Pub Date : 2025-03-27DOI: 10.1016/j.cobme.2025.100589
Peter A. Galie , Paul A. Janmey
Tissues are composites of cells and extracellular matrix that interact with each other both chemically and mechanically to form functioning organs with defined chemical and physical properties. Changes in the physical properties of the extracellular matrix often alter the function of cells, and reciprocally, modified cell function remodels the extracellular matrix in a complex iterative process that mediates normal development, wound healing, and pathological dysfunction. Recent advances in studying how cells and matrix physically interact with each other reveal new aspects of tissue and matrix mechanics and identify potential targets for therapeutic intervention in pathologic settings.
{"title":"Interplay between extracellular matrix mechanics and cell function in mechanobiology","authors":"Peter A. Galie , Paul A. Janmey","doi":"10.1016/j.cobme.2025.100589","DOIUrl":"10.1016/j.cobme.2025.100589","url":null,"abstract":"<div><div>Tissues are composites of cells and extracellular matrix that interact with each other both chemically and mechanically to form functioning organs with defined chemical and physical properties. Changes in the physical properties of the extracellular matrix often alter the function of cells, and reciprocally, modified cell function remodels the extracellular matrix in a complex iterative process that mediates normal development, wound healing, and pathological dysfunction. Recent advances in studying how cells and matrix physically interact with each other reveal new aspects of tissue and matrix mechanics and identify potential targets for therapeutic intervention in pathologic settings.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100589"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-19DOI: 10.1016/j.cobme.2025.100588
Mridu Malik , Stecia A. Steele , Deepshikha Mitra , Christopher J. Long , James J. Hickman
Trans-epithelial/endothelial electrical resistance (TEER) is a non-invasive and quick method of assessing the integrity of barrier tissues. Traditional TEER measurement methods such as chopstick electrode-based and chamber-based measurements work well with static, Transwell-based models; however, the same methods do not directly apply to human-on-a-chip or organ-on-a-chip (OOC) platforms. With the wide variety of organ-on-a-chip devices, innovative designs to accurately measure TEER, without disturbing cells, are customized for various devices. Wire electrode integration, integrating a two-probe or four-probe technique, flexible printed circuit boards or multi-electrode glass substrate-based methods are some of the TEER measurement setups being utilized in conjunction with OOC systems. The variability in measurement setups associated with OOCs make standardization challenging; however, the field is working towards establishing guidelines on acceptable TEER values for different OOC constructs.
{"title":"Trans-epithelial/endothelial electrical resistance (TEER): Current state of integrated TEER measurements in organ-on-a-chip devices","authors":"Mridu Malik , Stecia A. Steele , Deepshikha Mitra , Christopher J. Long , James J. Hickman","doi":"10.1016/j.cobme.2025.100588","DOIUrl":"10.1016/j.cobme.2025.100588","url":null,"abstract":"<div><div>Trans-epithelial/endothelial electrical resistance (TEER) is a non-invasive and quick method of assessing the integrity of barrier tissues. Traditional TEER measurement methods such as chopstick electrode-based and chamber-based measurements work well with static, Transwell-based models; however, the same methods do not directly apply to human-on-a-chip or organ-on-a-chip (OOC) platforms. With the wide variety of organ-on-a-chip devices, innovative designs to accurately measure TEER, without disturbing cells, are customized for various devices. Wire electrode integration, integrating a two-probe or four-probe technique, flexible printed circuit boards or multi-electrode glass substrate-based methods are some of the TEER measurement setups being utilized in conjunction with OOC systems. The variability in measurement setups associated with OOCs make standardization challenging; however, the field is working towards establishing guidelines on acceptable TEER values for different OOC constructs.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100588"},"PeriodicalIF":4.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-06DOI: 10.1016/j.cobme.2025.100587
Alejandro Forigua , Benjamin E. Campbell , Christopher Moraes
Mechanical features of tissues have been recognised as key drivers of disease progression and are increasingly investigated as diagnostic and therapeutic targets. Engineered tissue models with integrated embedded biomechanical sensors have recently uncovered complex mechanical behaviors across micro- and nanoscale environments, offering novel insights into developmental and disease mechanisms. This short opinion synthesizes emerging mechanical signatures that have been identified at high measurement sensitivities and spatial resolutions by embedding customized biomechanical sensors into engineered tissues, particularly for soft tissue pathologies like cancer and fibrosis. We then describe the challenges of achieving these increased resolutions in clinical practice, and highlight recent innovative strategies that may ultimately bridge these gaps. If successful, these improved biomechanical measurement systems could open new pathways for improving diagnostics and patient outcomes.
