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}
Pub Date : 2025-01-20DOI: 10.1016/j.cobme.2025.100577
Liam A. Matthews , Scott F. Lempka
Chronic pain is a leading cause of disability worldwide. Bioelectronic treatments for chronic pain are a class of therapies that apply electrical or magnetic stimuli to the nervous system to mitigate pain. In light of the opioid crisis, these strategies have garnered significant investment in recent years due to their ability to provide non-addictive pain relief. Despite remarkable success in some patients, the majority of bioelectronic approaches are typically recommended as a last-resort therapy due to their high cost, invasiveness, and limited evidence of long-term efficacy. Furthermore, these therapies are not a panacea for many patients, often providing clinically meaningful, but incomplete pain relief. Thus, there is substantial room for improvement and innovation to both increase therapeutic efficacy and develop novel strategies and devices that enable utilization of bioelectronic therapies earlier in the chronic pain treatment continuum. Here, we review recent advances to bioelectronic treatments for chronic pain.
{"title":"Bioelectronic therapies for chronic pain","authors":"Liam A. Matthews , Scott F. Lempka","doi":"10.1016/j.cobme.2025.100577","DOIUrl":"10.1016/j.cobme.2025.100577","url":null,"abstract":"<div><div>Chronic pain is a leading cause of disability worldwide. Bioelectronic treatments for chronic pain are a class of therapies that apply electrical or magnetic stimuli to the nervous system to mitigate pain. In light of the opioid crisis, these strategies have garnered significant investment in recent years due to their ability to provide non-addictive pain relief. Despite remarkable success in some patients, the majority of bioelectronic approaches are typically recommended as a last-resort therapy due to their high cost, invasiveness, and limited evidence of long-term efficacy. Furthermore, these therapies are not a panacea for many patients, often providing clinically meaningful, but incomplete pain relief. Thus, there is substantial room for improvement and innovation to both increase therapeutic efficacy and develop novel strategies and devices that enable utilization of bioelectronic therapies earlier in the chronic pain treatment continuum. Here, we review recent advances to bioelectronic treatments for chronic pain.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"34 ","pages":"Article 100577"},"PeriodicalIF":4.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377808","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 : 2025-01-08DOI: 10.1016/j.cobme.2025.100576
Allan Sun , Arian Nasser , Nicole Alexis Yap , Rui Gao , Lining Arnold Ju
Arterial thrombosis remains a significant global health concern, with shear-induced platelet aggregation (SIPA) playing a crucial role. This review focuses on the integration of three key engineering approaches—Computational Modeling Microfluidics and Mechanobiology (3 M)—in understanding and combating high-shear thrombosis. We discuss the biomechanical mechanisms of SIPA, highlighting how platelet mechanoreceptors and von Willebrand factor interactions drive thrombosis under pathological flow conditions. Through computational fluid dynamics (CFD), key hemodynamic metrics including time-averaged wall shear stress, oscillatory shear index, and relative residence time have been developed to predict thrombosis risk. Microfluidic platforms, ranging from straight channels to stenotic geometries, provide insights into platelet behavior under various shear conditions while enabling rapid screening of antithrombotic therapies. The integration of these experimental approaches with CFD analysis offers powerful tools for predicting thrombosis risk and optimizing device designs, particularly in mechanical circulatory support devices (MCSDs). Recent advances in mechanobiology have revealed how mechanical forces trigger cellular responses through membrane damage and mechanosensitive channels, offering new therapeutic targets. This review underscores how the synergy between these 3 M engineering approaches advances our understanding of the complex interplay between hemodynamics and thrombosis, paving the way for improved antithrombotic therapies and medical device designs essential to optimizing MCSDs, such as left ventricular assist devices and extracorporeal membrane oxygenators.
