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        <title>Alzheimer&apos;s Research &amp; Therapy - Most accessed articles</title>
        <link>http://alzres.com</link>
        <description>The most accessed research articles published by Alzheimer&apos;s Research &amp; Therapy</description>
        <dc:date>2012-05-09T00:00:00Z</dc:date>
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        <title>Examining the mechanisms that link beta-amyloid 
and alpha-synuclein pathologies
</title>
        <description>&#946;-amyloid (A&#946;) and &#945;-synuclein (&#945;-syn) are aggregation-prone proteins typically associated with two distinct neurodegenerative disorders: Alzheimer&apos;s disease (AD) and Parkinson&apos;s disease. Yet &#945;-syn was first found in association with AD plaques several years before being linked to Parkinson&apos;s disease or Lewy body formation. Nowadays, a large subset of AD patients (~50%) is well recognized to co-exhibit significant &#945;-syn Lewy body pathology. Unfortunately, these AD Lewy body variant patients suffer from additional symptoms and an accelerated disease course. Basic research has begun to show that A&#946; and &#945;-syn may act synergistically to promote the aggregation and accumulation of each other. While the exact mechanisms by which these proteins interact remain unclear, growing evidence suggests that A&#946; may drive &#945;-syn pathology by impairing protein clearance, activating inflammation, enhancing phosphorylation, or directly promoting aggregation. This review examines the interactions between A&#946; and &#945;-syn and proposes potential mechanistic links between A&#946; accumulation and &#945;-syn pathogenesis.</description>
        <link>http://alzres.com/content/4/2/11</link>
                <dc:creator>Samuel Marsh</dc:creator>
                <dc:creator>Mathew Blurton-Jones</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:11</dc:source>
        <dc:date>2012-04-30T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt109</dc:identifier>
                            <dc:title>&amp;#946;-amyloid and &amp;#945;-synuclein interaction</dc:title>
                            <dc:description>Marsh and Blurton-Jones review evidence suggesting &amp;#946;-amyloid (A&amp;#946;) and &amp;#945;-synuclein (&amp;#945;-syn) interact synergistically to enhance aggregation and accelerate cognitive decline, and propose potential mechanistic links between A&amp;#946; and &amp;#945;-syn pathologies.</dc:description>
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        <item rdf:about="http://alzres.com/content/4/3/13">
        <title>Long-term benefit from deep brain stimulation of the subthalamic nucleus: Is it for everyone?</title>
        <description>Although deep brain stimulation (DBS) has revolutionized our approach to therapy for patients with advanced Parkinson&apos;s disease, many questions remain. Should DBS be instituted earlier in the course of the disease? Why do some patients show striking improvements whereas others show limited benefit even when lead locations appear to be similar? Why can some patients markedly reduce medications whereas others cannot? What is the optimal target site for DBS and how does it work? One question that has long been asked but only recently become addressable is how long the therapeutic effect of DBS can be sustained in the face of what is still a progressive, neurodegenerative disease? A recent article by Castrioto and colleagues, &apos;Ten-year outcome of subthalamic stimulation in Parkinson disease&apos;, seeks to address this question. The authors report significant improvement at 10 years following the onset of subthalamic nucleus DBS in the off UPDRS (Unified Parkinson&apos;s Disease Rating Scale) III total motor score, tremor and bradykinesia subscores, UPDRS II meds on and off scores, and UPDRS IV dyskinesia and motor fluctuation score as well as a significant reduction in the levodopa equivalent daily dose when compared with baseline. Does this finally answer our question of the longevity of DBS? I would suggest not. The article by Castrioto and colleagues provides evidence that some patients can expect improvement for 10 years or longer. However, the young age of onset for patients in this study (average of less than 40 years) combined with a substantial loss of patients to follow-up (23 out of 41) likely leads to a data set that was biased in favor of better long-term outcomes, making it unlikely that the data from this study can be applied to the majority of older patients undergoing DBS, who are more likely to follow a more progressive course. Thus, the present findings are encouraging for some but are not likely to be predictive for all or even for most of the patients currently undergoing this procedure. In spite of these problems, one cannot help but be encouraged by the results of a study that was done early in the course of implementing DBS and that shows continued improvement for patients as long as 10 years following implantation.</description>
        <link>http://alzres.com/content/4/3/13</link>
                <dc:creator>Jerrold Vitek</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:13</dc:source>
        <dc:date>2012-05-09T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt111</dc:identifier>
                            <dc:title>Deep brain stimulation in PD</dc:title>
                            <dc:description>Jerrold Vitek comments on a recent research article addressing how long the benefits of deep brain stimulation for the treatment of Parkinson&apos;s disease (PD) can be sustained.</dc:description>
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        <item rdf:about="http://alzres.com/content/4/1/6">
        <title>Dementia prevention: current epidemiological evidence and future perspective</title>
