The Innovation Medicine最新文献

{"title":"High self-healing rate of oral ranula: A prospective study","authors":"Yunan Liu, Lin Wang, Yidan Zhu, Lin Lan, Diancang Wang","doi":"10.59717/j.xinn-med.2023.100011","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100011","url":null,"abstract":"","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125171614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing the battle against Alzheimer's Disease: a focus on targeting tau pathology by antisense oligonucleotide","authors":"Rong-Rong Lin, Hui-Fen Huang, Qing-Qing Tao","doi":"10.59717/j.xinn-med.2023.100020","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100020","url":null,"abstract":"clinical symptoms in AD patients.","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115083637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confinement-guided ultrasensitive optical assay with artificial intelligence for disease diagnostics","authors":"Wenjing Zhang, Yongfeng Lu, Chenyi Su, Yibo Wang, Yong-Fei Wang, Bo Zhang, Cheng Jiang, Keying Guo, Chuan Xu","doi":"10.59717/j.xinn-med.2023.100023","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100023","url":null,"abstract":"The necessity for ultrasensitive detection is becoming increasingly apparent as it plays a pivotal role in disease early diagnostics and health management, particularly when it comes to detecting and monitoring low-abundance biomarkers or precious samples with tiny volumes. In many disease cases, such as cancer, infectious disease, autoimmune disorder, and neurodegenerative disease, low-abundant target biomarkers like circulating tumor cells (CTCs), extracellular vesicle (EV) subpopulations, and post-translational modified proteins (PTMs) are commonly existing and can be served as early indicators of disease onset or progression. However, these biomarkers often exist in ultra-low quantities in body fluids, surpassing the detection limits of conventional diagnostic tools like enzyme-linked immunosorbent assay (ELISA). This leads to the inability to probe disease evolution at a very early stage from molecular pathology perspective. In such regard, ultrasensitive optical assays have emerged as a solution to overcome these limitations and have witnessed significant progress in recent decades. This review provides a comprehensive overview of the recent advancements in ultrasensitive optical detection for disease diagnostics, particularly focusing on the conjunction of confinement within micro-/nano-structures and signal amplification to generate distinguishable optical readouts. The discussion begins with a meticulous evaluation of the advantages and disadvantages of these ultra-sensitive optical assays. Then, the spotlight is turned towards the implementation of artificial intelligence (AI) algorithms. The ability of AI to process large volumes of visible reporter signal and clinical data has proven invaluable in identifying unique patterns across multi-center cohort samples. Looking forward, the review underscores future advancements in developing convergent biotechnology (BT) and information technology (IT) toolbox, especially optical biosensors for high-throughput biomarker screening, point-of-care (PoC) testing with appropriate algorithms for their clinical translation are highlighted.\u0000","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127616845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between air pollution and telomere length: A study of 471,808 UK Biobank participants","authors":"Yao Wu, D. Gasevic, Bo Wen, P. Yu, R. Xu, Guowei Zhou, Yan Zhang, Jiangning Song, Hong Liu, Shanshan Li, Yuming Guo","doi":"10.59717/j.xinn-med.2023.100017","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100017","url":null,"abstract":"Previous research suggested an association between air pollution and shortened telomere length (TL), a biomarker of oxidative stress and inflammation. However, supporting results are challenged by the small sample size and heterogeneity in participant characteristics. To comprehensively evaluate the association of long-term exposure to air pollution with telomere length, we studied 471,808 participants from UK Biobank with measurements on leukocyte telomere length (LTL). Air pollution data on PM2.5, PM10, NO2, NOx, SO2, and CO before baseline at 1 km spatial resolution were collected and linked to each participant��s residential address. We applied mixed-effects linear regression models to examine the association between long-term air pollution exposure and LTL. Compared to the lowest quartile (Q1) of air pollutants, the estimated percentage changes of age-corrected LTL were -2.71% [95% confidence interval (CI): -3.78, -1.63] for SO2, -0.82% (95% CI: -1.87, 0.23) for NO2, -1.17% (95% CI: -2.23, -0.11) for NOx, and -0.47% (95% CI: -1.45, 0.53) for CO in the highest quartile groups (Q4). Decreasing trends in age-corrected LTL following the increase in PM2.5 and PM10 leveled off during high levels of air pollutants. Among participants with lower household income, lower educational attainment, and higher BMI, a stronger association was found between air pollution and LTL. Our findings suggest a negative association between air pollution and LTL and provide insights into the potential pathways linking air pollution to age-related diseases.\u0000","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129375623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced prompting as a catalyst: Empowering large language models in the management of gastrointestinal cancers","authors":"J. Yuan, Peng Bao, Zi Chen, Mingze Yuan, Jie Zhao, Jiahua Pan, Yi Xie, Yanshuo Cao, Yakun Wang, Zhenghang Wang, Zhihao Lu, Xiaotian Zhang, Jian Li, Lei Ma, Yang Chen, Li Zhang, Lin Shen, Bin Dong","doi":"10.59717/j.xinn-med.2023.100019","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100019","url":null,"abstract":"Large Language Models' (LLMs) performance in healthcare can be significantly impacted by prompt engineering. However, the area of study remains relatively uncharted in gastrointestinal oncology until now. Our research delves into this unexplored territory, investigating the efficacy of varied prompting strategies, including simple prompts, templated prompts, in-context learning (ICL), and multi-round iterative questioning, for optimizing the performance of LLMs within a medical setting. We develop a comprehensive evaluation system to assess the performance of LLMs across multiple dimensions. This robust evaluation system ensures a thorough assessment of the LLMs' capabilities in the field of medicine. Our findings suggest a positive relationship between the comprehensiveness of the prompts and the LLMs' performance. Notably, the multi-round strategy, which is characterized by iterative question-and-answer rounds, consistently yields the best results. ICL, a strategy that capitalizes on interrelated contextual learning, also displays significant promise, surpassing the outcomes achieved with simpler prompts. The research underscores the potential of advanced prompt engineering and iterative learning approaches for boosting the applicability of LLMs in healthcare. We recommend that additional research be conducted to refine these strategies and investigate their potential integration, to truly harness the full potential of LLMs in medical applications.