Pub Date : 2023-12-30DOI: 10.1007/s44258-023-00014-y
Jiayu Liao
{"title":"Develop quantitative FRET (qFRET) technology as a high-throughput universal assay platform for basic quantitative biomedical and translational research and development","authors":"Jiayu Liao","doi":"10.1007/s44258-023-00014-y","DOIUrl":"https://doi.org/10.1007/s44258-023-00014-y","url":null,"abstract":"","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139139602","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 : 2023-11-06DOI: 10.1007/s44258-023-00012-0
Hector E. Muñoz, Jonathan Lin, Bonnie G. Yeh, Tridib Biswas, Dino Di Carlo
{"title":"Correction: Fluorescence imaging deformability cytometry: integrating nuclear structure with mechanical phenotyping","authors":"Hector E. Muñoz, Jonathan Lin, Bonnie G. Yeh, Tridib Biswas, Dino Di Carlo","doi":"10.1007/s44258-023-00012-0","DOIUrl":"https://doi.org/10.1007/s44258-023-00012-0","url":null,"abstract":"","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135636477","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 : 2023-10-13DOI: 10.1007/s44258-023-00011-1
Kimberly Seaman, Yu Sun, Lidan You
Abstract Three-dimensional cancer-on-a-chip tissue models aim to replicate the key hallmarks of the tumour microenvironment and allow for the study of dynamic interactions that occur during tumour progression. Recently, complex cancer-on-a-chip models incorporating multiple cell types and biomimetic extracellular matrices have been developed. These models have generated new research directions in engineering and medicine by allowing for the real-time observation of cancer-host cell interactions in a physiologically relevant microenvironment. However, these cancer-on-a-chip models have yet to overcome limitations including the complexity of device manufacturing, the selection of optimal materials for preclinical drug screening studies, long-term microfluidic cell culture as well as associated challenges, and the technical robustness or difficulty in the use of these microfluidic platforms. In this review, an overview of the tumour microenvironment, its unique characteristics, and the recent advances of cancer-on-a-chip models that recapitulate native features of the tumour microenvironment are presented. The current challenges that cancer-on-a-chip models face and the future directions of research that are expected to be seen are also discussed. Graphical Abstract
{"title":"Recent advances in cancer-on-a-chip tissue models to dissect the tumour microenvironment","authors":"Kimberly Seaman, Yu Sun, Lidan You","doi":"10.1007/s44258-023-00011-1","DOIUrl":"https://doi.org/10.1007/s44258-023-00011-1","url":null,"abstract":"Abstract Three-dimensional cancer-on-a-chip tissue models aim to replicate the key hallmarks of the tumour microenvironment and allow for the study of dynamic interactions that occur during tumour progression. Recently, complex cancer-on-a-chip models incorporating multiple cell types and biomimetic extracellular matrices have been developed. These models have generated new research directions in engineering and medicine by allowing for the real-time observation of cancer-host cell interactions in a physiologically relevant microenvironment. However, these cancer-on-a-chip models have yet to overcome limitations including the complexity of device manufacturing, the selection of optimal materials for preclinical drug screening studies, long-term microfluidic cell culture as well as associated challenges, and the technical robustness or difficulty in the use of these microfluidic platforms. In this review, an overview of the tumour microenvironment, its unique characteristics, and the recent advances of cancer-on-a-chip models that recapitulate native features of the tumour microenvironment are presented. The current challenges that cancer-on-a-chip models face and the future directions of research that are expected to be seen are also discussed. Graphical Abstract","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918402","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 : 2023-09-15DOI: 10.1007/s44258-023-00008-w
Hector E. Muñoz, Jonathan Lin, Bonnie G. Yeh, Tridib Biswas, Dino Di Carlo