        <description>Dementia, a major cause of disability and institutionalization in older people, poses a serious threat to public health and to the social and economic development of modern society. Alzheimer&apos;s disease (AD) and cerebrovascular diseases are the main causes of dementia; most dementia cases are attributable to both vascular and neurodegenerative brain damage. No curative treatment is available, but epidemiological research provides a substantial amount of evidence of modifiable risk and protective factors that can be addressed to prevent or delay onset of AD and dementia. Risk of late-life dementia is determined by exposures to multiple factors experienced over the life course, and the effect of specific risk/protective factors depends largely on age. Moreover, cumulative and combined exposure to different risk/protective factors can modify their effect on dementia/AD risk. Multidisciplinary research involving epidemiology, neuropathology, and neuroimaging has provided sufficient evidence that vascular risk factors significantly contribute to the expression and progression of cognitive decline (including dementia) but that active engagement in social, physical, and mentally stimulating activities may delay the onset of dementia. However, these findings need to be confirmed by randomized controlled trials (RCTs). A promising strategy for preventing dementia is to implement intervention programs that take into account both the life-course model and the multifactorial nature of this syndrome. In Europe, there are three ongoing multidomain interventional RCTs that focus on the optimal management of vascular risk factors and vascular diseases. The RCTs include medical and lifestyle interventions and promote social, mental, and physical activities aimed at increasing the cognitive reserve. These studies will provide new insights into prevention of cognitive impairment and dementia. Such knowledge can help researchers plan larger, international prevention trials that could provide robust evidence on dementia/AD prevention. Taking a step in this direction, researchers involved in these European RCTs recently started the European Dementia Prevention Initiative, an international collaboration aiming to improve strategies for preventing dementia.</description>
        <link>http://alzres.com/content/4/1/6</link>
                <dc:creator>Francesca Mangialasche</dc:creator>
                <dc:creator>Miia Kivipelto</dc:creator>
                <dc:creator>Alina Solomon</dc:creator>
                <dc:creator>Laura Fratiglioni</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:6</dc:source>
        <dc:date>2012-02-13T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt104</dc:identifier>
                            <dc:title>Preventative measures for AD and dementia</dc:title>
                            <dc:description>Mangialasche and colleagues address current epidemiological research and intervention studies to identify promising preventative strategies for Alzheimer&apos;s disease (AD) and dementia; considering the need for randomized controlled trials to confirm these findings.</dc:description>
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        <item rdf:about="http://alzres.com/content/4/2/10">
        <title>Relationships between the amyloid precursor protein and its various proteolytic fragments with neuronal systems</title>
        <description>Alzheimer&apos;s disease (AD) is a progressive neurodegenerative disease and in its familial form is associated with mutations in the amyloid precursor protein (APP) and the presenilins (PSs). Much data regarding the interactions of APP, its proteolytic fragments and PS have been generated, expanding our understanding of the roles of these proteins in mechanisms underlying cognitive function and revealing many complex relationships with wide ranging cellular systems. In this review, we examine the multiple interactions of APP and its proteolytic fragments with other neuronal systems in terms of feedback loops and use these relationships to build a map. We highlight the complexity involved in the APP proteolytic system and discuss alternative perspectives on the roles of APP and its proteolytic fragments in dynamic processes associated with disease progression in AD. We highlight areas where data are missing and suggest potential confounding factors. We suggest that a systems biology approach enhances representations of the data and may be more useful in modelling both normal cognition and disease processes.</description>
        <link>http://alzres.com/content/4/2/10</link>
                <dc:creator>Sally Hunter</dc:creator>
                <dc:creator>Carol Brayne</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:10</dc:source>
        <dc:date>2012-04-13T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt108</dc:identifier>
                            <dc:title>APP proteolytic system interactions</dc:title>
                            <dc:description>Hunter and Brayne build a map, modelling relationships between the amyloid precursor protein (APP) and its proteolytic fragments with other neuronal systems and discussing alternative perspectives for its role in Alzheimer&apos;s disease progression.</dc:description>
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        <prism:startingPage>10</prism:startingPage>
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        <item rdf:about="http://alzres.com/content/4/2/7">
        <title>Cognitive reserve, cortical plasticity and resistance to Alzheimer&amp;apos;s disease</title>
