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Animal models for bipolar disorder: from bedside to the cage

Overview of attention for article published in International Journal of Bipolar Disorders, October 2017
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Title
Animal models for bipolar disorder: from bedside to the cage
Published in
International Journal of Bipolar Disorders, October 2017
DOI 10.1186/s40345-017-0104-6
Pubmed ID
Authors

Dominik K. E. Beyer, Nadja Freund

Abstract

Bipolar disorder is characterized by recurrent manic and depressive episodes. Patients suffering from this disorder experience dramatic mood swings with a wide variety of typical behavioral facets, affecting overall activity, energy, sexual behavior, sense of self, self-esteem, circadian rhythm, cognition, and increased risk for suicide. Effective treatment options are limited and diagnosis can be complicated. To overcome these obstacles, a better understanding of the neurobiology underlying bipolar disorder is needed. Animal models can be useful tools in understanding brain mechanisms associated with certain behavior. The following review discusses several pathological aspects of humans suffering from bipolar disorder and compares these findings with insights obtained from several animal models mimicking diverse facets of its symptomatology. Various sections of the review concentrate on specific topics that are relevant in human patients, namely circadian rhythms, neurotransmitters, focusing on the dopaminergic system, stressful environment, and the immune system. We then explain how these areas have been manipulated to create animal models for the disorder. Even though several approaches have been conducted, there is still a lack of adequate animal models for bipolar disorder. Specifically, most animal models mimic only mania or depression and only a few include the cyclical nature of the human condition. Future studies could therefore focus on modeling both episodes in the same animal model to also have the possibility to investigate the switch from mania-like behavior to depressive-like behavior and vice versa. The use of viral tools and a focus on circadian rhythms and the immune system might make the creation of such animal models possible.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 199 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 39 20%
Student > Ph. D. Student 30 15%
Student > Master 26 13%
Researcher 22 11%
Student > Postgraduate 11 6%
Other 30 15%
Unknown 41 21%
Readers by discipline Count As %
Neuroscience 43 22%
Medicine and Dentistry 17 9%
Psychology 16 8%
Agricultural and Biological Sciences 16 8%
Biochemistry, Genetics and Molecular Biology 14 7%
Other 36 18%
Unknown 57 29%

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 13 October 2017.
All research outputs
#18,572,844
of 23,003,906 outputs
Outputs from International Journal of Bipolar Disorders
#231
of 286 outputs
Outputs of similar age
#249,678
of 325,887 outputs
Outputs of similar age from International Journal of Bipolar Disorders
#7
of 8 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 286 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.1. This one is in the 9th percentile – i.e., 9% 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 325,887 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.