{"title":"3M engineering approaches to combat high-shear thrombosis: Integrating modeling, microfluidics, and mechanobiology","authors":"Allan Sun , Arian Nasser , Nicole Alexis Yap , Rui Gao , Lining Arnold Ju","doi":"10.1016/j.cobme.2025.100576","DOIUrl":"10.1016/j.cobme.2025.100576","url":null,"abstract":"<div><div>Arterial thrombosis remains a significant global health concern, with shear-induced platelet aggregation (SIPA) playing a crucial role. This review focuses on the integration of three key engineering approaches—Computational Modeling Microfluidics and Mechanobiology (3 M)—in understanding and combating high-shear thrombosis. We discuss the biomechanical mechanisms of SIPA, highlighting how platelet mechanoreceptors and von Willebrand factor interactions drive thrombosis under pathological flow conditions. Through computational fluid dynamics (CFD), key hemodynamic metrics including time-averaged wall shear stress, oscillatory shear index, and relative residence time have been developed to predict thrombosis risk. Microfluidic platforms, ranging from straight channels to stenotic geometries, provide insights into platelet behavior under various shear conditions while enabling rapid screening of antithrombotic therapies. The integration of these experimental approaches with CFD analysis offers powerful tools for predicting thrombosis risk and optimizing device designs, particularly in mechanical circulatory support devices (MCSDs). Recent advances in mechanobiology have revealed how mechanical forces trigger cellular responses through membrane damage and mechanosensitive channels, offering new therapeutic targets. This review underscores how the synergy between these 3 M engineering approaches advances our understanding of the complex interplay between hemodynamics and thrombosis, paving the way for improved antithrombotic therapies and medical device designs essential to optimizing MCSDs, such as left ventricular assist devices and extracorporeal membrane oxygenators.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"33 ","pages":"Article 100576"},"PeriodicalIF":4.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098676","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 : 2024-12-20DOI: 10.1016/j.cobme.2024.100575
Alex Baldwin , Gregory States , Victor Pikov , Pallavi Gunalan , Sahar Elyahoodayan , Kevin Kilgore , Ellis Meng
Bioelectronic medicine is a growing field which involves directly interfacing with the vagus, sacral, enteric, and other autonomic nerves to treat conditions. Therapies based on bioelectronic medicine could address previously intractable diseases and provide an alternative to pharmaceuticals. However, translating a bioelectronic medicine therapy to the clinic requires overcoming several challenges, including titrating stimulation parameters to an individual's physiology, selectively stimulating target nerves without inducing off-target activation or block, and improving accessibility to clinically approved devices. This review describes recent progress towards solving these problems, including advances in mapping and characterizing the human autonomic nervous system, new sensor technology and signal processing techniques to enable closed-loop therapies, new methods for selectively stimulating autonomic nerves without inducing off-target effects, and efforts to develop open-source implantable devices. Recent commercial successes in bringing bioelectronic medicine therapies to the clinic are highlighted showing how addressing these challenges can lead to novel therapies.
{"title":"Recent advances in facilitating the translation of bioelectronic medicine therapies","authors":"Alex Baldwin , Gregory States , Victor Pikov , Pallavi Gunalan , Sahar Elyahoodayan , Kevin Kilgore , Ellis Meng","doi":"10.1016/j.cobme.2024.100575","DOIUrl":"10.1016/j.cobme.2024.100575","url":null,"abstract":"<div><div>Bioelectronic medicine is a growing field which involves directly interfacing with the vagus, sacral, enteric, and other autonomic nerves to treat conditions. Therapies based on bioelectronic medicine could address previously intractable diseases and provide an alternative to pharmaceuticals. However, translating a bioelectronic medicine therapy to the clinic requires overcoming several challenges, including titrating stimulation parameters to an individual's physiology, selectively stimulating target nerves without inducing off-target activation or block, and improving accessibility to clinically approved devices. This review describes recent progress towards solving these problems, including advances in mapping and characterizing the human autonomic nervous system, new sensor technology and signal processing techniques to enable closed-loop therapies, new methods for selectively stimulating autonomic nerves without inducing off-target effects, and efforts to develop open-source implantable devices. Recent commercial successes in bringing bioelectronic medicine therapies to the clinic are highlighted showing how addressing these challenges can lead to novel therapies.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"33 ","pages":"Article 100575"},"PeriodicalIF":4.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143081120","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}
Artificial scaffolds are indispensable tools in unraveling the complexity of mechanobiology under controlled conditions. Recent breakthroughs in microfabrication techniques for biological applications have revolutionized the field, enabling well-defined features that span from the subcellular to the multicellular scale. These methods particularly allow for unprecedented control of cell stimulation. This review will showcase research that combines such scaffolds with various stimulation techniques: mechanical stimulation, actuation by magnetic or electric fields, chemical stimulation, or manipulation by light. Additionally, it will introduce passive scaffolds that are actuated by the cells themselves. These systems help to understand forces applied by the cells to their environment and pave the way toward dynamic biohybrid, cell-based systems.