        <description>There are aspects of the ageing brain and cognition that remain poorly understood despite intensive efforts to understand how they are related. Cognitive reserve is the concept that has been developed to explain how it is that some elderly people with extensive neuropathology associated with dementia show little in the way of cognitive decline. Cognitive reserve is intimately related to cortical plasticity but this also, as it relates to ageing, remains poorly understood at the present time. Despite the shortcomings in understanding, we do have some knowledge on which to base efforts to minimise the likelihood of an elderly person developing dementia. For some risks the evidence is far from secure, but resistance to Alzheimer&apos;s disease (AD) appears from epidemiological studies to be contributed to by avoiding hypertension in middle life, obesity, depression, smoking and diabetes and head injury and by undertaking extended years of education, physical exercise, and social and intellectual pursuits in middle and late life. Nutritional factors may also promote healthy brain ageing. Resistance to AD is also contributed to by genetic factors, particularly apolipoprotein E2, but some combinations of other genetic polymorphisms as well. Although multiple factors and possible interventions may influence cognitive reserve and susceptibility to dementia, much more work is required on the mechanisms of action in order to determine which, if any, may improve the clinical and epidemiological picture. Understanding of how such factors operate may lead to new initiatives to keep the elderly population in the 21st century able to lead active and fulfilling lives.</description>
        <link>http://alzres.com/content/4/2/7</link>
                <dc:creator>Margaret Esiri</dc:creator>
                <dc:creator>Steven Chance</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:7</dc:source>
        <dc:date>2012-03-01T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt105</dc:identifier>
                            <dc:title>AD susceptibility in the ageing brain</dc:title>
                            <dc:description>Esiri and Chance discuss the impact of epidemiological factors on cognitive reserve and cortical plasticity, which act as preventative factors against cognitive decline and the development of Alzheimer&apos;s disease (AD) in the elderly.</dc:description>
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        <item rdf:about="http://alzres.com/content/4/2/12">
        <title>Reduction of low-density lipoprotein receptor-related protein (LRP1) in hippocampal
neurons does not proportionately reduce, or otherwise alter, amyloid deposition in
APPswe/PS1dE9 transgenic mice</title>
        <description>IntroductionThe low-density lipoprotein receptor-related protein (LRP1) and its family members have been implicated in the pathogenesis of Alzheimer&apos;s disease. Multiple susceptibility factors converge to metabolic pathways that involve LRP1, including modulation of the processing of amyloid precursor protein (APP) and the clearance of Abeta peptide.
Methods:
We used the Cre recombinase-Lox P site system (Cre-lox) system to lower LRP1 levels in hippocampal neurons of mice that develop Alzheimer-type amyloid by crosses between mice that express Cre recombinase under the transcriptional control of the glial fibrillary acidic protein (GFAP) promoter, mice that harbor loxp sites in the LRP1 gene, and the APPswe/PS1dE9 transgenic model. We compared amyloid plaque numbers in APPswe/PS1dE9 mice lacking LRP1 expression in hippocampus (n=13) to mice with normal levels of LRP1 (n=12).  Student t-test was used to test whether there were significant differences in plaque numbers and amyloid levels between the groups. F-test was used to test the significance of differences in the regression curves of amyloid deposition with aging.
Results:
Immunohistochemical analyses demonstrated efficient elimination of LRP1 expression in the CA fields and dentate gyrus of the hippocampus. Within hippocampus, we observed no effect on the severity of amyloid deposition, the rate of Abeta40/42 accumulation, or the architecture of amyloid plaques when LRP1 levels were reduced.
Conclusions:
Expression of LRP1 by neurons in proximity to senile amyloid plaques does not appear to play a major role in modulating the formation of these proximal deposits or in the appearance of the associated neuritic pathology.</description>
        <link>http://alzres.com/content/4/2/12</link>
                <dc:creator>Guilian Xu</dc:creator>
                <dc:creator>Cameron Green</dc:creator>
                <dc:creator>Susan Fromholt</dc:creator>
                <dc:creator>David Borchelt</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:12</dc:source>
        <dc:date>2012-04-26T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt110</dc:identifier>
                            <dc:title>LRP1 in amyloid deposition</dc:title>
                            <dc:description>Reduction in levels of low-density lipoprotein receptor-related protein (LRP1) in an in vivo mouse model failed to observe a reduction in amyloidosis, questioning its significance as a potential therapeutic target for Alzheimer&apos;s disease.</dc:description>
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        <prism:startingPage>12</prism:startingPage>
        <prism:publicationDate>2012-04-26T00:00:00Z</prism:publicationDate>
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        <item rdf:about="http://alzres.com/content/2/4/24">
        <title>Review of Alzheimer&apos;s disease scales: is there a need for a new multi-domain scale for therapy evaluation in medical practice?</title>
        <description>IntroductionThe present review of Alzheimer&apos;s disease (AD) rating scales aims to outline the need for a new rating scale to be used in routine clinical practice for long-term medical care of AD patients. An ideal scale would be: 1) practical, easy and quick to administer for an experienced clinician; 2) validated for AD; 3) multi-domain: covering the AD-relevant areas of cognition, activities of daily living, behavior, communication/social interaction, and quality of life; 4) applicable to all AD severity stages; 5) able to monitor disease progression; and 6) sensitive to measure therapy effects.
