Ante- and postmortem tau in autosomal dominant and late-onset Alzheimer\u27s disease

Antemortem tau positron emission tomography imaging suggests elevated tau pathology in autosomal dominant versus late-onset Alzheimer\u27s disease at equivalent clinical stages, but does not implicate the specific tau pathologies responsible. Here we made stereological measurements of tau neurofibrillary tangles, neuritic plaques, and neuropil threads and found compared to late-onset Alzheimer\u27s disease, autosomal dominant Alzheimer\u27s disease showed even greater tangle and thread burdens. Regional tau burden resembled that observed in tau imaging of a separate cohort at earlier clinical stages. Finally, our results suggest tau imaging measures total tau burden in Alzheimer\u27s disease, composed predominantly of tangle and thread pathology

Neuroglia at the crossroads of homoeostasis, metabolism and signalling: evolution of the concept

Ever since Rudolf Virchow in 1858 publicly announced his apprehension of neuroglia being a true connective substance, this concept has been evolving to encompass a heterogeneous population of cells with various forms and functions. We briefly compare the 19th–20th century perspectives on neuroglia with the up-to-date view of these cells as an integral, and possibly integrating, component of brain metabolism and signalling in heath and disease. We conclude that the unifying property of otherwise diverse functions of various neuroglial cell sub-types is to maintain brain homoeostasis at different levels, from whole organ to molecular

Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease

Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data. Results Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10−8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10−8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10−6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10−3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10−3) and visual (P = 5.6 × 10−4) cortices. Conclusions Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units

Background: The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. Methods: We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Results: Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Conclusions: Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction. (aut. ref.

Hypothermia-induced hyperphosphorylation: a new model to study tau kinase inhibitors

Tau hyperphosphorylation is one hallmark of Alzheimer's disease (AD) pathology. Pharmaceutical companies have thus developed kinase inhibitors aiming to reduce tau hyperphosphorylation. One obstacle in screening for tau kinase inhibitors is the low phosphorylation levels of AD-related phospho-epitopes in normal adult mice and cultured cells. We have shown that hypothermia induces tau hyperphosphorylation in vitro and in vivo. Here, we hypothesized that hypothermia could be used to assess tau kinase inhibitors efficacy. Hypothermia applied to models of biological gradual complexity such as neuronal-like cells, ex vivo brain slices and adult non-transgenic mice leads to tau hyperphosphorylation at multiple AD-related phospho-epitopes. We show that Glycogen Synthase Kinase-3 inhibitors LiCl and AR-A014418, as well as roscovitine, a cyclin-dependent kinase 5 inhibitor, decrease hypothermia-induced tau hyperphosphorylation, leading to different tau phosphorylation profiles. Therefore, we propose hypothermia-induced hyperphosphorylation as a reliable, fast, convenient and inexpensive tool to screen for tau kinase inhibitors

Results of Large-Scale Testing on Effects of Anti-Foam Agent on Gas Retention and Release

The U.S. Department of Energy (DOE) Office of River Protection’s Waste Treatment Plant (WTP) will process and treat radioactive waste that is stored in tanks at the Hanford Site. The waste treatment process in the pretreatment facility will mix both Newtonian and non-Newtonian slurries in large process tanks. Process vessels mixing non-Newtonian slurries will use pulse jet mixers (PJMs), air sparging, and recirculation pumps. An anti-foam agent (AFA) will be added to the process streams to prevent surface foaming, but may also increase gas holdup and retention within the slurry. The work described in this report addresses gas retention and release in simulants with AFA through testing and analytical studies. Gas holdup and release tests were conducted in a 1/4-scale replica of the lag storage vessel operated in the Pacific Northwest National Laboratory (PNNL) Applied Process Engineering Laboratory using a kaolin/bentonite clay and AZ-101 HLW chemical simulant with non-Newtonian rheological properties representative of actual waste slurries. Additional tests were performed in a small-scale mixing vessel in the PNNL Physical Sciences Building using liquids and slurries representing major components of typical WTP waste streams. Analytical studies were directed at discovering how the effect of AFA might depend on gas composition and predicting the effect of AFA on gas retention and release in the full-scale plant, including the effects of mass transfer to the sparge air. The work at PNNL was part of a larger program that included tests conducted at Savannah River National Laboratory (SRNL) that is being reported separately. SRNL conducted gas holdup tests in a small-scale mixing vessel using the AZ-101 high-level waste (HLW) chemical simulant to investigate the effects of different AFAs, their components, and of adding noble metals. Full-scale, single-sparger mass transfer tests were also conducted at SRNL in water and AZ-101 HLW simulant to provide data for PNNL’s WTP gas retention and release modeling

Na+ imaging reveals little difference in action potential–evoked Na+ influx between axon and soma

Author Posting. © The Authors, 2010. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Neuroscience 13 (2010): 852-860, doi:10.1038/nn.2574.In cortical pyramidal neurons, the axon initial segment (AIS) plays a pivotal role in synaptic integration. It has been asserted that this property reflects a high density of Na+ channels in AIS. However, we here report that AP–associated Na+ flux, as measured by high–speed fluorescence Na+ imaging, is about 3 times larger in the rat AIS than in the soma. Spike evoked Na+ flux in the AIS and the first node of Ranvier is about the same, and in the basal dendrites it is about 8 times lower. At near threshold voltages persistent Na+ conductance is almost entirely axonal. Finally, we report that on a time scale of seconds, passive diffusion and not pumping is responsible for maintaining transmembrane Na+ gradients in thin axons during high frequency AP firing. In computer simulations, these data were consistent with the known features of AP generation in these neurons.Supported by US– Israel BSF Grant (2003082), Grass Faculty Grant from the MBL, NIH Grant (NS16295), Multiple Sclerosis Society Grant (PP1367), and a fellowship from the Gruss Lipper Foundation

Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer’s Disease: Results from the DIAN Study Group

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer’s Network (DIAN), an autosomal dominant Alzheimer’s disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer’s disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted

Modeling autosomal dominant Alzheimer's disease with machine learning

INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease. METHODS: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status. RESULTS: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2  = 0.95), fluorodeoxyglucose (R2  = 0.93), and atrophy (R2  = 0.95) in mutation carriers compared to non-carriers. DISCUSSION: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions