bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combined caloric restriction and exercise provides the best benefit in obese brain
Authors: Pratchayasakul Wasana , Mantor Duangkamol , Suparan Kanokphong , Sangtragul Teepaka , Keawtep Puntarik , Chunchai Titikorn , Kerdphoo Sasiwan , Jaiwongkam Thidarat , Palee Siripong , Chattipakorn Nipon , Chattipakorn Siriporn C. 
Published: December 2020

AbstractBackgroundLifestyle modification, including dietary intervention or exercise training, has beneficial effects on the improvement of metabolic and brain function in cases of metabolic syndrome, diabetes and Alzheimer’s disease. However, the comparative effects of calorie restriction, exercise training, and a combination of calorie restriction and exercise training on brain and cognitive function in the obese condition have not been thoroughly investigated. Our hypothesis is that both calorie restriction and exercise training improve brain and cognitive function in an obese condition, but a combination of these two therapies has a greater efficacy in the restoration of brain functions and cognition than either single therapy.MethodTwenty‐five female rats were fed with either a normal diet (ND; n=5) or a high‐fat diet (HFD; n=20) for 27 weeks. At week 20, the ND‐fed rats were assigned to a sedentary lifestyle (NDS; n=5), and HFD‐fed rats were assigned to either a sedentary lifestyle (HFS; n=5), calorie restriction (HFCR; n=5), exercise (HFEX; n=5) or a combination of calorie restriction and exercise (HFCB; n=5) for 7 weeks. After that, metabolic parameters, brain parameters and cognition were determined.ResultHFD‐fed rats developed insulin resistance and cognitive decline via increased oxidative stress, inflammation, apoptosis, and synaptic dysfunction in the hippocampus. Calorie restriction decreased metabolic disturbance, decreased inflammation and oxidative stress in the hippocampus, but failed to improve cognition in HFD‐fed rats. Exercise attenuated metabolic disorders, oxidative stress, inflammation, apoptosis, and synaptic dysfunction, resulting in improved cognition in HFD‐fed rats, while the combined therapy had the greatest beneficial effect on this improvement (p<0.05, Figure 1).ConclusionA combination of calorie restriction and exercise may be the best therapeutic approach for the restoration of brain and cognitive function in the obese condition.
Effect of transthyretin gene therapy in the 5XFAD mouse model of Alzheimer’s disease
Authors: Batista Ana Rita , Rodriguez Paola , Otero Monique , King Robert M. , Gounis Matthew J. , Sena‐Esteves Miguel 
Published: December 2020

AbstractBackgroundEpidemiological studies and work in transgenic animals suggest that transthyretin (TTR) levels in plasma and/or CSF may modulate Alzheimer’s disease (AD) presentation and/or progression. AD patients exhibit lower levels of TTR in CSF compared to age‐matched healthy individuals. Similarly, genetic reduction of TTR in mouse models of AD is associated with earlier onset and more severe phenotypes. The current study was designed to determine the potential of somatic AAV mediated TTR expression to modulate disease presentation in AD.MethodWe designed an AAV9 vector to express TTR specifically in liver and choroid plexus using a TTR promoter to drive transgene expression. Two months old male and female 5XFAD mice were injected systemically with 2E12 gc AAV9‐TTRp‐TTRT119M (n=3M+6F), or PBS as controls (n=3M+6F). At nine months of age animals were subjected to neurobehavioral tests to assess cognitive function, and 3D isotropic T2‐weighted MRI to evaluate differences in brain volume.ResultCognitive function was assessed through measure of working and spatial memory using forced and spontaneous alternation tasks in the Y‐maze, and novel object recognition tests. All treated animals showed increased recognition index of novel objects, increased % of alternation, and % time in novel arm, compared to controls. General locomotion and anxiety were evaluated using the open field test, where AAV treated females presented higher locomotor activity and decreased anxiety levels. Interestingly, MRI revealed increased CSF volume in all treated animals compared to controls, with females showing larger differences.ConclusionOur initial results show that systemic delivery of an AAV9 vector that expresses TTR in appropriate tissues improves overall cognitive function, locomotor activity and anxiety symptoms in 5XFAD mice; Interestingly more noticeably in females. The unexpected increase in CSF volume may be related to increased TTR production by the choroid plexus of AAV treated animals, and additional experiments are ongoing to determine the cause of this outcome. Biochemical and histological studies of the brain are currently ongoing to assess the disease status in all experimental groups. This new AAV vector is an outstanding platform for therapeutic development and addresses biologically relevant questions about the role of TTR in AD.
Sleep‐dependent association between atrophy and functional connectivity in mild cognitive impairment
Authors: Wennberg Alexandra MV , Pini Lorenzo , Mitolo Micaela , Meneghello Francesca , Burgio Francesca , Semenza Carlo , Venneri Annalena , Mantini Dante , Vallesi Antonino 
Published: December 2020

AbstractBackgroundSleep quality might influence the risk of developing Alzheimer’s disease (AD) in mild cognitive impairment (MCI) patients, driving alterations in brain morphology and functional connectivity. However, the relationship between sleep, gray matter atrophy, and functional connectivity is poorly understood. The present study aims to compare levels of these brain alterations associated with sleep habits in MCI patients.MethodStructural magnetic resonance imaging (MRI) and resting‐state functional MRI (rs‐fMRI) data from 38 MCI and 38 age‐matched controls were analyzed to investigate atrophy and connectivity, respectively. MCI were stratified into “good” (n=20) and “poor” (n=18) sleepers, stratified at the 50th percentile of the Sleep Continuity in Alzheimer’s Disease Scale, a self‐report questionnaire assessing sleeping quality. Independent component analysis was used to identify the default mode (DMN) and frontoparietal (FPN) networks. For each patient and modality (i.e., structural and rs‐fMRI), z‐score maps were computed based on the control sample. Moreover, for each subject and network, a composite z‐score map across modalities was computed with the following formula: z‐score atrophy – z‐score connectivity. Voxelwise between‐modality comparisons were performed with nonparametric inference using FSL randomise (n=5000 permutations). Multiple comparisons were corrected at a threshold‐free‐cluster enhancement level of p < 0.025 FWE‐corrected.ResultConnectivity DMN values within the precuneus significantly exceed atrophy in both MCI groups. By contrast, only MCI good sleepers showed connectivity FPN values exceeding atrophy, widespread in frontal, temporal, and parietal regions. Finally, comparing MCI groups using composite z‐score maps, we reported significant FPN connectivity values exceeding atrophy within the right inferior frontal gyrus in MCI good sleeper.ConclusionThese findings suggest that, among MCI patients, sleep quality may influence the relationship between brain morphology and functional connectivity, resulting in FPN connectivity exceeding atrophy. Our findings might suggest different sleep‐induced slopes in brain atrophy and connectivity within the FPN network. These results might offer novel targets and surrogate outcomes for interventions aimed at restoring sleep disorders in MCI.