Methods:
The National Library of Medicines&apos; MEDLINE database was searched for the years 1981 to September 2008, using a set of keywords aiming to select instruments which cover at least some of the requirements for an ideal practical AD scale for therapy evaluation. Measures for AD staging and screening tests were not considered for review.
Results:
Of 1,902 articles resulting from the literature search, 68 relevant AD scales were identified. Most of them were scales that predominantly measure the severity of major dysfunctions in particular AD domains. Only five scales met some of the requirements for a practical multi-domain AD scale, but did not possess all required characteristics.
Conclusions:
Despite the multitude of AD scales for various purposes, there remains a need for a new multi-domain and easy to administer AD scale for assessment of disease progression and response to therapy in daily medical practice.</description>
        <link>http://alzres.com/content/2/4/24</link>
                <dc:creator>Philippe Robert</dc:creator>
                <dc:creator>Steven Ferris</dc:creator>
                <dc:creator>Serge Gauthier</dc:creator>
                <dc:creator>Ralf Ihl</dc:creator>
                <dc:creator>Bengt Winblad</dc:creator>
                <dc:creator>Frank Tennigkeit</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2010, null:24</dc:source>
        <dc:date>2010-08-26T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt48</dc:identifier>
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                <prism:publicationName>Alzheimer&apos;s Research &amp; Therapy</prism:publicationName>
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        <prism:startingPage>24</prism:startingPage>
        <prism:publicationDate>2010-08-26T00:00:00Z</prism:publicationDate>
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        <item rdf:about="http://alzres.com/content/4/2/9">
        <title>Molecular consequences of amyloid precursor protein and presenilin mutations causing autosomal-dominant 
Alzheimer&apos;s disease
</title>
        <description>Mutations in both the amyloid precursor protein (APP) and the presenilin (PSEN) genes cause familial Alzheimer&apos;s disease (FAD) with autosomal dominant inheritance and early onset of disease. The clinical course and neuropathology of FAD and sporadic Alzheimer&apos;s disease are highly similar, and patients with FAD constitute a unique population in which to conduct treatment and, in particular, prevention trials with novel pharmaceutical entities. It is critical, therefore, to exactly defi ne the molecular consequences of APP and PSEN FAD mutations. Both APP and PSEN mutations drive amyloidosis in FAD patients through changes in the brain metabolism of amyloid-&#946; (A&#946;) peptides that promote the formation of pathogenic aggregates. APP mutations do not seem to impair the physiological functions of APP. In contrast, it has been proposed that PSEN mutations compromise &#947;-secretase-dependent and -independent functions of PSEN. However, PSEN mutations have mostly been studied in model systems that do not accurately refl ect the genetic background in FAD patients. In this review, we discuss the reported cellular phenotypes of APP and PSEN mutations, the current understanding of their molecular mechanisms, the need to generate faithful models of PSEN mutations, and the potential bias of APP and PSEN mutations on therapeutic strategies that target A&#946;.</description>
        <link>http://alzres.com/content/4/2/9</link>
                <dc:creator>Sascha Weggen</dc:creator>
                <dc:creator>Dirk Beher</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:9</dc:source>
        <dc:date>2012-03-30T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt107</dc:identifier>
                            <dc:title>FAD: from genotype to phenotype</dc:title>
                            <dc:description>The molecular consequences of amyloid precursor protein and presenilin gene mutations in familial Alzheimer&apos;s disease (FAD) are examined by Weggen and Beher; in view of potential therapeutic treatments directed at amyloid-beta peptides.</dc:description>
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                <prism:publicationName>Alzheimer&apos;s Research &amp; Therapy</prism:publicationName>
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        <prism:startingPage>9</prism:startingPage>
        <prism:publicationDate>2012-03-30T00:00:00Z</prism:publicationDate>
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        <item rdf:about="http://alzres.com/content/2/1/2">
        <title>Predicting progression of Alzheimer&apos;s disease</title>
        <description>IntroductionClinicians need to predict prognosis of Alzheimer&apos;s disease (AD), and researchers need models of progression to develop biomarkers and clinical trials designs. We tested a calculated initial progression rate to see whether it predicted performance on cognition, function and behavior over time, and to see whether it predicted survival.
