↓ Skip to main content

Long-term expansion of alveolar stem cells derived from human iPS cells in organoids

Overview of attention for article published in Nature Methods, October 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

blogs
1 blog
twitter
50 X users
patent
8 patents
facebook
1 Facebook page

Citations

dimensions_citation
205 Dimensions

Readers on

mendeley
261 Mendeley
Title
Long-term expansion of alveolar stem cells derived from human iPS cells in organoids
Published in
Nature Methods, October 2017
DOI 10.1038/nmeth.4448
Pubmed ID
Authors

Yuki Yamamoto, Shimpei Gotoh, Yohei Korogi, Masahide Seki, Satoshi Konishi, Satoshi Ikeo, Naoyuki Sone, Tadao Nagasaki, Hisako Matsumoto, Shigeo Muro, Isao Ito, Toyohiro Hirai, Takashi Kohno, Yutaka Suzuki, Michiaki Mishima

Abstract

The stable expansion of tissue-specific stem cells in vitro has contributed to research on several organs. Alveolar epithelial type II (AT2) cells function as tissue stem cells in the lung, but robust models for studying human AT2 cells are lacking. Here we report a method for the efficient generation and long-term expansion of alveolar organoids (AOs) harboring SFTPC(+) alveolar stem cells derived from human induced pluripotent stem cells (hiPSCs). hiPSC-derived SFTPC(+) cells self-renewed, with transcriptomes and morphology consistent with those of AT2 cells, and were able to differentiate into alveolar epithelial type I (AT1)-like cells. Single-cell RNA-seq of SFTPC(+) cells and their progenitors demonstrated that their differentiation process and cellular heterogeneity resembled those of developing AT2 cells in vivo. AOs were applicable to drug toxicology studies recapitulating AT2-cell-specific phenotypes. Our methods can help scientists overcome the limitations of current approaches to the modeling of human alveoli and should be useful for disease modeling and regenerative medicine.

X Demographics

X Demographics

The data shown below were collected from the profiles of 50 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 261 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 261 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 19%
Student > Ph. D. Student 47 18%
Student > Master 29 11%
Student > Bachelor 21 8%
Other 14 5%
Other 36 14%
Unknown 65 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 62 24%
Agricultural and Biological Sciences 32 12%
Medicine and Dentistry 24 9%
Engineering 15 6%
Pharmacology, Toxicology and Pharmaceutical Science 12 5%
Other 39 15%
Unknown 77 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 March 2023.
All research outputs
#805,968
of 25,220,525 outputs
Outputs from Nature Methods
#1,056
of 5,344 outputs
Outputs of similar age
#16,755
of 329,026 outputs
Outputs of similar age from Nature Methods
#24
of 81 outputs
Altmetric has tracked 25,220,525 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.1. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,026 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.