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Human Embryonic Stem Cells Derived by Somatic Cell Nuclear Transfer

Overview of attention for article published in Cell, May 2013
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Citations

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629 Dimensions

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1601 Mendeley
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7 CiteULike
Title
Human Embryonic Stem Cells Derived by Somatic Cell Nuclear Transfer
Published in
Cell, May 2013
DOI 10.1016/j.cell.2013.05.006
Pubmed ID
Authors

Masahito Tachibana, Paula Amato, Michelle Sparman, Nuria Marti Gutierrez, Rebecca Tippner-Hedges, Hong Ma, Eunju Kang, Alimujiang Fulati, Hyo-Sang Lee, Hathaitip Sritanaudomchai, Keith Masterson, Janine Larson, Deborah Eaton, Karen Sadler-Fredd, David Battaglia, David Lee, Diana Wu, Jeffrey Jensen, Phillip Patton, Sumita Gokhale, Richard L. Stouffer, Don Wolf, Shoukhrat Mitalipov

Abstract

Reprogramming somatic cells into pluripotent embryonic stem cells (ESCs) by somatic cell nuclear transfer (SCNT) has been envisioned as an approach for generating patient-matched nuclear transfer (NT)-ESCs for studies of disease mechanisms and for developing specific therapies. Past attempts to produce human NT-ESCs have failed secondary to early embryonic arrest of SCNT embryos. Here, we identified premature exit from meiosis in human oocytes and suboptimal activation as key factors that are responsible for these outcomes. Optimized SCNT approaches designed to circumvent these limitations allowed derivation of human NT-ESCs. When applied to premium quality human oocytes, NT-ESC lines were derived from as few as two oocytes. NT-ESCs displayed normal diploid karyotypes and inherited their nuclear genome exclusively from parental somatic cells. Gene expression and differentiation profiles in human NT-ESCs were similar to embryo-derived ESCs, suggesting efficient reprogramming of somatic cells to a pluripotent state.

X Demographics

X Demographics

The data shown below were collected from the profiles of 291 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 1,601 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 35 2%
United Kingdom 17 1%
Germany 11 <1%
Spain 10 <1%
Japan 9 <1%
France 5 <1%
Italy 3 <1%
Russia 3 <1%
Sweden 2 <1%
Other 24 1%
Unknown 1482 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 380 24%
Researcher 271 17%
Student > Bachelor 265 17%
Student > Master 197 12%
Student > Doctoral Student 71 4%
Other 249 16%
Unknown 168 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 717 45%
Biochemistry, Genetics and Molecular Biology 294 18%
Medicine and Dentistry 157 10%
Engineering 51 3%
Neuroscience 41 3%
Other 142 9%
Unknown 199 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1259. 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 02 March 2024.
All research outputs
#10,752
of 25,459,177 outputs
Outputs from Cell
#86
of 17,195 outputs
Outputs of similar age
#35
of 207,229 outputs
Outputs of similar age from Cell
#2
of 129 outputs
Altmetric has tracked 25,459,177 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,195 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 59.2. This one has done particularly well, scoring higher than 99% 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 207,229 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 99% of its contemporaries.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.