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Mendeley readers
Attention Score in Context
| Title |
Directed differentiation of human iPSC into insulin producing cells is improved by induced expression of PDX1 and NKX6.1 factors in IPC progenitors
|
|---|---|
| Published in |
Journal of Translational Medicine, December 2016
|
| DOI | 10.1186/s12967-016-1097-0 |
| Pubmed ID | |
| Authors |
Maciej P. Walczak, Anna M. Drozd, Ewelina Stoczynska-Fidelus, Piotr Rieske, Dawid P. Grzela |
| Abstract |
Induced pluripotent stem cells (iPSC) possess an enormous potential as both, scientific and therapeutic tools. Their application in the regenerative medicine provides new treatment opportunities for numerous diseases, including type 1 diabetes. In this work we aimed to derive insulin producing cells (IPC) from iPS cells established in defined conditions. We optimized iPSC generation protocol and created pluripotent cell lines with stably integrated PDX1 and NKX6.1 transgenes under the transcriptional control of doxycycline-inducible promoter. These cells were differentiated using small chemical molecules and recombinant Activin A in the sequential process through the definitive endoderm, pancreatic progenitor cells and insulin producing cells. Efficiency of the procedure was assessed by quantitative gene expression measurements, immunocytochemical stainings and functional assays for insulin secretion. Generated cells displayed molecular markers characteristic for respective steps of the differentiation. The obtained IPC secreted insulin and produced C-peptide with significantly higher hormone release level in case of the combined expression of PDX1 and NKX6.1 induced at the last stage of the differentiation. Efficiency of differentiation of iPSC to IPC can be increased by concurrent expression of PDX1 and NKX6.1 during progenitor cells maturation. Protocols established in our study allow for iPSC generation and derivation of IPC in chemically defined conditions free from animal-derived components, which is of the utmost importance in the light of their prospective applications in the field of regenerative medicine. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 74 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 27% |
| Student > Master | 10 | 13% |
| Student > Bachelor | 8 | 11% |
| Researcher | 7 | 9% |
| Other | 5 | 7% |
| Other | 5 | 7% |
| Unknown | 20 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 23 | 31% |
| Agricultural and Biological Sciences | 11 | 15% |
| Medicine and Dentistry | 9 | 12% |
| Engineering | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Other | 4 | 5% |
| Unknown | 23 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 19 December 2023.
All research outputs
#6,952,861
of 24,682,395 outputs
Outputs from Journal of Translational Medicine
#1,107
of 4,451 outputs
Outputs of similar age
#121,952
of 431,182 outputs
Outputs of similar age from Journal of Translational Medicine
#15
of 57 outputs
Altmetric has tracked 24,682,395 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 4,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 74% 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 431,182 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 57 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 73% of its contemporaries.