Waiting for results of RECage clinical trial: A preliminary context analysis
Authors: Fascendini Sara , Barocco Federica , Mara Zanni , Cosetta Sangiovanni , De Fanti Carlo Alberto , Avesani Mirko , Stucchi Carlo Maria , Matarazzo Carmine , Elena Mariani , Cristina Cilia Maria , Ciccone Alfonso , Casanova Georgia 
Published: December 2020

AbstractBackgroundThe RECage Project, funded by the European Commission, in the framework of the H2020 RIA projects, has a threefold objective: a) to validate a clinical intervention (the Special Care Unit for Behavioural and Psychological Symptoms of Dementia: acronym SCU‐B); b) to adapt it and produce a consensus document on a model SCU‐B c) to promote the implementation and scaling up of the intervention.The first objective is pursued through a clinical trial comparing two cohorts of persons with dementia of any etiology and important BPSD, the first one followed by clinical centres endowed with a SCU‐B and the second by centres lacking this facility. The study involves 520 patients and the follow‐up will last three years. Presently the recruitment phase has just ended and the results are foreseen in 2023. The clinical centres are located in six countries: Italy, France, Germany, Greece, Switzerland and Norway.MethodIn order to provide useful data for the second and third phase of the Recage project the Consortium decided to conduct a qualitative analysis in two Italian centres, the one with SCU‐B (Gazzaniga) and the other without SCU‐B (Mantova).The aims of this qualitative study were: to provide context and needs analysis for each case, underlying strengths, weaknesses, opportunities and threats (SWOT analysis); to identify the (social) innovations promoted by SCU‐B experiences; to identify the replicability characteristics of the SCU‐Bs, to support its implementation in different context. Seven expert interviews and four focus groups have been conducted, with 40 experts and stakeholders involved by specific invitation. The focus groups have been carried out both with the professionals (physicians, physiotherapists, psychologists, occupational therapists, nursing assistants, nurses, educational workers) and with the local stakeholders (local institutions, social services, volunteers, GPs, informal caregivers).ResultThe qualitative analysis shows that: the SCU‐B promotes social innovation; there are opportunities to promote SI and to build a SCU‐B in context in which it is lacking; currently, the complete system seems less replicable than some specific part of it.ConclusionWe hope that these preliminary results can be confirmed by future analysis and help the development of new SCU‐B.
Early dysregulation of neuronal activities in models of Alzheimer’s disease
Authors: Busche Marc A. 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is a fatal brain disease with a massive societal impact. Identifying effective treatments for AD has proven extremely challenging and has instigated a recent shift in AD research focus towards the earliest disease‐initiating cellular and circuit processes.MethodWe employ in vivo multiphoton calcium imaging alone and in combination with electrophysiological recordings to determine how the abnormal accumulation of proteins (ie, amyloid‐beta and tau) in AD mouse models affects the activity of brain circuits and their components.ResultWe find that soluble amyloid‐beta causes hyperexcitability of neurons in vivo. In striking contrast, tau, even before tangles form, suppresses neuronal activity. Remarkably, the combination of amyloid‐beta and tau leads to suppressed activity as well, as the tau phenotype seems to dominate.ConclusionWe have identified an unexpected functional effect of tau leading to the suppression of brain circuit activity, blocking the pro‐excitatory effects of Abeta. These data help to understand possible reasons for the recent failures of anti‐amyloid therapies for the treatment of AD.
Neuronal network hyperactivity in computational models of AD
Authors: de Haan Willem , van Nifterick Anne M. , Gouw Alida A. , Stam Cornelis J. , Scheltens Philip 
Published: December 2020

AbstractBackgroundNeuronal excitation/inhibition imbalance is a core feature of early Alzheimer’s disease (AD). Although non‐invasive clinical diagnostic methods have not yet reported reliable detection of this phenomenon, MEG studies do report transient increases in oscillatory power and functional network connectivity. However, the relation between these phenomena at different scales is unclear. Computational modeling can be employed to simulate multiscale brain dynamics, relating abnormal neuronal behaviour to brain network impairment. This way, a macroscopic EEG ‘signature’ of underlying neuronal hyperactivity can be predicted.MethodOur dynamic brain network model consists of 78 neural mass models (representing AAL‐atlas brain regions) coupled according to human DTI‐based structural network topology. By altering neural mass parameters, the level of excitability of inhibitory and/or excitatory neurons can be tuned, in order to assess their influence on overall oscillatory network behavior (absolute and relative power, peak frequency and spike density). The model produces EEG‐like neurophysiological data that can be analyzed the same way as patient data. We compared model outcomes with clinical data of amyloid‐positive (CSF) MCI patients.ResultRecent computational brain network modeling experiments show a strong effect of inhibition on oscillatory activity as compared to excitation, in line with existing literature. The scenario most compatible with MCI patient data is ‘global decreased inhibition’, producing a decrease in peak frequency and lower relative alpha power, and higher total and relative theta power. This scenario also resulted in the highest spike density levels.ConclusionThis preliminary study illustrates how computational brain network modeling can aid to construct a coherent framework for the neuropathophysiological findings in AD at different scales of investigation. Although further systematic exploration is needed, computational brain network modeling in AD can become a powerful tool for both research and clinical purposes.
