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Find video protocols related to scientific articles indexed in Pubmed.
Systematically labeling developmental stage-specific genes for the study of pancreatic ?-cell differentiation from human embryonic stem cells.
Cell Res.
PUBLISHED: 09-05-2014
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The applications of human pluripotent stem cell (hPSC)-derived cells in regenerative medicine has encountered a long-standing challenge: how can we efficiently obtain mature cell types from hPSCs? Attempts to address this problem are hindered by the complexity of controlling cell fate commitment and the lack of sufficient developmental knowledge for guiding hPSC differentiation. Here, we developed a systematic strategy to study hPSC differentiation by labeling sequential developmental genes to encompass the major developmental stages, using the directed differentiation of pancreatic ? cells from hPSCs as a model. We therefore generated a large panel of pancreas-specific mono- and dual-reporter cell lines. With this unique platform, we visualized the kinetics of the entire differentiation process in real time for the first time by monitoring the expression dynamics of the reporter genes, identified desired cell populations at each differentiation stage and demonstrated the ability to isolate these cell populations for further characterization. We further revealed the expression profiles of isolated NGN3-eGFP(+) cells by RNA sequencing and identified sushi domain-containing 2 (SUSD2) as a novel surface protein that enriches for pancreatic endocrine progenitors and early endocrine cells both in human embryonic stem cells (hESC)-derived pancreatic cells and in the developing human pancreas. Moreover, we captured a series of cell fate transition events in real time, identified multiple cell subpopulations and unveiled their distinct gene expression profiles, among heterogeneous progenitors for the first time using our dual reporter hESC lines. The exploration of this platform and our new findings will pave the way to obtain mature ? cells in vitro.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.