{"title":"Emerging views of biomechanics via embedded sensors in model tissues: Pathways to the clinic","authors":"Alejandro Forigua , Benjamin E. Campbell , Christopher Moraes","doi":"10.1016/j.cobme.2025.100587","DOIUrl":"10.1016/j.cobme.2025.100587","url":null,"abstract":"<div><div>Mechanical features of tissues have been recognised as key drivers of disease progression and are increasingly investigated as diagnostic and therapeutic targets. Engineered tissue models with integrated embedded biomechanical sensors have recently uncovered complex mechanical behaviors across micro- and nanoscale environments, offering novel insights into developmental and disease mechanisms. This short opinion synthesizes emerging mechanical signatures that have been identified at high measurement sensitivities and spatial resolutions by embedding customized biomechanical sensors into engineered tissues, particularly for soft tissue pathologies like cancer and fibrosis. We then describe the challenges of achieving these increased resolutions in clinical practice, and highlight recent innovative strategies that may ultimately bridge these gaps. If successful, these improved biomechanical measurement systems could open new pathways for improving diagnostics and patient outcomes.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100587"},"PeriodicalIF":4.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-04DOI: 10.1016/j.cobme.2025.100586
Marc Vila Cuenca , Merve Bulut , Christine L. Mummery , Valeria V. Orlova
Generation of functional vasculature within organoids is considered important for their development and maturation. However, direct differentiation of endothelial cells (ECs) in organoids remains challenging so that creating fully perfusable vasculature often still requires transplantation into host animals. This review discusses recent strategies for generating pre-vascularized human pluripotent stem cell (hPSC)-derived organoids, that include co-differentiation of ECs using growth factors or (an inducible transcription factor) ETV2, controlled assembly of tissue organoids with hPSC-derived ECs or Blood Vessel Organoids (BVOs), and 3D bioprinting. Additionally, the potential and key challenges of organ-on-chip technology for creating perfusable and functional vascular networks in organoids are explored, highlighting their implications for advancing research and improving experimental models of human tissue and disease.
{"title":"Vascularization of organoid microenvironments: Perfusable networks for organoid growth and maturation","authors":"Marc Vila Cuenca , Merve Bulut , Christine L. Mummery , Valeria V. Orlova","doi":"10.1016/j.cobme.2025.100586","DOIUrl":"10.1016/j.cobme.2025.100586","url":null,"abstract":"<div><div>Generation of functional vasculature within organoids is considered important for their development and maturation. However, direct differentiation of endothelial cells (ECs) in organoids remains challenging so that creating fully perfusable vasculature often still requires transplantation into host animals. This review discusses recent strategies for generating pre-vascularized human pluripotent stem cell (hPSC)-derived organoids, that include co-differentiation of ECs using growth factors or (an inducible transcription factor) ETV2, controlled assembly of tissue organoids with hPSC-derived ECs or Blood Vessel Organoids (BVOs), and 3D bioprinting. Additionally, the potential and key challenges of organ-on-chip technology for creating perfusable and functional vascular networks in organoids are explored, highlighting their implications for advancing research and improving experimental models of human tissue and disease.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100586"},"PeriodicalIF":4.7,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-21DOI: 10.1016/j.cobme.2025.100583
Sophia Epstein , Joshua Chang , Daniel Johnston , David Paydarfar
Exogenous electrical stimulation of peripheral nerves preferentially activates the larger diameter fibers due to the lower applied current (or voltage) needed for their activation. However, the ability to selectively stimulate small fibers, and sparing large fibers, would have an important role in clinical applications. This review elucidates the biophysical basis and clinical significance of achieving fiber size-specific recruitment in neuromodulation therapies. We evaluate various methodologies designed to modulate recruitment patterns, including spatial electrical modulation techniques such as electrode configuration and field shaping, temporal modulation strategies involving pulse parameter adjustments. Other neuromodulating technologies are reviewed, including focused ultrasound, optogenetics, and chemogenetics. We discuss the limitations of current techniques and directions for future research to enhance the precision of nerve fiber recruitment, thereby optimizing therapeutic efficacy.
