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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using mice to model Alzheimer's dementia: an overview of the clinical disease and the preclinical behavioral changes in 10 mouse models
|
|---|---|
| Published in |
Frontiers in Genetics, April 2014
|
| DOI | 10.3389/fgene.2014.00088 |
| Pubmed ID | |
| Authors |
Scott J. Webster, Adam D. Bachstetter, Peter T. Nelson, Frederick A. Schmitt, Linda J. Van Eldik |
| Abstract |
The goal of this review is to discuss how behavioral tests in mice relate to the pathological and neuropsychological features seen in human Alzheimer's disease (AD), and present a comprehensive analysis of the temporal progression of behavioral impairments in commonly used AD mouse models that contain mutations in amyloid precursor protein (APP). We begin with a brief overview of the neuropathological changes seen in the AD brain and an outline of some of the clinical neuropsychological assessments used to measure cognitive deficits associated with the disease. This is followed by a critical assessment of behavioral tasks that are used in AD mice to model the cognitive changes seen in the human disease. Behavioral tests discussed include spatial memory tests [Morris water maze (MWM), radial arm water maze (RAWM), Barnes maze], associative learning tasks (passive avoidance, fear conditioning), alternation tasks (Y-Maze/T-Maze), recognition memory tasks (Novel Object Recognition), attentional tasks (3 and 5 choice serial reaction time), set-shifting tasks, and reversal learning tasks. We discuss the strengths and weaknesses of each of these behavioral tasks, and how they may correlate with clinical assessments in humans. Finally, the temporal progression of both cognitive and non-cognitive deficits in 10 AD mouse models (PDAPP, TG2576, APP23, TgCRND8, J20, APP/PS1, TG2576 + PS1 (M146L), APP/PS1 KI, 5×FAD, and 3×Tg-AD) are discussed in detail. Mouse models of AD and the behavioral tasks used in conjunction with those models are immensely important in contributing to our knowledge of disease progression and are a useful tool to study AD pathophysiology and the resulting cognitive deficits. However, investigators need to be aware of the potential weaknesses of the available preclinical models in terms of their ability to model cognitive changes observed in human AD. It is our hope that this review will assist investigators in selecting an appropriate mouse model, and accompanying behavioral paradigms to investigate different aspects of AD pathology and disease progression. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 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 1,186 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 5 | <1% |
| United States | 5 | <1% |
| Germany | 3 | <1% |
| France | 2 | <1% |
| Israel | 1 | <1% |
| Mexico | 1 | <1% |
| Italy | 1 | <1% |
| Belgium | 1 | <1% |
| Indonesia | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 1164 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 231 | 19% |
| Student > Bachelor | 175 | 15% |
| Researcher | 162 | 14% |
| Student > Master | 158 | 13% |
| Student > Doctoral Student | 57 | 5% |
| Other | 163 | 14% |
| Unknown | 240 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 280 | 24% |
| Agricultural and Biological Sciences | 229 | 19% |
| Biochemistry, Genetics and Molecular Biology | 113 | 10% |
| Medicine and Dentistry | 99 | 8% |
| Psychology | 48 | 4% |
| Other | 133 | 11% |
| Unknown | 284 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 15 November 2023.
All research outputs
#2,669,698
of 26,017,215 outputs
Outputs from Frontiers in Genetics
#636
of 13,784 outputs
Outputs of similar age
#25,957
of 244,505 outputs
Outputs of similar age from Frontiers in Genetics
#11
of 109 outputs
Altmetric has tracked 26,017,215 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 13,784 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 95% 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 244,505 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 89% of its contemporaries.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.