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Organoid and organ-on-a-chip technologies are three-dimensional tissue structures that are cultivated in vitro from stem cells or tissue-derived primary cells. They replicate the functions and microenvironments of actual organs, allowing researchers to study biological processes and disease mechanisms more accurately. This offers new possibilities for establishing in vitro disease models, drug screening, and personalized medicine. In vitro-constructed organoids could potentially be used as anti-aging or regenerative therapies to replace diseased or aging tissues in the future. However, the current construction of organoid models still presents numerous problems and challenges. To simulate the microenvironment of human organs accurately and to understand the functional relationship between various components, constructing organoids face challenges in terms of cell complexity and diversity, tissue structure, geometrical morphology, and functional component integrity. This review proposes an integrated design strategy based on engineering principles to tackle these challenges and to optimize organoid technologies. The aim is to examine following five key bioengineering elements: integrating essential cell types, constructing macroscopic and microscopic structures, controlling and mimicking developmental processes, establishing cellular interactions, and designing for different functional purposes. The article establishes a systematic connection between biological elements and the technological interventions in organ and disease development. The optimization of organoids-on-a-chip technology involves multiple fields, including biology, medicine, mechanobiology, optics, materials science, biofabrication, and computational modeling. This allows for collaboration among teams with different areas of expertise, all focused on improving organoids and organ-on-a-chip technologies. Such collaboration is necessary to enhance in vitro culture, tissue development, functional acquisition, dynamic monitoring, and standardization. Furthermore, the integration of high-dimensional data sets in digital twin organoid systems can aid in the management, analysis, and tracking of big data in organoids and organ-on-a-chip. These advancements can lead to more accurate disease analysis, improved predictions, and early intervention strategies, ultimately advancing precision medicine into a new era of preemptive healthcare.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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