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The Maze of APP Processing in Alzheimer’s Disease: Where Did We Go Wrong in Reasoning?

Overview of attention for article published in Frontiers in Cellular Neuroscience, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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109 Mendeley
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Title
The Maze of APP Processing in Alzheimer’s Disease: Where Did We Go Wrong in Reasoning?
Published in
Frontiers in Cellular Neuroscience, May 2015
DOI 10.3389/fncel.2015.00186
Pubmed ID
Authors

Ming Chen

Abstract

Why has Alzheimer's disease (AD) remained a conundrum today? The main reason is the stagnation in understanding the origins of plaques and tangles. While they are widely thought to be the products of the "aberrant" pathways, we believe that plaques and tangles result from natural aging. From this new perspective, we have proposed that age-related inefficiency of α-secretase is the underpinning for Aβ overproduction. This view contrasts sharply with the current doctrine that Aβ overproduction is the product of the "overactivated" β- and γ-secretases. Following this doctrine, it has been claimed that the two secretases are "positively identified" and that their inhibitors have "successfully reduced Aβ levels." But, why have these studies not led to the understanding of AD or successful clinical trials? And if so, where did they go off course in reasoning? These questions may touch the basics of biological science and must be answered. In this paper, I dissected several prevailing assumptions and some influential reports with an attempt to trace the origins of the conundrum. This work led me to an original model for Aβ overproduction and also to a serious question: given the universal knowledge that boosting α-secretase reduces Aβ, a straightforward highway for intervention, then why is there such an obsession on "inhibiting β- and γ-secretases," a much more costly and twisting road even if possible? This issue requires the attention of policymakers and all researchers. I therefore call for a game change in AD study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
United Kingdom 1 <1%
Unknown 106 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 17%
Student > Master 18 17%
Student > Bachelor 16 15%
Researcher 14 13%
Professor 6 6%
Other 14 13%
Unknown 22 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 21%
Biochemistry, Genetics and Molecular Biology 16 15%
Medicine and Dentistry 14 13%
Neuroscience 10 9%
Pharmacology, Toxicology and Pharmaceutical Science 7 6%
Other 13 12%
Unknown 26 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 January 2018.
All research outputs
#2,651,166
of 22,807,037 outputs
Outputs from Frontiers in Cellular Neuroscience
#452
of 4,241 outputs
Outputs of similar age
#35,641
of 266,679 outputs
Outputs of similar age from Frontiers in Cellular Neuroscience
#15
of 116 outputs
Altmetric has tracked 22,807,037 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,241 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. 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 266,679 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 86% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.