Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing
Hyaluronic acid (HA) is a popular surface modifier in targeted cancer delivery due to its receptor-binding abilities. However, HA alone faces limitations in lipid solubility, biocompatibility, and cell internalization, making it less effective as a standalone delivery system. This comprehensive stud...
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Elsevier
2025-01-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024172775 |
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| author | Abd Kakhar Umar Patanachai K. Limpikirati Bachtiar Rivai Ilham Ardiansah Sriwidodo Sriwidodo Jittima Amie Luckanagul |
| author_facet | Abd Kakhar Umar Patanachai K. Limpikirati Bachtiar Rivai Ilham Ardiansah Sriwidodo Sriwidodo Jittima Amie Luckanagul |
| author_sort | Abd Kakhar Umar |
| collection | DOAJ |
| description | Hyaluronic acid (HA) is a popular surface modifier in targeted cancer delivery due to its receptor-binding abilities. However, HA alone faces limitations in lipid solubility, biocompatibility, and cell internalization, making it less effective as a standalone delivery system. This comprehensive study aimed to explore a dynamic landscape of complexation in HA-based nanoparticles in cancer therapy, examining diverse aspects from influential modifiers to emerging trends in cancer diagnostics. We discovered that certain active substances, such as 5-aminolevulinic acid, adamantane, and protamine, have been on trend in terms of their usage over the past decade. Dextran, streptavidin, and catechol emerge as intriguing conjugates for HA, coupled with nanostar, quantum dots, and nanoprobe structures for optimal drug delivery and diagnostics. Strategies like hypoxic conditioning, dual responsiveness, and pulse laser activation enhance controlled release, targeted delivery, and real-time diagnostic techniques like ultrasound imaging and X-ray computed tomography (X-ray CT). Based on our findings, conventional bibliometric tools fail to highlight relevant topics in this area, instead producing merely abstract and broad-meaning keywords. Extraction using Named Entity Recognition and topic search with Latent Dirichlet Allocation successfully revealed five representative topics with the ability to exclude irrelevant keywords. A shift in research focuses from optimizing chemical toxicity to particular targeting tactics and precise release mechanisms is evident. These findings reflect the dynamic landscape of HA-based nanoparticle research in cancer therapy, emphasizing advancements in targeted drug delivery, therapeutic efficacy, and multimodal diagnostic approaches to improve overall patient outcomes. |
| format | Article |
| id | doaj-art-1ff7f0aa0de745b09db8aae57794c93b |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-1ff7f0aa0de745b09db8aae57794c93b2025-01-17T04:50:38ZengElsevierHeliyon2405-84402025-01-01111e41246Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processingAbd Kakhar Umar0Patanachai K. Limpikirati1Bachtiar Rivai2Ilham Ardiansah3Sriwidodo Sriwidodo4Jittima Amie Luckanagul5Pharmaceutical Sciences and Technology Program, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Medical Informatics Laboratory, ETFLIN, Palu City, 94225, IndonesiaPharmaceutical Sciences and Technology Program, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Metabolomics for Life Sciences Research Unit, Chulalongkorn University, Bangkok, 10330, ThailandPharmaceutical Sciences and Technology Program, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Medical Informatics Laboratory, ETFLIN, Palu City, 94225, IndonesiaDepartment of Animal Husbandry, Faculty Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand; Medical Informatics Laboratory, ETFLIN, Palu City, 94225, IndonesiaDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, 45363, IndonesiaPharmaceutical Sciences and Technology Program, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Center of Excellence in Plant-produced Pharmaceuticals, Chulalongkorn University, Bangkok, 10330, Thailand; Corresponding author. Pharmaceutical Sciences and Technology Program, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.Hyaluronic acid (HA) is a popular surface modifier in targeted cancer delivery due to its receptor-binding abilities. However, HA alone faces limitations in lipid solubility, biocompatibility, and cell internalization, making it less effective as a standalone delivery system. This comprehensive study aimed to explore a dynamic landscape of complexation in HA-based nanoparticles in cancer therapy, examining diverse aspects from influential modifiers to emerging trends in cancer diagnostics. We discovered that certain active substances, such as 5-aminolevulinic acid, adamantane, and protamine, have been on trend in terms of their usage over the past decade. Dextran, streptavidin, and catechol emerge as intriguing conjugates for HA, coupled with nanostar, quantum dots, and nanoprobe structures for optimal drug delivery and diagnostics. Strategies like hypoxic conditioning, dual responsiveness, and pulse laser activation enhance controlled release, targeted delivery, and real-time diagnostic techniques like ultrasound imaging and X-ray computed tomography (X-ray CT). Based on our findings, conventional bibliometric tools fail to highlight relevant topics in this area, instead producing merely abstract and broad-meaning keywords. Extraction using Named Entity Recognition and topic search with Latent Dirichlet Allocation successfully revealed five representative topics with the ability to exclude irrelevant keywords. A shift in research focuses from optimizing chemical toxicity to particular targeting tactics and precise release mechanisms is evident. These findings reflect the dynamic landscape of HA-based nanoparticle research in cancer therapy, emphasizing advancements in targeted drug delivery, therapeutic efficacy, and multimodal diagnostic approaches to improve overall patient outcomes.http://www.sciencedirect.com/science/article/pii/S2405844024172775Latent dirichlet allocationNamed entity recognitionSurface conjugationMultiple compartment systemTumor microenvironmentCancer dual targeting therapy |
| spellingShingle | Abd Kakhar Umar Patanachai K. Limpikirati Bachtiar Rivai Ilham Ardiansah Sriwidodo Sriwidodo Jittima Amie Luckanagul Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing Heliyon Latent dirichlet allocation Named entity recognition Surface conjugation Multiple compartment system Tumor microenvironment Cancer dual targeting therapy |
| title | Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing |
| title_full | Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing |
| title_fullStr | Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing |
| title_full_unstemmed | Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing |
| title_short | Complexed hyaluronic acid-based nanoparticles in cancer therapy and diagnosis: Research trends by natural language processing |
| title_sort | complexed hyaluronic acid based nanoparticles in cancer therapy and diagnosis research trends by natural language processing |
| topic | Latent dirichlet allocation Named entity recognition Surface conjugation Multiple compartment system Tumor microenvironment Cancer dual targeting therapy |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024172775 |
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