Presynaptic membrane cholesterol homeostasis: A multifactorial contender in Alzheimer’s disease pathogenesis
Authors: Zhang Qi , Stawikowski Maciej 
Published: December 2020

AbstractBackgroundCholesterol (Chol) is highly enriched in the axonal plasma membrane and crucial for exo‐/endocytosis of synaptic vesicles (SVs). At axon terminals, the neuronal activity causes massive SV turnover and in turn perturbs Chol homeostasis between the surface and intracellular membranes. Amyloid precursor protein (APP), enriched at axon terminals, exhibits an intricate association with Cholesterol in multiple aspects. First, it directly binds to Chol via a Chol‐binding motif (CBM) that overlaps with the Abeta sequence. Second, its cleavage by secretases is heavily influenced by Chol. Third, its cleavage products, namely AICD, regulates neurons’ Chol uptake. Our recent work revealed an even more intriguing relationship between APP and neuronal membrane Chol, an inverse correlation between the two in the synaptic membrane.MethodHere, we developed a novel fluorescent reporter for acute surface‐intracellular exchange of Chol at active synapses.ResultSurprisingly, we observed a significantly delayed Chol recycling upon stimulation, which intriguingly coordinates with APP turnover at axon terminals. Moreover, point mutations disrupting APP‐Chol binding disengaged the APP and Chol coordination, and disrupted Chol recycling as well as surface Chol distribution. Such disruption led to disruption in SV regeneration, presynaptic sustainability, and axon membrane integrity after extended stimulation or moderate reduction of membrane Chol. Moreover, familial Alzheimer’s Disease (AD) mutations outside of APP’s Chol‐binding motif but increasing APP surface distribution also altered Chol recycling and distressed axon functionality as well as integrity. Last but not the least, we found AD‐related pathological phenotypes like hyperphosphorylated Tau and gliosis as well as higher death rate in aging APP knockout mice.ConclusionTaking together, we postulate that APP and its proteolytic processing a part of the regulatory mechanism for the homeostasis of neuronal membrane cholesterol. More importantly, presynaptic Chol dysregulation is a multifactorial contender in AD pathogenesis.
Altered resting state activity associated with anosognosia in Alzheimer's clinical syndrome: Findings from the DELCODE study
Authors: Incesoy Enise I. , Metzger Coraline D. , Yakupov Renat , Spottke Annika , Schneider Anja , Fließbach Klaus , Wiltfang Jens , Boecker Henning , Bürger Katharina , Perneczky Robert , Teipel Stefan J. , Laske Christoph , Priller Josef , Jessen Frank , Wagner Michael , Düzel Emrah , Peters Oliver 
Published: December 2020

AbstractBackgroundAnosognosia, or lack of awareness of cognitive impairments, is a common phenomenon in Alzheimer’s clinical syndrome (ACS). Not just patients with dementia(AD) but also patients with mild cognitive impairment(MCI) may have diminished awareness of their deficits. Previous studies have shown that anosognosia is associated with dysfunction and reduced connectivity in the default mode network of the brain and insula. However, less is known about the level of awareness and its neural correlations in individuals with subjective cognitive decline(SCD). This study investigated the underlying neural mechanisms of anosognosia at different stages of ACS.Method504 participants (59 AD, 88 MCI, 176 SCD and 181 healthy controls[HCs]) from the DELCODE, a longitudinal multicenter observational study, were included. Cognitive awareness was assessed with a discrepancy score between participants’ report about their own cognitive abilities and report provided by informants. Resting‐state fMRI data of all subjects were analyzed and the fractional amplitude of low frequency fluctuations(fALFF) were calculated as an index of regional spontaneous neural activity. Voxel‐ and clusterwise correlations were conducted using SPM12, controlling for multiple