Title |
Neuronal aging: learning from C. elegans
|
---|---|
Published in |
Journal of Molecular Signaling, December 2013
|
DOI | 10.1186/1750-2187-8-14 |
Pubmed ID | |
Authors |
Chun-Hao Chen, Yen-Chih Chen, Hao-Ching Jiang, Chung-Kuan Chen, Chun-Liang Pan |
Abstract |
The heterogeneity and multigenetic nature of nervous system aging make modeling of it a formidable task in mammalian species. The powerful genetics, simple anatomy and short life span of the nematode Caenorhabditis elegans offer unique advantages in unraveling the molecular genetic network that regulates the integrity of neuronal structures and functions during aging. In this review, we first summarize recent breakthroughs in the morphological and functional characterization of C. elegans neuronal aging. Age-associated morphological changes include age-dependent neurite branching, axon beading or swelling, axon defasciculation, progressive distortion of the neuronal soma, and early decline in presynaptic release function. We then discuss genetic pathways that modulate the speed of neuronal aging concordant with alteration in life span, such as insulin signaling, as well as cell-autonomous factors that promote neuronal integrity during senescence, including membrane activity and JNK/MAPK signaling. As a robust genetic model for aging, insights from C. elegans neuronal aging studies will contribute to our mechanistic understanding of human brain aging. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 50% |
United States | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Science communicators (journalists, bloggers, editors) | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Hungary | 1 | <1% |
Australia | 1 | <1% |
India | 1 | <1% |
Belgium | 1 | <1% |
United States | 1 | <1% |
Unknown | 111 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 27 | 23% |
Student > Master | 22 | 19% |
Student > Bachelor | 15 | 13% |
Researcher | 12 | 10% |
Student > Doctoral Student | 6 | 5% |
Other | 14 | 12% |
Unknown | 20 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 38 | 33% |
Biochemistry, Genetics and Molecular Biology | 21 | 18% |
Neuroscience | 16 | 14% |
Medicine and Dentistry | 4 | 3% |
Engineering | 4 | 3% |
Other | 10 | 9% |
Unknown | 23 | 20% |