\u0000","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124630378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Win-win cooperation for advancing medical innovation","authors":"Jie Qiao","doi":"10.59717/j.xinn-med.2023.100002","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100002","url":null,"abstract":"Peking University Health Science Center, Beijing 100191, China *Correspondence: Jie Qiao: jie.qiao@263.net Received: May 5, 2023; Accepted: May 29, 2023; Published Online: June 6, 2023; https://doi.org/10.59717/j.xinn-med.2023.100002 © 2023 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Citation: Qiao J. (2023). Win-win cooperation for advancing medical innovation. The Innovation Medicine 1(1), 100002. Scientific and technological advancements in medicine have always been highly esteemed worldwide. According to statistics published by the Organization for Economic Cooperation and Development (OECD), global health spending accounted for 9.6% of GDP in 2021. Research and development expenses incurred in “health and environmental projects” comprised 30% to 50% of the total R&D funds available in major developed countries such as the United States and the United Kingdom in 2019. . Novel scientific and technological advancements in medicine will be key areas for innovation and capital investments globally over the next 30 years. These medical innovations are expected to generate new preventative, diagnostic, and treatment methods, as well as health monitoring techniques, new drugs, and devices for managing diseases. These advancements in medicine will not only accelerate existing medical and commercial processes to address people’s ever-changing health demands but also enhance the ability to respond effectively to future emergencies, such as pandemics. Ultimately, the benefits will extend to the entire global community. Achieving this goal requires global cooperation across all levels: governments, medical companies, hospitals, and scientific research institutes must collaborate to create a favorable ecosystem for medical innovation. Governments and companies must partner to tackle the critical challenge of ensuring that innovative products benefit as many individuals as possible.","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121631819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics: Advancing biomedical discovery and innovation in the era of big data and artificial intelligence","authors":"Yuan Liu, Ya-Min Chen, Leng Han","doi":"10.59717/j.xinn-med.2023.100012","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100012","url":null,"abstract":"Brown Center for Immunotherapy, School of Medicine, Indiana University, Indianapolis, IN 46202, USA *Correspondence: yl218@iu.edu (Y.L.); lenghan@iu.edu (L.H.) Received: April 12, 2023; Accepted: May 16, 2023; Published Online: May 28, 2023; https://doi.org/10.59717/j.xinn-med.2023.100012 © 2023 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Citation: Liu Y., Chen Y., and Han L. (2023). Bioinformatics: Advancing biomedical discovery and innovation in the era of big data and artificial intelligence. The Innovation Medicine 1(1), 100012. Bioinformatics made significant progress in generating, analyzing, and interpreting vast amounts of biological data in the past decades. Challenged by the vast amount of data collected from diverse sources, bioinformatics research powered by artificial intelligence has led to novel insights into the field of biomedicine and will continue to drive further discoveries.","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122138442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new perspective in the research of antibody drug conjugate","authors":"Qiao Li, Mingxia Jiang, Bing-he Xu","doi":"10.59717/j.xinn-med.2023.100018","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100018","url":null,"abstract":"Antibody drug conjugate (ADC) combines the high specificity of monoclonal antibodies and the high activity of small molecule cytotoxic drugs through linkers to improve the targeting of tumor drugs and reduce the toxic side effects. Due to the advantages of clear targets, mature technology, and good selectivity, ADCs have shown excellent application prospects in hematological and solid tumor therapeutic fields. In this perspective, the selection of ADC-targeting antigens is described in the group of driver gene target antigens and non-driver gene target antigens to make more evident the importance of targeting antigens in advancing ADCs for tumor therapy. In the future, continued research and innovation in this field will help provide more effective, targeted, and personalized treatments for cancer patients, ultimately improving patients�� outcomes and quality of life.\u0000","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"162 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114099022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lilly's Donanemab, will it be the light at the end of the tunnel?","authors":"Jianhong Dong, Ying Wang","doi":"10.59717/j.xinn-med.2023.100006","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100006","url":null,"abstract":"","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123587989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 Pandemic: End of emergency, but not end of challenge","authors":"Rongrong Song, Jiuyang Xu, B. Cao","doi":"10.59717/j.xinn-med.2023.100004","DOIUrl":"https://doi.org/10.59717/j.xinn-med.2023.100004","url":null,"abstract":"","PeriodicalId":423184,"journal":{"name":"The Innovation Medicine","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131529516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}