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Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease

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Cover of 'Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction and Technical Survey: Protein Aggregation and Fibrillogenesis
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    Chapter 2 Fibril Formation by Short Synthetic Peptides
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    Chapter 3 In vitro Oligomerization and Fibrillogenesis of Amyloid-beta Peptides
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    Chapter 4 Tau Fibrillogenesis
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    Chapter 5 Prion Protein Aggregation and Fibrillogenesis In Vitro
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    Chapter 6 α-Synuclein Aggregation and Modulating Factors
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    Chapter 7 Pathological Self-Aggregation ofb 2 -Microglobulin: A Challenge for Protein Biophysics
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    Chapter 8 Islet Amyloid Polypeptide: Aggregation and Fibrillogenesisin vitroand Its Inhibition.
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    Chapter 9 Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease
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    Chapter 10 Fibrillogenesis of Huntingtin and Other Glutamine Containing Proteins
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    Chapter 11 Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease
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    Chapter 12 Experimental Inhibition of Peptide Fibrillogenesis by Synthetic Peptides, Carbohydrates and Drugs
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    Chapter 13 Experimental Inhibition of Fibrillogenesis and Neurotoxicity by amyloid-beta (Aβ) and Other Disease-Related Peptides/Proteins by Plant Extracts and Herbal Compounds
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    Chapter 14 Alzheimer's disease.
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    Chapter 15 Modeling the Polyglutamine Aggregation Pathway in Huntington’s Disease: From Basic Studies to Clinical Applications
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    Chapter 16 Parkinson’s Disease
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    Chapter 17 Human prion diseases: from kuru to variant creutzfeldt-jakob disease.
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    Chapter 18 Animal prion diseases.
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    Chapter 19 β(2)-Microglobulin Amyloidosis.
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    Chapter 20 Systemic AA Amyloidosis
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    Chapter 21 Familial amyloidotic polyneuropathy and transthyretin.
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    Chapter 22 The Challenge of Systemic Immunoglobulin Light-Chain Amyloidosis (AL)
Attention for Chapter 14: Alzheimer's disease.
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 377)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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2 news outlets
blogs
1 blog
twitter
2 X users
patent
1 patent
facebook
2 Facebook pages

Citations

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36 Dimensions

Readers on

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641 Mendeley
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Chapter title
Alzheimer's disease.
Chapter number 14
Book title
Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease
Published in
Sub cellular biochemistry, December 2012
DOI 10.1007/978-94-007-5416-4_14
Pubmed ID
Book ISBNs
978-9-40-075415-7, 978-9-40-075416-4
Authors

De-Paula VJ, Radanovic M, Diniz BS, Forlenza OV, De-Paula, Vanessa J., Radanovic, Marcia, Diniz, Breno S., Forlenza, Orestes V., Vanessa J. De-Paula, Marcia Radanovic, Breno S. Diniz, Orestes V. Forlenza

Abstract

Alzheimer's disease (AD) is a chronic neurodegenerative disease with well-defined pathophysiological mechanisms, mostly affecting medial temporal lobe and associative neocortical structures. Neuritic plaques and neurofibrillary tangles represent the pathological hallmarks of AD, and are respectively related to the accumulation of the amyloid-beta peptide (Aβ) in brain tissues, and to cytoskeletal changes that arise from the hyperphosphorylation of microtubule-associated Tau protein in neurons. According to the amyloid hypothesis of AD, the overproduction of Aβ is a consequence of the disruption of homeostatic processes that regulate the proteolytic cleavage of the amyloid precursor protein (APP). Genetic, age-related and environmental factors contribute to a metabolic shift favoring the amyloidogenic processing of APP in detriment of the physiological, secretory pathway. Aβ peptides are generated by the successive cleavage of APP by beta-secretase (BACE-1) and gamma-secretase, which has been recently characterized as part of the presenilin complex. Among several beta-amyloid isoforms that bear subtle differences depending on the number of C-terminal amino acids, Aβ (1-42) plays a pivotal role in the pathogenesis of AD. The neurotoxic potential of the Aβ peptide results from its biochemical properties that favor aggregation into insoluble oligomers and protofibrils. These further originate fibrillary Aβ species that accumulate into senile and neuritic plaques. These processes, along with a reduction of Aβ clearance from the brain, leads to the extracellular accumulation of Aβ, and the subsequent activation of neurotoxic cascades that ultimately lead to cytoskeletal changes, neuronal dysfunction and cellular death. Intracerebral amyloidosis develops in AD patients in an age-dependent manner, but recent evidence indicate that it may be observed in some subjects as early as in the third or fourth decades of life, with increasing magnitude in late middle age, and highest estimates in old age. According to recent propositions, three clinical phases of Alzheimer's disease may be defined: (i) pre-symptomatic (or pre-clinical) AD, which may last for several years or decades until the overproduction and accumulation of Aβ in the brain reaches a critical level that triggers the amyloid cascade; (ii) pre-dementia phase of AD (compatible with the definition of progressive, amnestic mild cognitive impairment), in which early-stage pathology is present, ranging from mild neuronal dystrophy to early-stage Braak pathology, and may last for several years according to individual resilience and brain reserve; (iii) clinically defined dementia phase of AD, in which cognitive and functional impairment is severe enough to surmount the dementia threshold; at this stage there is significant accumulation of neuritic plaques and neurofibrillary tangles in affected brain areas, bearing relationship with the magnitude of global impairment. New technologies based on structural and functional neuroimaging, and on the biochemical analysis of cerebrospinal fluid may depict correlates of intracerebral amyloidosis in individuals with mild, pre-dementia symptoms. These methods are commonly referred to as AD-related biomarkers, and the combination of clinical and biological information yields good diagnostic accuracy to identify individuals at high risk of AD. In other words, the characterization of pathogenic Aβ by means of biochemical analysis of biological fluids or by molecular neuroimaging are presented as diagnostic tools to help identify AD cases at the earliest stages of the disease process. The relevance of this early diagnosis of AD relies on the hypothesis that pharmacological interventions with disease-modifying compounds are more likely to produce clinically relevant benefits if started early enough in the continuum towards dementia. Therapies targeting the modification of amyloid-related cascades may be viewed as promising strategies to attenuate or even to prevent dementia. Therefore, the cumulative knowledge on the pathogenesis of AD derived from basic science models will hopefully be translated into clinical practice in the forthcoming years.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 641 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 3 <1%
United Kingdom 2 <1%
Brazil 1 <1%
Egypt 1 <1%
Unknown 634 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 110 17%
Student > Master 78 12%
Student > Ph. D. Student 63 10%
Researcher 35 5%
Student > Postgraduate 22 3%
Other 55 9%
Unknown 278 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 69 11%
Neuroscience 58 9%
Medicine and Dentistry 53 8%
Agricultural and Biological Sciences 47 7%
Pharmacology, Toxicology and Pharmaceutical Science 41 6%
Other 83 13%
Unknown 290 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 03 November 2023.
All research outputs
#1,224,247
of 24,744,050 outputs
Outputs from Sub cellular biochemistry
#16
of 377 outputs
Outputs of similar age
#10,044
of 288,850 outputs
Outputs of similar age from Sub cellular biochemistry
#3
of 20 outputs
Altmetric has tracked 24,744,050 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 377 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done particularly well, scoring higher than 96% 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 288,850 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.