Pub Date : 2023-01-01DOI: 10.1007/s42242-022-00226-y
Xuan Du, Zaozao Chen, Qiwei Li, Sheng Yang, Lincao Jiang, Yi Yang, Yanhui Li, Zhongze Gu
In modern terminology, "organoids" refer to cells that grow in a specific three-dimensional (3D) environment in vitro, sharing similar structures with their source organs or tissues. Observing the morphology or growth characteristics of organoids through a microscope is a commonly used method of organoid analysis. However, it is difficult, time-consuming, and inaccurate to screen and analyze organoids only manually, a problem which cannot be easily solved with traditional technology. Artificial intelligence (AI) technology has proven to be effective in many biological and medical research fields, especially in the analysis of single-cell or hematoxylin/eosin stained tissue slices. When used to analyze organoids, AI should also provide more efficient, quantitative, accurate, and fast solutions. In this review, we will first briefly outline the application areas of organoids and then discuss the shortcomings of traditional organoid measurement and analysis methods. Secondly, we will summarize the development from machine learning to deep learning and the advantages of the latter, and then describe how to utilize a convolutional neural network to solve the challenges in organoid observation and analysis. Finally, we will discuss the limitations of current AI used in organoid research, as well as opportunities and future research directions.
{"title":"Organoids revealed: morphological analysis of the profound next generation in-vitro model with artificial intelligence.","authors":"Xuan Du, Zaozao Chen, Qiwei Li, Sheng Yang, Lincao Jiang, Yi Yang, Yanhui Li, Zhongze Gu","doi":"10.1007/s42242-022-00226-y","DOIUrl":"https://doi.org/10.1007/s42242-022-00226-y","url":null,"abstract":"<p><p>In modern terminology, \"organoids\" refer to cells that grow in a specific three-dimensional (3D) environment in vitro, sharing similar structures with their source organs or tissues. Observing the morphology or growth characteristics of organoids through a microscope is a commonly used method of organoid analysis. However, it is difficult, time-consuming, and inaccurate to screen and analyze organoids only manually, a problem which cannot be easily solved with traditional technology. Artificial intelligence (AI) technology has proven to be effective in many biological and medical research fields, especially in the analysis of single-cell or hematoxylin/eosin stained tissue slices. When used to analyze organoids, AI should also provide more efficient, quantitative, accurate, and fast solutions. In this review, we will first briefly outline the application areas of organoids and then discuss the shortcomings of traditional organoid measurement and analysis methods. Secondly, we will summarize the development from machine learning to deep learning and the advantages of the latter, and then describe how to utilize a convolutional neural network to solve the challenges in organoid observation and analysis. Finally, we will discuss the limitations of current AI used in organoid research, as well as opportunities and future research directions.</p><p><strong>Graphic abstract: </strong></p>","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 3","pages":"319-339"},"PeriodicalIF":7.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9374483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-28DOI: 10.1007/s42242-022-00222-2
Naima Valentin, W. Hua, A. Kasar, Lily Raymond, P. Menezes, Yifei Jin
{"title":"Direct ink writing to fabricate porous acetabular cups from titanium alloy","authors":"Naima Valentin, W. Hua, A. Kasar, Lily Raymond, P. Menezes, Yifei Jin","doi":"10.1007/s42242-022-00222-2","DOIUrl":"https://doi.org/10.1007/s42242-022-00222-2","url":null,"abstract":"","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 1","pages":"121-135"},"PeriodicalIF":7.9,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47463328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-17DOI: 10.1007/s42242-022-00210-6
Francesco Biagini, C. Daddi, Marco Calvigioni, C. De Maria, Y. S. Zhang, E. Ghelardi, G. Vozzi
{"title":"Designs and methodologies to recreate in vitro human gut microbiota models","authors":"Francesco Biagini, C. Daddi, Marco Calvigioni, C. De Maria, Y. S. Zhang, E. Ghelardi, G. Vozzi","doi":"10.1007/s42242-022-00210-6","DOIUrl":"https://doi.org/10.1007/s42242-022-00210-6","url":null,"abstract":"","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 1","pages":"298-318"},"PeriodicalIF":7.9,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42814712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of a portable reflectance confocal microscope and its application in the noninvasive in vivo evaluation of mesenchymal stem cell-promoted cutaneous wound healing","authors":"Lixing Zhang, Xin Miao, Meijia Wang, Aihua Shi, Jingwen Wang, Zhonglin Ma, Yunhai Zhang, Jingzhong Zhang, Shuang Yu","doi":"10.1007/s42242-022-00223-1","DOIUrl":"https://doi.org/10.1007/s42242-022-00223-1","url":null,"abstract":"","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 1","pages":"268-283"},"PeriodicalIF":7.9,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42967205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-03DOI: 10.1007/s42242-022-00219-x
Se-Hwan Lee, Kang-Gon Lee, Jaeyeon Lee, Y. Cho, Min-Soo Ghim, Soojin Kim, S. Heo, Yongdoo Park, Young-Sam Cho, B. Lee
{"title":"Three-dimensional kagome structures in a PCL/HA-based hydrogel scaffold to lead slow BMP-2 release for effective bone regeneration","authors":"Se-Hwan Lee, Kang-Gon Lee, Jaeyeon Lee, Y. Cho, Min-Soo Ghim, Soojin Kim, S. Heo, Yongdoo Park, Young-Sam Cho, B. Lee","doi":"10.1007/s42242-022-00219-x","DOIUrl":"https://doi.org/10.1007/s42242-022-00219-x","url":null,"abstract":"","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 1","pages":"12-25"},"PeriodicalIF":7.9,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44655707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-10DOI: 10.1007/s42242-022-00217-z
M. Mandolini, Agnese Brunzini, Manila Caragiuli, A. Mazzoli, M. Pagnoni
{"title":"An innovative orbital implant positioner for the proper restoration of eye-socket defects","authors":"M. Mandolini, Agnese Brunzini, Manila Caragiuli, A. Mazzoli, M. Pagnoni","doi":"10.1007/s42242-022-00217-z","DOIUrl":"https://doi.org/10.1007/s42242-022-00217-z","url":null,"abstract":"","PeriodicalId":48627,"journal":{"name":"Bio-Design and Manufacturing","volume":"6 1","pages":"82-89"},"PeriodicalIF":7.9,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42910903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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