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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Neural stem cells for disease modeling and evaluation of therapeutics for Tay-Sachs disease
|
|---|---|
| Published in |
Orphanet Journal of Rare Diseases, September 2018
|
| DOI | 10.1186/s13023-018-0886-3 |
| Pubmed ID | |
| Authors |
Mylinh Vu, Rong Li, Amanda Baskfield, Billy Lu, Atena Farkhondeh, Kirill Gorshkov, Omid Motabar, Jeanette Beers, Guokai Chen, Jizhong Zou, Angela J. Espejo-Mojica, Alexander Rodríguez-López, Carlos J. Alméciga-Díaz, Luis A. Barrera, Xuntian Jiang, Daniel S. Ory, Juan J. Marugan, Wei Zheng |
| Abstract |
Tay-Sachs disease (TSD) is a rare neurodegenerative disorder caused by autosomal recessive mutations in the HEXA gene on chromosome 15 that encodes β-hexosaminidase. Deficiency in HEXA results in accumulation of GM2 ganglioside, a glycosphingolipid, in lysosomes. Currently, there is no effective treatment for TSD. We generated induced pluripotent stem cells (iPSCs) from two TSD patient dermal fibroblast lines and further differentiated them into neural stem cells (NSCs). The TSD neural stem cells exhibited a disease phenotype of lysosomal lipid accumulation. The Tay-Sachs disease NSCs were then used to evaluate the therapeutic effects of enzyme replacement therapy (ERT) with recombinant human Hex A protein and two small molecular compounds: hydroxypropyl-β-cyclodextrin (HPβCD) and δ-tocopherol. Using this disease model, we observed reduction of lipid accumulation by employing enzyme replacement therapy as well as by the use of HPβCD and δ-tocopherol. Our results demonstrate that the Tay-Sachs disease NSCs possess the characteristic phenotype to serve as a cell-based disease model for study of the disease pathogenesis and evaluation of drug efficacy. The enzyme replacement therapy with recombinant Hex A protein and two small molecules (cyclodextrin and tocopherol) significantly ameliorated lipid accumulation in the Tay-Sachs disease cell model. |
X Demographics
The data shown below were collected from the profiles of 10 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 Kingdom | 2 | 20% |
| United States | 2 | 20% |
| Colombia | 2 | 20% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Science communicators (journalists, bloggers, editors) | 2 | 20% |
| Scientists | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 128 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 36 | 28% |
| Researcher | 12 | 9% |
| Student > Ph. D. Student | 11 | 9% |
| Student > Master | 11 | 9% |
| Other | 4 | 3% |
| Other | 10 | 8% |
| Unknown | 44 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 34 | 27% |
| Agricultural and Biological Sciences | 13 | 10% |
| Medicine and Dentistry | 11 | 9% |
| Engineering | 6 | 5% |
| Neuroscience | 5 | 4% |
| Other | 13 | 10% |
| Unknown | 46 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 25 September 2018.
All research outputs
#2,321,068
of 23,103,436 outputs
Outputs from Orphanet Journal of Rare Diseases
#291
of 2,648 outputs
Outputs of similar age
#50,886
of 341,518 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#3
of 51 outputs
Altmetric has tracked 23,103,436 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,648 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 88% 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 341,518 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 51 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 94% of its contemporaries.