Striatal Hypodensities, Not White Matter Hypodensities on CT, Are Associated with Late-Onset Depression in Alzheimer's Disease

This study examined whether there were neuroanatomical differences evident on CT scans of individuals with dementia who differed on depression history. Neuroanatomical variables consisted of visual ratings of frontal lobe deep white matter, subcortical white matter, and subcortical gray matter hypodensities in the CT scans of 182 individuals from the Study of Dementia in Swedish Twins who were diagnosed with dementia and had information on depression history. Compared to individuals with Alzheimer's disease and no depression, individuals with Alzheimer's disease and late-onset depression (first depressive episode at age 60 or over) had a greater number of striatal hypodensities (gray matter hypodensities in the caudate nucleus and lentiform nucleus). There were no significant differences in frontal lobe deep white matter or subcortical white matter. These findings suggest that late-onset depression may be a process that is distinct from the neurodegenerative changes caused by Alzheimer's disease

The East Asian Journal of British History, vol. 4

The East Asian Journal of British History is produced by the East Asian Society of British History, and supported by the Institute for Historical Research. The Institute of Historical Research is pleased and proud to be supporting this recent addition to British history scholarship. Developing out of the IHR’s long-standing collaborative partnership with Japanese universities, and now in its fourth year, the East Asian Journal of British History features some of the best emergent scholarship from Anglophone historians working in China, Japan, and South Korea. Divided between an articles section and one devoted to reviews, the journal’s remit wide-ranging covering all fields and periods of British history. It complements the triennial Anglo-Japanese Conference organised by the IHR and Japanese historians based at the universities of Tokyo, Kyoto and Osaka, and the conference of the East Asian Society of British history, in which we are joined by our colleagues from South Korea. In future, we hope that more contributions will be featured in the journal from the Chinese mainland and from Taiwan

'To live and die [for] Dixie': Irish civilians and the Confederate States of America

Around 20,000 Irishmen served in the Confederate army in the Civil War. As a result, they left behind, in various Southern towns and cities, large numbers of friends, family, and community leaders. As with native-born Confederates, Irish civilian support was crucial to Irish participation in the Confederate military effort. Also, Irish civilians served in various supporting roles: in factories and hospitals, on railroads and diplomatic missions, and as boosters for the cause. They also, however, suffered in bombardments, sieges, and the blockade. Usually poorer than their native neighbours, they could not afford to become 'refugees' and move away from the centres of conflict. This essay, based on research from manuscript collections, contemporary newspapers, British Consular records, and Federal military records, will examine the role of Irish civilians in the Confederacy, and assess the role this activity had on their integration into Southern communities. It will also look at Irish civilians in the defeat of the Confederacy, particularly when they came under Union occupation. Initial research shows that Irish civilians were not as upset as other whites in the South about Union victory. They welcomed a return to normalcy, and often 'collaborated' with Union authorities. Also, Irish desertion rates in the Confederate army were particularly high, and I will attempt to gauge whether Irish civilians played a role in this. All of the research in this paper will thus be put in the context of the Drew Gilpin Faust/Gary Gallagher debate on the influence of the Confederate homefront on military performance. By studying the Irish civilian experience one can assess how strong the Confederate national experiment was. Was it a nation without a nationalism

Author Correction: FAM222A encodes a protein which accumulates in plaques in Alzheimer’s disease (Nature Communications, (2020), 11, 1, (411), 10.1038/s41467-019-13962-0)

In the original version of the manuscript, the image shown in Figure 4g, bottom row (Aβ1–42 + rAggregatin), under “6h” was incorrect. This image incorrectly showed the same sample as shown in the original Figure 4g, top row (Aβ1–42), under “0.5h”. The correct version of figure 4g is as follows: (Figure presented.) which replaces the previous incorrect version: (Figure presented.)

Cascaded Multi-View Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer\u27s Disease via Fusion of Clinical, Imaging and Omic Features

The introduction of mild cognitive impairment (MCI) as a diagnostic category adds to the challenges of diagnosing Alzheimer\u27s Disease (AD). No single marker has been proven to accurately categorize patients into their respective diagnostic groups. Thus, previous studies have attempted to develop fused predictors of AD and MCI. These studies have two main limitations. Most do not simultaneously consider all diagnostic categories and provide suboptimal fused representations using the same set of modalities for prediction of all classes. In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic categories and optimizes classification by selectively combining a subset of modalities at each level of the cascade. CaMCCo is evaluated on a data cohort comprising 149 patients for whom neurophysiological, neuroimaging, proteomic and genomic data were available. Results suggest that fusion of select modalities for each classification task outperforms (mean AUC = 0.92) fusion of all modalities (mean AUC = 0.54) and individual modalities (mean AUC = 0.90, 0.53, 0.71, 0.73, 0.62, 0.68). In addition, CaMCCo outperforms all other multi-class classification methods for MCI prediction (PPV: 0.80 vs. 0.67, 0.63)

Transcriptome Analysis of Synaptoneurosomes Identifies Neuroplasticity Genes Overexpressed in Incipient Alzheimer's Disease

In Alzheimer's disease (AD), early deficits in learning and memory are a consequence of synaptic modification induced by toxic beta-amyloid oligomers (oAβ). To identify immediate molecular targets downstream of oAβ binding, we prepared synaptoneurosomes from prefrontal cortex of control and incipient AD (IAD) patients, and isolated mRNAs for comparison of gene expression. This novel approach concentrates synaptic mRNA, thereby increasing the ratio of synaptic to somal mRNA and allowing discrimination of expression changes in synaptically localized genes. In IAD patients, global measures of cognition declined with increasing levels of dimeric Aβ (dAβ). These patients also showed increased expression of neuroplasticity related genes, many encoding 3′UTR consensus sequences that regulate translation in the synapse. An increase in mRNA encoding the GluR2 subunit of the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) was paralleled by elevated expression of the corresponding protein in IAD. These results imply a functional impact on synaptic transmission as GluR2, if inserted, maintains the receptors in a low conductance state. Some overexpressed genes may induce early deficits in cognition and others compensatory mechanisms, providing targets for intervention to moderate the response to dAβ

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature