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Maharjan S, Ma C, Singh B, Kang H, Orive G, Yao J, Shrike Zhang Y. Advanced 3D imaging and organoid bioprinting for biomedical research and therapeutic applications. Adv Drug Deliv Rev 2024; 208:115237. [PMID: 38447931 PMCID: PMC11031334 DOI: 10.1016/j.addr.2024.115237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/15/2024] [Accepted: 02/27/2024] [Indexed: 03/08/2024]
Abstract
Organoid cultures offer a valuable platform for studying organ-level biology, allowing for a closer mimicry of human physiology compared to traditional two-dimensional cell culture systems or non-primate animal models. While many organoid cultures use cell aggregates or decellularized extracellular matrices as scaffolds, they often lack precise biochemical and biophysical microenvironments. In contrast, three-dimensional (3D) bioprinting allows precise placement of organoids or spheroids, providing enhanced spatial control and facilitating the direct fusion for the formation of large-scale functional tissues in vitro. In addition, 3D bioprinting enables fine tuning of biochemical and biophysical cues to support organoid development and maturation. With advances in the organoid technology and its potential applications across diverse research fields such as cell biology, developmental biology, disease pathology, precision medicine, drug toxicology, and tissue engineering, organoid imaging has become a crucial aspect of physiological and pathological studies. This review highlights the recent advancements in imaging technologies that have significantly contributed to organoid research. Additionally, we discuss various bioprinting techniques, emphasizing their applications in organoid bioprinting. Integrating 3D imaging tools into a bioprinting platform allows real-time visualization while facilitating quality control, optimization, and comprehensive bioprinting assessment. Similarly, combining imaging technologies with organoid bioprinting can provide valuable insights into tissue formation, maturation, functions, and therapeutic responses. This approach not only improves the reproducibility of physiologically relevant tissues but also enhances understanding of complex biological processes. Thus, careful selection of bioprinting modalities, coupled with appropriate imaging techniques, holds the potential to create a versatile platform capable of addressing existing challenges and harnessing opportunities in these rapidly evolving fields.
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Affiliation(s)
- Sushila Maharjan
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA
| | - Chenshuo Ma
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Bibhor Singh
- Winthrop L. Chenery Upper Elementary School, Belmont, MA 02478, USA
| | - Heemin Kang
- Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea; College of Medicine, Korea University, Seoul 02841, Republic of Korea
| | - Gorka Orive
- NanoBioCel Research Group, School of Pharmacy, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain; Bioaraba, NanoBioCel Research Group, Vitoria-Gasteiz, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN). Vitoria-Gasteiz, Spain; University Institute for Regenerative Medicine and Oral Implantology - UIRMI (UPV/EHU-Fundación Eduardo Anitua), Vitoria, 01007, Spain; Singapore Eye Research Institute, The Academia, 20 College Road, Discovery Tower, Singapore 169856, Singapore
| | - Junjie Yao
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
| | - Yu Shrike Zhang
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA.
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Kim MJ, Kulkarni V, Goode MA, Hernandez J, Graham S, Sivesind TE, Manchadi ML. Utilizing systems genetics to enhance understanding into molecular targets of skin cancer. Exp Dermatol 2024; 33:e15043. [PMID: 38459629 PMCID: PMC11018140 DOI: 10.1111/exd.15043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 02/12/2024] [Accepted: 02/16/2024] [Indexed: 03/10/2024]
Abstract
Despite progress made with immune checkpoint inhibitors and targeted therapies, skin cancer remains a significant public health concern in the United States. The intricacies of the disease, encompassing genetics, immune responses, and external factors, call for a comprehensive approach. Techniques in systems genetics, including transcriptional correlation analysis, functional pathway enrichment analysis, and protein-protein interaction network analysis, prove valuable in deciphering intricate molecular mechanisms and identifying potential diagnostic and therapeutic targets for skin cancer. Recent studies demonstrate the efficacy of these techniques in uncovering molecular processes and pinpointing diagnostic markers for various skin cancer types, highlighting the potential of systems genetics in advancing innovative therapies. While certain limitations exist, such as generalizability and contextualization of external factors, the ongoing progress in AI technologies provides hope in overcoming these challenges. By providing protocols and a practical example involving Braf, we aim to inspire early-career experimental dermatologists to adopt these tools and seamlessly integrate these techniques into their skin cancer research, positioning them at the forefront of innovative approaches in combating this devastating disease.
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Affiliation(s)
- Minjae J Kim
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | | | - Micah A Goode
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Jacob Hernandez
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Sean Graham
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Torunn E Sivesind
- Department of Dermatology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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Kim MJ, Martin CA, Kim J, Jablonski MM. Computational methods in glaucoma research: Current status and future outlook. Mol Aspects Med 2023; 94:101222. [PMID: 37925783 PMCID: PMC10842846 DOI: 10.1016/j.mam.2023.101222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/06/2023] [Accepted: 10/19/2023] [Indexed: 11/07/2023]
Abstract
Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and potential therapeutic targets. Systems genetics integrates genomic and clinical data, aiding in identifying drug targets, comprehending disease mechanisms, and personalizing treatment strategies for glaucoma. Molecular dynamics simulations offer valuable molecular-level insights into glaucoma-related biomolecule behavior and drug interactions, guiding experimental studies and drug discovery efforts. Artificial intelligence (AI) technologies hold promise in revolutionizing glaucoma research, enhancing disease diagnosis, target identification, and drug candidate selection. The generalized protocols for systems genetics, MD simulations, and AI model development are included as a guide for glaucoma researchers. These computational methods, however, are not separate and work harmoniously together to discover novel ways to combat glaucoma. Ongoing research and progresses in genomics technologies, MD simulations, and AI methodologies project computational methods to become an integral part of glaucoma research in the future.
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Affiliation(s)
- Minjae J Kim
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| | - Cole A Martin
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| | - Jinhwa Kim
- Graduate School of Artificial Intelligence, Graduate School of Metaverse, Department of Management Information Systems, Sogang University, 1 Shinsoo-Dong, Mapo-Gu, Seoul, South Korea.
| | - Monica M Jablonski
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
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Lavekar SS, Patel MD, Montalvo-Parra MD, Krencik R. Asteroid impact: the potential of astrocytes to modulate human neural networks within organoids. Front Neurosci 2023; 17:1305921. [PMID: 38075269 PMCID: PMC10702564 DOI: 10.3389/fnins.2023.1305921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/08/2023] [Indexed: 02/12/2024] Open
Abstract
Astrocytes are a vital cellular component of the central nervous system that impact neuronal function in both healthy and pathological states. This includes intercellular signals to neurons and non-neuronal cells during development, maturation, and aging that can modulate neural network formation, plasticity, and maintenance. Recently, human pluripotent stem cell-derived neural aggregate cultures, known as neurospheres or organoids, have emerged as improved experimental platforms for basic and pre-clinical neuroscience compared to traditional approaches. Here, we summarize the potential capability of using organoids to further understand the mechanistic role of astrocytes upon neural networks, including the production of extracellular matrix components and reactive signaling cues. Additionally, we discuss the application of organoid models to investigate the astrocyte-dependent aspects of neuropathological diseases and to test astrocyte-inspired technologies. We examine the shortcomings of organoid-based experimental platforms and plausible improvements made possible by cutting-edge neuroengineering technologies. These advancements are expected to enable the development of improved diagnostic strategies and high-throughput translational applications regarding neuroregeneration.
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Affiliation(s)
| | | | | | - R. Krencik
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, United States
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