{"title":"Size principles governing selective neuromodulation and recruitment order of nerve fibers","authors":"Sophia Epstein , Joshua Chang , Daniel Johnston , David Paydarfar","doi":"10.1016/j.cobme.2025.100583","DOIUrl":"10.1016/j.cobme.2025.100583","url":null,"abstract":"<div><div>Exogenous electrical stimulation of peripheral nerves preferentially activates the larger diameter fibers due to the lower applied current (or voltage) needed for their activation. However, the ability to selectively stimulate small fibers, and sparing large fibers, would have an important role in clinical applications. This review elucidates the biophysical basis and clinical significance of achieving fiber size-specific recruitment in neuromodulation therapies. We evaluate various methodologies designed to modulate recruitment patterns, including spatial electrical modulation techniques such as electrode configuration and field shaping, temporal modulation strategies involving pulse parameter adjustments. Other neuromodulating technologies are reviewed, including focused ultrasound, optogenetics, and chemogenetics. We discuss the limitations of current techniques and directions for future research to enhance the precision of nerve fiber recruitment, thereby optimizing therapeutic efficacy.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100583"},"PeriodicalIF":4.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-10DOI: 10.1016/j.cobme.2025.100581
Aining Fan , Erick Alvarado , Anton Block , Lingyan Shi
Label-free imaging techniques, with their nondestructive, dye-free operation, and broad detection capabilities, have rapidly advanced and found application in biological tissue analysis. The integration of multimodal label-free imaging technologies has gained significant attention as it enables the acquisition of diverse molecular information from multiple sources while overcoming the limitations associated with conventional single-modality approaches. In this review, we examine several key label-free optical imaging technologies and their recent applications. We also discuss innovative multimodal imaging platforms, along with current advancements, limitations, and prospects in the field of label-free imaging.
{"title":"A mini review of quantitative optical technologies for imaging cell and tissue metabolism","authors":"Aining Fan , Erick Alvarado , Anton Block , Lingyan Shi","doi":"10.1016/j.cobme.2025.100581","DOIUrl":"10.1016/j.cobme.2025.100581","url":null,"abstract":"<div><div>Label-free imaging techniques, with their nondestructive, dye-free operation, and broad detection capabilities, have rapidly advanced and found application in biological tissue analysis. The integration of multimodal label-free imaging technologies has gained significant attention as it enables the acquisition of diverse molecular information from multiple sources while overcoming the limitations associated with conventional single-modality approaches. In this review, we examine several key label-free optical imaging technologies and their recent applications. We also discuss innovative multimodal imaging platforms, along with current advancements, limitations, and prospects in the field of label-free imaging.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100581"},"PeriodicalIF":4.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-03DOI: 10.1016/j.cobme.2025.100582
Zahra Rezaei , Niyou Wang , Alan De Jesus Alarcon Rodriguez , Shougo Higashi , Su Ryon Shin
Biosensing technology is essential for advancing biomedical research, enabling real-time, continuous monitoring of biomarkers to deepen our understanding of cellular and tissue behaviors within their environments. This review categorizes sensors as intracellular or extracellular types and discusses the integration of various biosensors into in vitro models. Special focus is given to electrochemical biosensors for their precision, potential for miniaturization, quantitative sensitivity, and real-time detection capabilities. We discuss how biosensors are transforming fields such as cancer research, toxicology, neuroscience, cardiovascular studies, and tissue regeneration. Biosensors play a significant role in disease modeling, drug testing, and smart wound healing systems, where continuous, non-invasive monitoring supports personalized therapeutic strategies and creates new possibilities for large-scale biofabrication. Importantly, biosensors operate in direct contact with cells or tissue, thus preserving tissue integrity during development. Integrating biosensors into in vitro models allows researchers to monitor physiological behavior, bridging critical gaps between laboratory studies and clinical applications.
