The Innovation最新文献

{"title":"A bio-feedback-mimicking electrode combining real-time monitoring and drug delivery.","authors":"Shuaiyin Liu, Tianqin Ning, Junlin Chen, Yanzhe Fu, Jiebo Li, Jinyu Li, Xufeng Niu, Yubo Fan","doi":"10.1016/j.xinn.2024.100705","DOIUrl":"10.1016/j.xinn.2024.100705","url":null,"abstract":"<p><p>Effective disease management based on real-time physiological changes presents a significant clinical challenge. A flexible electrode system integrating diagnosis and treatment can overcome the uncertainties associated with treatment progress during localized interventions. In this study, we develop a system featuring a biomimetic feedback regulation mechanism for drug delivery and real-time monitoring. To prevent drug leakage, the system incorporates a magnesium (Mg) valve in the outer layer, ensuring zero leakage when drug release is not required. The middle layer contains a drug-laden poly(3,4-ethylenedioxythiophene) (PEDOT) sponge (P-sponge), which supplies the water to partially or fully activate the Mg valve under electrical stimulation and initiate drug release. Once the valve is fully opened, the exposed and expanded P-sponge electrode establishes excellent contact with various tissues, facilitating the collection of electrophysiological signals. Encapsulation with polylactic acid film ensures the system's flexibility and bioresorbability, thereby minimizing potential side effects on surrounding tissues. Animal experiments demonstrate the system's capability to mimic feedback modulation mechanisms, enabling real-time monitoring and timely drug administration. This integrated diagnosis and treatment system offers an effective solution for the emergency management of acute diseases in clinical settings.</p>","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"5 6","pages":"100705"},"PeriodicalIF":33.2,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584456","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":"When will dual-purpose pigs fly?","authors":"Leli Wang, Zhen Jia, Kui Xu, Feng Zhang, Yulong Yin","doi":"10.1016/j.xinn.2024.100702","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100702","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"19 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring the daily variation of Sun-Earth magnetic fields using galactic cosmic rays","authors":"The LHAASO Collaboration","doi":"10.1016/j.xinn.2024.100695","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100695","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"17 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to manage fish within and after the 10-year fishing ban","authors":"Haijun Wang, Jun Chen, Puze Wang, Erik Jeppesen, Ping Xie","doi":"10.1016/j.xinn.2024.100694","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100694","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"187 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing science, technology, and innovation to drive synergy between climate goals and the SDGs","authors":"Lei Huang, Ranjula Bali Swain, Erik Jeppesen, Hai Cheng, Panmao Zhai, Baojing Gu, Damià Barceló, Jianhua Lu, Ke Wei, Lei Luo, Fang Wang, Haijun Wang, Jiangyuan Zeng, Huadong Guo","doi":"10.1016/j.xinn.2024.100693","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100693","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"27 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Massive water production from lunar ilmenite through reaction with endogenous hydrogen","authors":"Xiao Chen, Shiyu Yang, Guoxin Chen, Wei Xu, Lijian Song, Ao Li, Hangboce Yin, Weixing Xia, Meng Gao, Ming Li, Haichen Wu, Junfeng Cui, Lei Zhang, Lijing Miao, Xiaoxue Shui, Weiping Xie, Peiling Ke, Yongjiang Huang, Jianfei Sun, Bingnan Yao, Min Ji, Mingliang Xiang, Yan Zhang, Shaofan Zhao, Wei Yao, Zhigang Zou, Mengfei Yang, Weihua Wang, Juntao Huo, Jun-Qiang Wang, Haiyang Bai","doi":"10.1016/j.xinn.2024.100690","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100690","url":null,"abstract":"Finding water resources is a crucial objective of lunar missions. However, both hydroxyl (OH) and natural water (HO) have been reported to be scarce on the Moon. We propose a potential method for obtaining water on the Moon through HO formation via endogenous reactions in lunar regolith (LR), specifically through the reaction FeO/FeO + H → Fe + HO. This process is demonstrated using LR samples brought back by the Chang’E-5 mission. FeO and FeO are lunar minerals containing Fe oxides. Hydrogen (H) retained in lunar minerals from the solar wind can be used to