Methods:
We used standardized approaches to assess baseline characteristics and to estimate disease duration, and calculated the initial (pre-progression) rate in 597 AD patients followed for up to 15 years. We designated slow, intermediate and rapidly progressing groups. Using mixed effects regression analysis, we examined the predictive value of a pre-progression group for longitudinal performance on standardized measures. We used Cox survival analysis to compare survival time by progression group.
Results:
Patients in the slow and intermediate groups maintained better performance on the cognitive (ADAScog and VSAT), global (CDR-SB) and complex activities of daily living measures (IADL) (P values &lt; 0.001 slow versus fast; P values &lt; 0.003 to 0.03 intermediate versus fast). Interaction terms indicated that slopes of ADAScog and PSMS change for the slow group were smaller than for the fast group, and that rates of change on the ADAScog were also slower for the intermediate group, but that CDR-SB rates increased in this group relative to the fast group. Slow progressors survived longer than fast progressors (P = 0.024).
Conclusions:
A simple, calculated progression rate at the initial visit gives reliable information regarding performance over time on cognition, global performance and activities of daily living. The slowest progression group also survives longer. This baseline measure should be considered in the design of long duration Alzheimer&apos;s disease clinical trials.</description>
        <link>http://alzres.com/content/2/1/2</link>
                <dc:creator>Rachelle Doody</dc:creator>
                <dc:creator>Valory Pavlik</dc:creator>
                <dc:creator>Paul Massman</dc:creator>
                <dc:creator>Susan Rountree</dc:creator>
                <dc:creator>Eveleen Darby</dc:creator>
                <dc:creator>Wenyaw Chan</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2010, null:2</dc:source>
        <dc:date>2010-02-23T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt25</dc:identifier>
                            <dc:title>Alzheimer&amp;#8217;s progression can be predicted </dc:title>
                            <dc:description>Baseline cognitive assessments of probable Alzheimer&amp;#8217;s disease patients can help predict future performance in cognition and activities of daily living, and should be considered when designing clinical trials in Alzheimer&amp;#8217;s disease.</dc:description>
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        <prism:startingPage>2</prism:startingPage>
        <prism:publicationDate>2010-02-23T00:00:00Z</prism:publicationDate>
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        <title>Resting-state fMRI as a biomarker for Alzheimer&amp;apos;s disease?</title>
        <description>Previous work indicates that resting-state functional magnetic resonance imaging (fMRI) is sensitive to functional brain changes related to Alzheimer&apos;s disease (AD) pathology across the clinical spectrum. Cross-sectional studies have found functional connectivity differences in the brain&apos;s default mode network in aging, mild cognitive impairment, and AD. In addition, two recent longitudinal studies have shown that functional connectivity changes track AD progression. This earlier work suggests that resting-state fMRI may be a promising biomarker for AD. However, some key issues still need to be addressed before resting-state fMRI can be successfully applied clinically. In a previous issue of Alzheimer&apos;s Research &amp; Therapy, Vemuri and colleagues discuss the use of resting-state fMRI in the study of AD. In this commentary, I will highlight and expand upon some of their main conclusions.</description>
        <link>http://alzres.com/content/4/2/8</link>
                <dc:creator>Jessica Damoiseaux</dc:creator>
                <dc:source>Alzheimer&apos;s Research &amp; Therapy 2012, null:8</dc:source>
        <dc:date>2012-03-15T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/alzrt106</dc:identifier>
                            <dc:title>Clinical uses and issues of fMRI</dc:title>
                            <dc:description>Damoiseaux comments on a recent review discussing resting-state functional magnetic resonance imaging (fMRI) in the study of Alzheimer&apos;s disease, considering key aspects surrounding its biomarker potential.</dc:description>
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                <prism:publicationName>Alzheimer&apos;s Research &amp; Therapy</prism:publicationName>
        <prism:issn>1758-9193</prism:issn>
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        <prism:startingPage>8</prism:startingPage>
        <prism:publicationDate>2012-03-15T00:00:00Z</prism:publicationDate>
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