comparisons(GRF). Age, gender and site (9 sites total) were controlled for in each statistical model.ResultCompared to HCs, subjects with SCD showed heightened awareness for cognitive changes and on the contrary, MCI and AD subjects had higher anosognosia scores. Within‐group comparisons revealed that MCI subjects with anosognosia had reduced neural activity in the left anterior insula compared to MCI subjects without anosognosia (GRF corrected, p<0.005). Moreover, SCD subjects with heightened awareness showed reduced right amygdala activity(GRF corrected, p<0.005), whereas higher activity was observed in the dorsomedial prefrontal cortex (dmPFC) compared to SCD subjects without heightened awareness(GRF corrected, p<0.001).ConclusionThis is the first study evaluating the association between cognitive awareness at different stages of ACS and regional neural activity using fALFF. Consistent with prior findings, MCI subjects with anosognosia showed reduced neural activity in the anterior insula. Heightened awareness in SCD was associated with higher activity in the dmPFC. Future work should examine the interplay between amyloid pathology and fALFF measures for cognitive awareness, in order to specify neural correlates of cognitive awareness in the Alzheimer’s continuum.
The identification of mild cognitive impairment in Parkinson’s disease using EEG and machine learning
Authors: Sweeney Aoife , Devereux Barry , Ong Charlie , McKinley John , Kearney Seamus , Doherty Karen , Foy Julia , Murphy Brian , McGuinness Bernadette , Passmore Anthony Peter 
Published: December 2020

AbstractBackgroundElectroencephalography (EEG) is an inexpensive, non‐invasive and faster method to assess cognition in aging clinical groups. In this study, we are investigating the feasibility of using a ‘dry‐EEG’ mobile headset to assess cognitive impairment in Parkinson’s disease (PD) over a 12‐month period. Cognitive impairment is prevalent in PD with approximately 75% of patients developing dementia within 10 years (Aarsland and Kurz, 2010). The presence of mild cognitive impairment (PD‐MCI) has been associated with increased dementia risk (Pederson et al. 2013). Very little is known about the EEG correlates of PD‐MCI, however EEG has previously been used to predict outcomes in MCI associated with Alzheimer’s disease.Method50 Parkinson’s disease patients and 50 age and sex‐matched controls have completed a battery of baseline neuropsychological and EEG tasks. These tasks measured attention, language, memory, visuospatial and executive function domains. Resting state EEG was also recorded. Event‐related potential components and spectral analyses on the delta, theta and alpha oscillatory bands were computed. Differences between groups were assessed using randomisation tests with FDR‐corrected pairwise comparisons. Random forest, k‐nearest neighbours, support‐vector machine and logistic regression machine learning algorithms were also applied to these data. An identical 12‐month follow‐up assessment will be conducted.ResultFindings from the baseline assessments are presented. 52% of the Parkinson’s disease cohort fulfilled the criteria for MCI. There was no difference in age, education or pre‐morbid IQ between groups. Machine learning classifiers derived from EEG and neuropsychological test metrics discriminated between PD‐MCI, PD normal cognition (PD‐NC) and healthy controls with over 80% accuracy.ConclusionCognitive impairment is prevalent in PD. Our findings show that it is feasible to use dry‐EEG to profile cognition in PD and can differentially discriminate between cognitively normal and cognitively impaired PD patients at an early stage. The features selected are in agreement with the dual syndrome hypothesis of cognition (Kehagia et al., 2013) and those identified in a 10 year follow‐up study (Williams‐Grey et al., 2013). The stability of these features and their ability to predict cognitive status at 12 months will be investigated at a follow‐up assessment.