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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modeling Human Neurological and Neurodegenerative Diseases: From Induced Pluripotent Stem Cells to Neuronal Differentiation and Its Applications in Neurotrauma
|
|---|---|
| Published in |
Frontiers in Molecular Neuroscience, February 2017
|
| DOI | 10.3389/fnmol.2017.00050 |
| Pubmed ID | |
| Authors |
Hisham Bahmad, Ola Hadadeh, Farah Chamaa, Katia Cheaito, Batoul Darwish, Ahmad-Kareem Makkawi, Wassim Abou-Kheir |
| Abstract |
With the help of several inducing factors, somatic cells can be reprogrammed to become induced pluripotent stem cell (iPSCs) lines. The success is in obtaining iPSCs almost identical to embryonic stem cells (ESCs), therefore various approaches have been tested and ultimately several ones have succeeded. The importance of these cells is in how they serve as models to unveil the molecular pathways and mechanisms underlying several human diseases, and also in its potential roles in the development of regenerative medicine. They further aid in the development of regenerative medicine, autologous cell therapy and drug or toxicity screening. Here, we provide a comprehensive overview of the recent development in the field of iPSCs research, specifically for modeling human neurological and neurodegenerative diseases, and its applications in neurotrauma. These are mainly characterized by progressive functional or structural neuronal loss rendering them extremely challenging to manage. Many of these diseases, including Parkinson's disease (PD), Huntington's disease (HD), Amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD) have been explored in vitro. The main purpose is to generate patient-specific iPS cell lines from the somatic cells that carry mutations or genetic instabilities for the aim of studying their differentiation potential and behavior. This new technology will pave the way for future development in the field of stem cell research anticipating its use in clinical settings and in regenerative medicine in order to treat various human diseases, including neurological and neurodegenerative diseases. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | <1% |
| Unknown | 228 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 49 | 21% |
| Student > Ph. D. Student | 47 | 21% |
| Student > Master | 27 | 12% |
| Researcher | 24 | 10% |
| Student > Doctoral Student | 13 | 6% |
| Other | 24 | 10% |
| Unknown | 45 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 61 | 27% |
| Agricultural and Biological Sciences | 36 | 16% |
| Neuroscience | 33 | 14% |
| Medicine and Dentistry | 19 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 3% |
| Other | 17 | 7% |
| Unknown | 56 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 March 2017.
All research outputs
#20,718,666
of 23,317,888 outputs
Outputs from Frontiers in Molecular Neuroscience
#2,546
of 2,972 outputs
Outputs of similar age
#271,735
of 311,593 outputs
Outputs of similar age from Frontiers in Molecular Neuroscience
#89
of 102 outputs
Altmetric has tracked 23,317,888 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,972 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 311,593 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.