| Title |
Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, May 2016
|
| DOI | 10.1007/s00018-016-2265-3 |
| Pubmed ID | |
| Authors |
Martin Engel, Dzung Do-Ha, Sonia Sanz Muñoz, Lezanne Ooi |
| Abstract |
Induced pluripotent stem cells and embryonic stem cells have revolutionized cellular neuroscience, providing the opportunity to model neurological diseases and test potential therapeutics in a pre-clinical setting. The power of these models has been widely discussed, but the potential pitfalls of stem cell differentiation in this research are less well described. We have analyzed the literature that describes differentiation of human pluripotent stem cells into three neural cell types that are commonly used to study diseases, including forebrain cholinergic neurons for Alzheimer's disease, midbrain dopaminergic neurons for Parkinson's disease and cortical astrocytes for neurodegenerative and psychiatric disorders. Published protocols for differentiation vary widely in the reported efficiency of target cell generation. Additionally, characterization of the cells by expression profile and functionality differs between studies and is often insufficient, leading to highly variable protocol outcomes. We have synthesized this information into a simple methodology that can be followed when performing or assessing differentiation techniques. Finally we propose three considerations for future research, including the use of physiological O2 conditions, three-dimensional co-culture systems and microfluidics to control feeding cycles and growth factor gradients. Following these guidelines will help researchers to ensure that robust and meaningful data is generated, enabling the full potential of stem cell differentiation for disease modeling and regenerative medicine. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 33% |
| Denmark | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 1 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 212 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | <1% |
| United States | 2 | <1% |
| Australia | 1 | <1% |
| Mexico | 1 | <1% |
| Netherlands | 1 | <1% |
| Unknown | 205 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 46 | 22% |
| Researcher | 33 | 16% |
| Student > Master | 29 | 14% |
| Student > Bachelor | 29 | 14% |
| Student > Doctoral Student | 11 | 5% |
| Other | 29 | 14% |
| Unknown | 35 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 52 | 25% |
| Agricultural and Biological Sciences | 44 | 21% |
| Biochemistry, Genetics and Molecular Biology | 42 | 20% |
| Medicine and Dentistry | 18 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 2% |
| Other | 13 | 6% |
| Unknown | 38 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 23 October 2023.
All research outputs
#1,780,898
of 24,727,020 outputs
Outputs from Cellular and Molecular Life Sciences
#199
of 5,628 outputs
Outputs of similar age
#28,996
of 304,275 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#4
of 90 outputs
Altmetric has tracked 24,727,020 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,628 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 96% of its peers.
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We're also able to compare this research output to 90 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 96% of its contemporaries.