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Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection
Here, we present a protocol to generate a murine model of liver metastasis by directly injecting tumor cells into the portal vein under ultrasound guidance. We describe steps for animal and cell preparation and two techniques for injecting tumor cells. One technique is freehand, while the other tech...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036864/ https://www.ncbi.nlm.nih.gov/pubmed/36930646 http://dx.doi.org/10.1016/j.xpro.2023.102163 |
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author | Labora, Amanda Lee, Hailey Chan, Charlotte Tabornal, Erin Le, Thuc Rashid, Khalid Abt, Evan Yamao, Takanobu Mandl, Hanna Creech, Amanda Premji, Alykhan Li, Luyi Link, Jason Wu, Nanping Radu, Caius Donahue, Timothy |
author_facet | Labora, Amanda Lee, Hailey Chan, Charlotte Tabornal, Erin Le, Thuc Rashid, Khalid Abt, Evan Yamao, Takanobu Mandl, Hanna Creech, Amanda Premji, Alykhan Li, Luyi Link, Jason Wu, Nanping Radu, Caius Donahue, Timothy |
author_sort | Labora, Amanda |
collection | PubMed |
description | Here, we present a protocol to generate a murine model of liver metastasis by directly injecting tumor cells into the portal vein under ultrasound guidance. We describe steps for animal and cell preparation and two techniques for injecting tumor cells. One technique is freehand, while the other technique is device-assisted using a 3D-printed prototype device. Finally, we describe tumor surveillance with bioluminescent imaging. |
format | Online Article Text |
id | pubmed-10036864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100368642023-03-25 Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection Labora, Amanda Lee, Hailey Chan, Charlotte Tabornal, Erin Le, Thuc Rashid, Khalid Abt, Evan Yamao, Takanobu Mandl, Hanna Creech, Amanda Premji, Alykhan Li, Luyi Link, Jason Wu, Nanping Radu, Caius Donahue, Timothy STAR Protoc Protocol Here, we present a protocol to generate a murine model of liver metastasis by directly injecting tumor cells into the portal vein under ultrasound guidance. We describe steps for animal and cell preparation and two techniques for injecting tumor cells. One technique is freehand, while the other technique is device-assisted using a 3D-printed prototype device. Finally, we describe tumor surveillance with bioluminescent imaging. Elsevier 2023-03-16 /pmc/articles/PMC10036864/ /pubmed/36930646 http://dx.doi.org/10.1016/j.xpro.2023.102163 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Protocol Labora, Amanda Lee, Hailey Chan, Charlotte Tabornal, Erin Le, Thuc Rashid, Khalid Abt, Evan Yamao, Takanobu Mandl, Hanna Creech, Amanda Premji, Alykhan Li, Luyi Link, Jason Wu, Nanping Radu, Caius Donahue, Timothy Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title | Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title_full | Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title_fullStr | Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title_full_unstemmed | Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title_short | Generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
title_sort | generation of liver metastases in a mouse model using ultrasound-guided intravenous injection |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036864/ https://www.ncbi.nlm.nih.gov/pubmed/36930646 http://dx.doi.org/10.1016/j.xpro.2023.102163 |
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