produce water. The results of this study reveal that 51–76 mg of HO can be generated from 1 g of LR after melting at temperatures above 1,200 K. This amount is ∼10,000 times the naturally occurring OH and HO on the Moon. Among the five primary minerals in LR returned by the Chang’E-5 mission, FeTiO ilmenite contains the highest amount of H, owing to its unique lattice structure with sub-nanometer tunnels. For the first time, heating experiments using a transmission electron microscope reveal the concurrent formation of Fe crystals and HO bubbles. Electron irradiation promotes the endogenous redox reaction, which is helpful for understanding the distribution of OH on the Moon. Our findings suggest that the hydrogen retained in LR is a significant resource for obtaining HO on the Moon, which is helpful for establishing a scientific research station on the Moon.","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"18 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for geoscience: Progress, challenges, and perspectives","authors":"Tianjie Zhao, Sheng Wang, Chaojun Ouyang, Min Chen, Chenying Liu, Jin Zhang, Long Yu, Fei Wang, Yong Xie, Jun Li, Fang Wang, Sabine Grunwald, Bryan M. Wong, Fan Zhang, Zhen Qian, Yongjun Xu, Chengqing Yu, Wei Han, Tao Sun, Zezhi Shao, Tangwen Qian, Zhao Chen, Jiangyuan Zeng, Huai Zhang, Husi Letu, Bing Zhang, Li Wang, Lei Luo, Chong Shi, Hongjun Su, Hongsheng Zhang, Shuai Yin, Ni Huang, Wei Zhao, Nan Li, Chaolei Zheng, Yang Zhou, Changping Huang, Defeng Feng, Qingsong Xu, Yan Wu, Danfeng Hong, Zhenyu Wang, Yinyi Lin, Tangtang Zhang, Prashant Kumar, Antonio Plaza, Jocelyn Chanussot, Jiabao Zhang, Jiancheng Shi, Lizhe Wang","doi":"10.1016/j.xinn.2024.100691","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100691","url":null,"abstract":"This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the “black-box” nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"61 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pursue the nature of science: Advocate for a better research environment","authors":"Ji Dai","doi":"10.1016/j.xinn.2024.100686","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100686","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"404 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tobacco as a promising crop for low-carbon biorefinery","authors":"Fan Wang, Xinglin Jiang, Yuchen Liu, Ge Zhang, Yao Zhang, Yongming Jin, Sujuan Shi, Xiao Men, Lijuan Liu, Lei Wang, Weihong Liao, Xiaona Chen, Guoqiang Chen, Haobao Liu, Manzoor Ahmad, Chunxiang Fu, Qian Wang, Haibo Zhang, Sang Yup Lee","doi":"10.1016/j.xinn.2024.100687","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100687","url":null,"abstract":"Energy crops play a vital role in meeting future energy and chemical demands while addressing climate change. However, the idealization of low-carbon workflows and careful consideration of cost-benefit equations are crucial for their more sustainable implementation. Here, we propose tobacco as a promising energy crop because of its exceptional water solubility, mainly attributed to a high proportion of water-soluble carbohydrates and nitrogen, less lignocellulose, and the presence of acids. We then designed a strategy that maximizes biomass conversion into bio-based products while minimizing energy and material inputs. By autoclaving tobacco leaves in water, we obtained a nutrient-rich medium capable of supporting the growth of microorganisms and the production of bioproducts without the need for extensive pretreatment, hydrolysis, or additional supplements. Additionally, cultivating tobacco on barren lands can generate sufficient biomass to produce approximately 573 billion gallons of ethanol per year. This approach also leads to a reduction of greenhouse gas emissions by approximately 76% compared to traditional corn stover during biorefinery processes. Therefore, our study presents a novel and direct strategy that could significantly contribute to the goal of reducing carbon emissions and global sustainable development compared to traditional methods.","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"19 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Light sheet fluorescence microscopy: Advancing biological discovery with more dimensions, higher speed, and lower phototoxicity","authors":"Yao Zhou, Shiqi Mao, Peng Fei","doi":"10.1016/j.xinn.2024.100692","DOIUrl":"https://doi.org/10.1016/j.xinn.2024.100692","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"33 1","pages":""},"PeriodicalIF":32.1,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}