{"title":"Biosensors in biomedical research: Bridging cell and tissue engineering and real-time monitoring","authors":"Zahra Rezaei , Niyou Wang , Alan De Jesus Alarcon Rodriguez , Shougo Higashi , Su Ryon Shin","doi":"10.1016/j.cobme.2025.100582","DOIUrl":"10.1016/j.cobme.2025.100582","url":null,"abstract":"<div><div>Biosensing technology is essential for advancing biomedical research, enabling real-time, continuous monitoring of biomarkers to deepen our understanding of cellular and tissue behaviors within their environments. This review categorizes sensors as intracellular or extracellular types and discusses the integration of various biosensors into <em>in vitro</em> models. Special focus is given to electrochemical biosensors for their precision, potential for miniaturization, quantitative sensitivity, and real-time detection capabilities. We discuss how biosensors are transforming fields such as cancer research, toxicology, neuroscience, cardiovascular studies, and tissue regeneration. Biosensors play a significant role in disease modeling, drug testing, and smart wound healing systems, where continuous, non-invasive monitoring supports personalized therapeutic strategies and creates new possibilities for large-scale biofabrication. Importantly, biosensors operate in direct contact with cells or tissue, thus preserving tissue integrity during development. Integrating biosensors into <em>in vitro</em> models allows researchers to monitor physiological behavior, bridging critical gaps between laboratory studies and clinical applications.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100582"},"PeriodicalIF":4.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-03DOI: 10.1016/j.cobme.2025.100580
Mahima Choudhury , Annika J. Deans , Daniel R. Candland , Tara L. Deans
Artificial intelligence provides an exciting avenue to improve approaches in cell therapies by learning and predicting dynamic gene expression patterns from large datasets of stem cell differentiation. The integration of synthetic biology provides genetic tools that mimic the spatial and temporal expression patterns during differentiation, enhancing the potential to significantly improve differentiation outcomes and further our understanding of the mechanisms involved during cell fate decisions.
{"title":"Advancing cell therapies with artificial intelligence and synthetic biology","authors":"Mahima Choudhury , Annika J. Deans , Daniel R. Candland , Tara L. Deans","doi":"10.1016/j.cobme.2025.100580","DOIUrl":"10.1016/j.cobme.2025.100580","url":null,"abstract":"<div><div>Artificial intelligence provides an exciting avenue to improve approaches in cell therapies by learning and predicting dynamic gene expression patterns from large datasets of stem cell differentiation. The integration of synthetic biology provides genetic tools that mimic the spatial and temporal expression patterns during differentiation, enhancing the potential to significantly improve differentiation outcomes and further our understanding of the mechanisms involved during cell fate decisions.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100580"},"PeriodicalIF":4.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.cobme.2025.100579
Kylee North , Sonny T. Jones , Grange M. Simpson , Ashley N. Dalrymple
Lumbosacral spinal cord stimulation shows promise in restoring walking after spinal cord injury. This review discusses recently developed machine learning approaches to provide customized stimulation patterns and parameters according to the extent of injury to achieve community ambulation. Key challenges include the need for control strategies that enhance residual limb function and adapt to variable motor impairments across individuals. Efficient identification of optimal stimulation parameters and the ability to adapt parameters over time without manual tuning is essential for long-term use upon clinical translation of spinal cord stimulation therapies for rehabilitation. Machine learning provides the necessary framework for personalized rehabilitation treatment by offering a flexible architecture that evolves and adapts automatically to suit individual patient rehabilitation needs and preferences.
