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Kim GS, Lee JH, Shin DY, Lee HS, Park H, Lee KW, Yang HM, Kim SJ, Park JB. Integrated whole liver histologic analysis of the allogeneic islet distribution and characteristics in a nonhuman primate model. Sci Rep 2020; 10:793. [PMID: 31964980 PMCID: PMC6972963 DOI: 10.1038/s41598-020-57701-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/06/2020] [Indexed: 12/21/2022] Open
Abstract
The most obvious method to observe transplanted islets in the liver is direct biopsy, but the distribution and location of the best biopsy site in the recipient's liver are poorly understood. Islets transplanted into the whole liver of five diabetic cynomolgus monkeys that underwent insulin-independent survival for an extended period of time after allo-islet transplantation were analyzed for characteristics and distribution tendency. The liver was divided into segments (S1-S8), and immunohistochemistry analysis was performed to estimate the diameter, beta cell area, and islet location. Islets were more distributed in S2 depending on tissue size; however, the number of islets per tissue size was high in S1 and S8. Statistical analysis revealed that the characteristics of islets in S1 and S8 were relatively similar to other segments despite various transplanted islet dosages and survival times. In conclusion, S1, which exhibited high islet density and reflected the overall characteristics of transplanted islets, can be considered to be a reasonable candidate for a liver biopsy site in this monkey model. The findings obtained from the five monkey livers with similar anatomical features to human liver can be used as a reference for monitoring transplanted islets after clinical islet transplantation.
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Affiliation(s)
- Geun Soo Kim
- Samsung Advanced Institute for Health Sciences & Technology, Graduate School, Department of Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Republic of Korea.,Transplantation Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | | | - Du Yeon Shin
- Samsung Advanced Institute for Health Sciences & Technology, Graduate School, Department of Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Republic of Korea.,Transplantation Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Han Sin Lee
- Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Republic of Korea.,Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyojun Park
- Department of Medicine, Sungkyunkwan University School of Medicine, Gyeonggi, Republic of Korea.,GenNBio Inc, Seoul, Republic of Korea
| | - Kyo Won Lee
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Department of Medicine, Sungkyunkwan University School of Medicine, Gyeonggi, Republic of Korea
| | - Heung-Mo Yang
- Department of Medicine, Sungkyunkwan University School of Medicine, Gyeonggi, Republic of Korea.,GenNBio Inc, Seoul, Republic of Korea
| | - Sung Joo Kim
- Department of Medicine, Sungkyunkwan University School of Medicine, Gyeonggi, Republic of Korea.,GenNBio Inc, Seoul, Republic of Korea
| | - Jae Berm Park
- Samsung Advanced Institute for Health Sciences & Technology, Graduate School, Department of Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea. .,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Republic of Korea. .,Transplantation Research Center, Samsung Medical Center, Seoul, Republic of Korea. .,Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. .,Department of Medicine, Sungkyunkwan University School of Medicine, Gyeonggi, Republic of Korea.
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Molnár C, Essand M, Wennberg L, Berne C, Larsson E, Tufveson G, Korsgren O. Islet Engraftment and Revascularization in Clinical and Experimental Transplantation. Cell Transplant 2013; 22:243-51. [DOI: 10.3727/096368912x640637] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Proper revascularization after transplantation is assumed to be crucial for appropriate islet graft function. We developed a novel noninvasive imaging method, based on adenoviral transduction of islets with a hypoxia responsive reporter gene, for continuous in vivo monitoring of hypoxia in islet grafts in a mouse model. In addition, morphological data were obtained from a deceased patient previously subject to intraportal transplantation. We detected only transient hypoxia in a minority of the animals transplanted. Importantly, a clear response to hypoxia was observed in vitro after removal of the islet grafts on day 28 after transplantation. Also, the morphological data from the deceased patient demonstrated an extensive revascularization of the transplanted islets. In fact, no differences could be seen between native islets, in pancreas biopsies taken prior to islet isolation, and transplanted islets regarding the number, distribution, and shape of the blood vessels. However, fewer small islets (diameter <39 μm) were found in the liver compared to those found in native pancreases. Notably, an absolute majority of the transplanted islets were found remaining within the venous lumen, in direct contact with the vessel wall. In conclusion, the results presented show less pronounced islet graft hypoxia after subcapsular transplantation than previously reported using more invasive methods. Also, formation of an extensive intraislet capillary network, similar to that seen in native islets in the pancreas, was seen after clinical islet transplantation.
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Affiliation(s)
- Christian Molnár
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Department of Transplantation Surgery, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - Magnus Essand
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Lars Wennberg
- Department of Transplantation Surgery, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - Christian Berne
- Department of Medical Sciences, Division of Medicine, Uppsala University Hospital, Uppsala, Sweden
| | - Erik Larsson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Gunnar Tufveson
- Department of Surgical Sciences, Division of Transplantation Surgery, Uppsala University Hospital, Uppsala, Sweden
| | - Olle Korsgren
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
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Buchwald P, Wang X, Khan A, Bernal A, Fraker C, Inverardi L, Ricordi C. Quantitative assessment of islet cell products: estimating the accuracy of the existing protocol and accounting for islet size distribution. Cell Transplant 2009; 18:1223-35. [PMID: 19818209 DOI: 10.3727/096368909x476968] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
The ability to consistently and reliably assess the total number and the size distribution of isolated pancreatic islet cells from a small sample is of crucial relevance for the adequate characterization of islet cell preparations used for research or transplantation purposes. Here, data from a large number of isolations were used to establish a continuous probability density function describing the size distribution of human pancreatic islets. This function was then used to generate a polymeric microsphere mixture with a composition resembling those of isolated islets, which, in turn, was used to quantitatively assess the accuracy, reliability, and operator-dependent variability of the currently utilized manual standard procedure of quantification of islet cell preparation. Furthermore, on the basis of the best fit probability density function, which corresponds to a Weibull distribution, a slightly modified scale of islet equivalent number (IEQ) conversion factors is proposed that incorporates the size distribution of islets and accounts for the decreasing probability of finding larger islets within each size group. Compared to the current calculation method, these factors introduce a 4-8% downward correction of the total IEQ estimate, but they reflect a statistically more accurate contribution of differently sized islets.
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Affiliation(s)
- Peter Buchwald
- Diabetes Research Institute, University of Miami Leonard M. Miller School of Medicine, Miami, FL 33136, USA.
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