{"title":"3D fabrication of artificial cell microenvironments for mechanobiology","authors":"Annabelle Sonn , Caterina Tomba , Christine Selhuber-Unkel , Barbara Schamberger","doi":"10.1016/j.cobme.2024.100574","DOIUrl":"10.1016/j.cobme.2024.100574","url":null,"abstract":"<div><div>Artificial scaffolds are indispensable tools in unraveling the complexity of mechanobiology under controlled conditions. Recent breakthroughs in microfabrication techniques for biological applications have revolutionized the field, enabling well-defined features that span from the subcellular to the multicellular scale. These methods particularly allow for unprecedented control of cell stimulation. This review will showcase research that combines such scaffolds with various stimulation techniques: mechanical stimulation, actuation by magnetic or electric fields, chemical stimulation, or manipulation by light. Additionally, it will introduce passive scaffolds that are actuated by the cells themselves. These systems help to understand forces applied by the cells to their environment and pave the way toward dynamic biohybrid, cell-based systems.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"33 ","pages":"Article 100574"},"PeriodicalIF":4.7,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098738","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 : 2024-11-29DOI: 10.1016/j.cobme.2024.100570
M. Walker , D. Gourdon , M. Cantini
The dynamic mechanical nature of extracellular matrices (ECMs) is crucial for the mechanosensitive regulation of cell fate. This is evident in pathological conditions such as cancer and fibrosis, which are characterised by highly fibrotic tissue developing over time. This fibrotic progression not only alters tissue mechanics, but also coincides with the reprogramming of resident cells, promoting their differentiation into aberrant phenotypes and increasing drug resistance. Hydrogels, with their tuneable mechanical and biochemical properties, emerge as powerful ECM mimetics to model and study these abnormal, mechanically-driven cell differentiation phenomena. In this review, after establishing how conventional, mechanically static hydrogels contribute to our understanding of the role of altered mechanosensing in cell differentiation during cancer and fibrosis, we explore the research opportunities given by advanced dynamic matrices. Models employing hydrogels that are fast relaxing, plastic or even with temporally switchable mechanics reveal the otherwise hidden role of time-dependent phenomena during disease development.
{"title":"Beyond static models: Mechanically dynamic matrices reveal new insights into cancer and fibrosis progression","authors":"M. Walker , D. Gourdon , M. Cantini","doi":"10.1016/j.cobme.2024.100570","DOIUrl":"10.1016/j.cobme.2024.100570","url":null,"abstract":"<div><div>The dynamic mechanical nature of extracellular matrices (ECMs) is crucial for the mechanosensitive regulation of cell fate. This is evident in pathological conditions such as cancer and fibrosis, which are characterised by highly fibrotic tissue developing over time. This fibrotic progression not only alters tissue mechanics, but also coincides with the reprogramming of resident cells, promoting their differentiation into aberrant phenotypes and increasing drug resistance. Hydrogels, with their tuneable mechanical and biochemical properties, emerge as powerful ECM mimetics to model and study these abnormal, mechanically-driven cell differentiation phenomena. In this review, after establishing how conventional, mechanically static hydrogels contribute to our understanding of the role of altered mechanosensing in cell differentiation during cancer and fibrosis, we explore the research opportunities given by advanced dynamic matrices. Models employing hydrogels that are fast relaxing, plastic or even with temporally switchable mechanics reveal the otherwise hidden role of time-dependent phenomena during disease development.</div></div>","PeriodicalId":36748,"journal":{"name":"Current Opinion in Biomedical Engineering","volume":"33 ","pages":"Article 100570"},"PeriodicalIF":4.7,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098677","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}
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