical behaviour of the composite. Significantly, the dextran inclusion, which is a biocompatible polysaccharide, makes the composite more hydroph.lic, film forming, and stable enhancing sensor properties, more importantly, electrochemically. The sensor showed high electrocatalytic activity towards MEL oxidation as studied using CV and dPV. For MEL oxidation, the oxidation peak was found at +0.6 V in ph.sph.te buffer (ph.7.0) with an increase in current with respect to melatonin concentration. The sensor has a detection limit of 5.2 nM with a linear range of 10.0 nM to 850.0 μM, found to be better than most reported sensors. Analysis of real samples, such as human serum and urine, demonstrated the ability to selectively, stably, and reproducibly detect MEL. These data confirm the potential possibilities of using the sensor for clinical and point-of-care testing showing a significant development in polysaccharide-based electrochemical sensors. © 2025 Elsevier B.V.

关键词： dextran-based composite Electrochemical sensor Melatonin

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The Bacterial Outer Membrane Vesicle-Cloaked Immunostimulatory Nanoplatform Reinvigorates T Cell Function and Reprograms Tumor Immunity

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ACS Nano 2025年 2025 May 20页

作者： Lin, Yu-Han Chen, Chia-Wei Chen, Mei-Yi Xu, Li Tian, Xuejiao Cheung, Siu-Hung Wu, Yen-Ling Siriwon, Natnaree Wu, Si-Han Mou, Kurt Yun Taiwan International Graduate Program in Molecular Medicine National Yang Ming Chiao Tung University and Academia Sinica Taipei 11529 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University Taipei 11031 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei 11529 Taiwan Research Center for Applied Sciences Academia Sinica Taipei 11529 Taiwan Chakri Naruebodindra Medical Institute Faculty of Medicine Ramathibodi Hospital Mahidol University Samutprakarn 10540 Thailand International Ph.D. Program in Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei 11529 Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu 30013 Taiwan

Bacterial outer membrane vesicles (OMVs) represent powerful immunoadjuvant nanocarriers with the capacity to reprogram the tumor microenvironment (TME) and activate immune responses. Here, we investigate a nanotherapeutic platform integrating immunostimulatory cytosine-ph.sph.te-guanine oligodeoxynucleotides (CpG-OdNs, hereafter termed CpG) into mesoporous silica nanoparticles cloaked with OMVs (CpG@MSN-PEG/PEI@OMVs) for cancer immunotherapy. Systemic administration of these nanohybrids facilitates precise tumor targeting, induces antitumor cytokines such as IFNγ, and suppresses immunosuppressive cytokine TGF-β, reshaping the TME. Additionally, CpG@MSN-PEG/PEI@OMVs promote M1 macroph.ge polarization, dendritic cell maturation, and the generation of durable tumor-specific immune memory, resulting in pronounced tumor regression with minimal systemic toxicity. The platform demonstrates efficacy against metastatic and solid tumor models including 4T1 breast and MC38 colorectal cancers. Transcriptomic analyses reveal that CpG@MSN-PEG/PEI@OMVs enhance mitochondrial oxidative ph.sph.rylation in T cells within tumor-draining lymph.nodes, mitigating T cell exhaustion and restoring metabolic fitness. These results support the potential of CpG@MSN-PEG/PEI@OMVs as a modular nanoplatform to modulate innate and adaptive immunity in cancer immunotherapy. © 2025 The Authors. Published by American Chemical Society.

关键词： bacterial outer membrane vesicles mesoporous silica nanoparticles mitochondrial activity T cell exhaustion ph.notypes tumor microenvironment

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