Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100020
Rong-Rong Lin, Hui-Fen Huang, Qing-Qing Tao
clinical symptoms in AD patients.
AD患者的临床症状。
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100023
Wenjing Zhang, Yongfeng Lu, Chenyi Su, Yibo Wang, Yong-Fei Wang, Bo Zhang, Cheng Jiang, Keying Guo, Chuan Xu
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.
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100017
Yao Wu, D. Gasevic, Bo Wen, P. Yu, R. Xu, Guowei Zhou, Yan Zhang, Jiangning Song, Hong Liu, Shanshan Li, Yuming Guo
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.
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100019
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
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.
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100018
Qiao Li, Mingxia Jiang, Bing-he Xu
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.
抗体药物偶联物(Antibody drug conjugate, ADC)通过连接体将单克隆抗体的高特异性和小分子细胞毒药物的高活性结合起来，提高肿瘤药物的靶向性，减少毒副作用。adc因其靶点明确、技术成熟、选择性好等优点，在血液学和实体肿瘤治疗领域显示出良好的应用前景。从这个角度出发，本文将adc靶向抗原的选择分为驱动基因靶向抗原和非驱动基因靶向抗原两组，进一步说明靶向抗原在推进adc肿瘤治疗中的重要性。未来，这一领域的持续研究和创新将有助于为癌症患者提供更有效、更有针对性和更个性化的治疗方法，最终改善患者的预后和生活质量。
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100006
Jianhong Dong, Ying Wang
{"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}
Pub Date : 1900-01-01DOI: 10.59717/j.xinn-med.2023.100004
Rongrong Song, Jiuyang Xu, B. Cao
{"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：