{"title":"Personalized gait rehabilitation with spinal cord stimulation and machine learning: Recent advances and promising applications","authors":"Kylee North , Sonny T. Jones , Grange M. Simpson , Ashley N. Dalrymple","doi":"10.1016/j.cobme.2025.100579","DOIUrl":"10.1016/j.cobme.2025.100579","url":null,"abstract":"<div><div>Lumbosacral spinal cord stimulation shows promise in restoring walking after spinal cord injury. This review discusses recently developed machine learning approaches to provide customized stimulation patterns and parameters according to the extent of injury to achieve community ambulation. Key challenges include the need for control strategies that enhance residual limb function and adapt to variable motor impairments across individuals. Efficient identification of optimal stimulation parameters and the ability to adapt parameters over time without manual tuning is essential for long-term use upon clinical translation of spinal cord stimulation therapies for rehabilitation. Machine learning provides the necessary framework for personalized rehabilitation treatment by offering a flexible architecture that evolves and adapts automatically to suit individual patient rehabilitation needs and preferences.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100579"},"PeriodicalIF":4.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-20DOI: 10.1016/j.cobme.2025.100578
Lingyu Sun , Yile Fang , Yu Wang , Feika Bian , Yuanjin Zhao
As an emerging modeling platform for cardiac cells and tissues, heart-on-a-chip systems have aroused great interest and made remarkable progress in recent decades. To expand the practical values of such microphysiological systems, various biosensing modules have been integrated into microfluidic chips to realize real-time monitoring of cardiomyocytes or cardiac tissues under different stimulations. Among them, photonic crystal colorimetric sensors are popular because of their intrinsic biocompatibility, visual characteristics, and lack of need for complex instrumentation. In this review, we will provide an overview of research concerning heart-on-a-chip systems integrated with photonic crystal colorimetric sensors, ranging from the natural structural colors, the fabrication of artificial photonic crystal materials, to their colorimetric sensing principle. The emphasis will be put on how the photonic crystal colorimetric sensors address the current limitations of heart-on-a-chip systems through visual optical signals and thus expand their biomedical applications. Finally, the remaining challenges of colorimetric sensing strategy will be summarized, with its future directions for organs-on-chips being discussed.
{"title":"Photonic crystal colorimetric sensing in heart-on-a-chip systems","authors":"Lingyu Sun , Yile Fang , Yu Wang , Feika Bian , Yuanjin Zhao","doi":"10.1016/j.cobme.2025.100578","DOIUrl":"10.1016/j.cobme.2025.100578","url":null,"abstract":"<div><div>As an emerging modeling platform for cardiac cells and tissues, heart-on-a-chip systems have aroused great interest and made remarkable progress in recent decades. To expand the practical values of such microphysiological systems, various biosensing modules have been integrated into microfluidic chips to realize real-time monitoring of cardiomyocytes or cardiac tissues under different stimulations. Among them, photonic crystal colorimetric sensors are popular because of their intrinsic biocompatibility, visual characteristics, and lack of need for complex instrumentation. In this review, we will provide an overview of research concerning heart-on-a-chip systems integrated with photonic crystal colorimetric sensors, ranging from the natural structural colors, the fabrication of artificial photonic crystal materials, to their colorimetric sensing principle. The emphasis will be put on how the photonic crystal colorimetric sensors address the current limitations of heart-on-a-chip systems through visual optical signals and thus expand their biomedical applications. Finally, the remaining challenges of colorimetric sensing strategy will be summarized, with its future directions for organs-on-chips being discussed.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100578"},"PeriodicalIF":4.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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