Abstract Mechanical measurements of cells can provide unique insights into cell state and disease processes. The overall mechanical properties of cells can be heavily affected by the stiffest organelle, the nucleus. However, it is challenging to fully characterize internal nuclear structures in most cell mechanical measurement platforms. Here, we demonstrate single-cell deformability measurements of whole cells and stained nuclei in a fluorescence imaging flow cytometry platform. We also introduce bending energy derived metrics as a way to normalize measurements of cytoskeletal cortex and nuclear shape changes of cells and demonstrate the utility of relative deformability distributions to characterize populations of cells. We apply the platform to measure changes in cell biophysical properties during the process of NETosis, whereby neutrophils undergo drastic nuclear restructuring. We characterize cell size, deformability, and nuclear structure changes and their correlations in thousands of neutrophils undergoing NETosis, a process implicated in development of critical disease states, such as sepsis. This platform can aid in understanding heterogeneity in deformability in cell populations and how this may be influenced by nuclear or internal structure changes. Graphical Abstract
{"title":"Fluorescence imaging deformability cytometry: integrating nuclear structure with mechanical phenotyping","authors":"Hector E. Muñoz, Jonathan Lin, Bonnie G. Yeh, Tridib Biswas, Dino Di Carlo","doi":"10.1007/s44258-023-00008-w","DOIUrl":"https://doi.org/10.1007/s44258-023-00008-w","url":null,"abstract":"Abstract Mechanical measurements of cells can provide unique insights into cell state and disease processes. The overall mechanical properties of cells can be heavily affected by the stiffest organelle, the nucleus. However, it is challenging to fully characterize internal nuclear structures in most cell mechanical measurement platforms. Here, we demonstrate single-cell deformability measurements of whole cells and stained nuclei in a fluorescence imaging flow cytometry platform. We also introduce bending energy derived metrics as a way to normalize measurements of cytoskeletal cortex and nuclear shape changes of cells and demonstrate the utility of relative deformability distributions to characterize populations of cells. We apply the platform to measure changes in cell biophysical properties during the process of NETosis, whereby neutrophils undergo drastic nuclear restructuring. We characterize cell size, deformability, and nuclear structure changes and their correlations in thousands of neutrophils undergoing NETosis, a process implicated in development of critical disease states, such as sepsis. This platform can aid in understanding heterogeneity in deformability in cell populations and how this may be influenced by nuclear or internal structure changes. Graphical Abstract","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352894","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 : 2023-08-24DOI: 10.1007/s44258-023-00010-2
Li Lin, Haoqi He, Ruiyang Xue, Yumin Zhang, Ziwen Wang, S. Nie, Jian Ye
{"title":"Direct and quantitative assessments of near-infrared light attenuation and spectroscopic detection depth in biological tissues using surface-enhanced Raman scattering","authors":"Li Lin, Haoqi He, Ruiyang Xue, Yumin Zhang, Ziwen Wang, S. Nie, Jian Ye","doi":"10.1007/s44258-023-00010-2","DOIUrl":"https://doi.org/10.1007/s44258-023-00010-2","url":null,"abstract":"","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82621461","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 : 2023-07-11DOI: 10.1007/s44258-023-00005-z
Zhi Zhang, Han Wang, Lei Chen, Chensi Cao, Tengwen Liu, Ruifang Ren, Ruixing Zhou, Rudan Huang, D. Hu, Chenxing Zhu, Chong Lu, Yunsheng Xu, Zhaohui Fang, Fuer Lu, Huimin Pan, Yanjin Su, Nanlin Fu, Huixia Zhan, Qin Si, Chenze Bai, Ri Le Ge, Hongmei Cao, Wei Dong, Guohui Yang, Lan Wu, Jiao‐yang Guo, Jing Cheng
{"title":"Noninvasive and affordable type 2 diabetes screening by deep learning-based risk assessment and detection using ophthalmic images inspired by traditional Chinese medicine","authors":"Zhi Zhang, Han Wang, Lei Chen, Chensi Cao, Tengwen Liu, Ruifang Ren, Ruixing Zhou, Rudan Huang, D. Hu, Chenxing Zhu, Chong Lu, Yunsheng Xu, Zhaohui Fang, Fuer Lu, Huimin Pan, Yanjin Su, Nanlin Fu, Huixia Zhan, Qin Si, Chenze Bai, Ri Le Ge, Hongmei Cao, Wei Dong, Guohui Yang, Lan Wu, Jiao‐yang Guo, Jing Cheng","doi":"10.1007/s44258-023-00005-z","DOIUrl":"https://doi.org/10.1007/s44258-023-00005-z","url":null,"abstract":"","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79459067","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 : 2023-07-11DOI: 10.1007/s44258-023-00007-x
Song Li, L. Xu
{"title":"X for medicine: exploration and innovation in biomedical engineering","authors":"Song Li, L. Xu","doi":"10.1007/s44258-023-00007-x","DOIUrl":"https://doi.org/10.1007/s44258-023-00007-x","url":null,"abstract":"","PeriodicalId":74169,"journal":{"name":"Med-X","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80152670","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}
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