Guest Editors' Introduction

‘I shall have to speak of things, of which I cannot speak’, writes Samuel Beckett in The Unnameable, ‘but also, which is even more interesting, but also that I, which is if possible even more interesting, that I shall have to, I forget, no matter’. Listening to the voice of folly can be like this: an endless flow of inconsistencies, of contradictions, sayings and unsayings; a tantalising, mischievous mockery of speech –unable to go on, unable to end. And yet – as this volume shows – we are irresistibly drawn to folly, its promises, its whispers of ‘even more interesting’ things: of how we are split between conscious and unconscious, familiar and unfamiliar, same and other. For psychoanalysis, folly is not only a site of hidden truths; it is also, perhaps more importantly, a source of unconscious freedom, a momentary escape from our obsession with rules and order. According to Christopher Bollas, the unconscious self is like a fool, who ‘raises potentially endless questions about diverse and disparate issues’ and thereby provides us with a ‘separate sense’, which opens us to others and to our own creative potential. As Rachel Bowlby elegantly puts it, folly is a ‘soul-mole’, forever shovelling our secrets out into the light: ‘there’s no possible moment of release or resignation when the mole might stop vainly, interminably working away’. Folly’s subversive, creative soliloquies reveal to us a psychic ‘underground repertoire of secrets’; they challenge our established knowledge and invite us, as Bolwby shows, to endless, titillating games of ‘suppression and confession’. For Anne Duprat, this deep-seated playfulness explains folly’s close relation to fiction: what makes them so atone is their ‘capacity of creating alternative representations of the world — and thus of re-figuring the world depicted by reason or history – […] but also their paradoxical structure, and hence the instability of their speech acts, which deny, suspend, or do not seriously guarantee the truth of their statements’. (First paragraph

The heparin-binding domain of HB-EGF mediates localization to sites of cell-cell contact and prevents HB-EGF proteolytic release

Heparin-binding EGF-like growth factor (HB-EGF) is a ligand for EGF receptor (EGFR) and possesses the ability to signal in juxtacrine, autocrine and/or paracrine mode, with these alternatives being governed by the degree of proteolytic release of the ligand. Although the spatial range of diffusion of released HB-EGF is restricted by binding heparan-sulfate proteoglycans (HSPGs) in the extracellular matrix and/or cellular glycocalyx, ascertaining mechanisms governing non-released HB-EGF localization is also important for understanding its effects. We have employed a new method for independently tracking the localization of the extracellular EGF-like domain of HB-EGF and the cytoplasmic C-terminus. A striking observation was the absence of the HB-EGF transmembrane pro-form from the leading edge of COS-7 cells in a wound-closure assay; instead, this protein localized in regions of cell-cell contact. A battery of detailed experiments found that this localization derives from a trans interaction between extracellular HSPGs and the HB-EGF heparin-binding domain, and that disruption of this interaction leads to increased release of soluble ligand and a switch in cell phenotype from juxtacrine-induced growth inhibition to autocrine-induced proliferation. Our results indicate that extracellular HSPGs serve to sequester the transmembrane pro-form of HB-EGF at the point of cell-cell contact, and that this plays a role in governing the balance between juxtacrine versus autocrine and paracrine signaling.National Institute of Biomedical Imaging and Bioengineering (U.S.) (Grant EB003805)National Cancer Institute (U.S.) (Grant CA96504)Massachusetts Institute of Technology. Poitras Pre-Doctoral FellowshipNational Science Foundation (U.S.). Graduate Research Fellowship Progra

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)

Prevention of LPS-Induced Acute Lung Injury in Mice by Mesenchymal Stem Cells Overexpressing Angiopoietin 1

Using a mouse model of acute respiratory distress syndrome, Duncan Stewart and colleagues report that rescue with mesenchymal stem cells expressing human angiopoietin 1 can avert lung injury from lipopolysaccharide

Dietary responses to a multiple sclerosis diagnosis: a qualitative study

Background/objectives: Multiple sclerosis (MS) is an immune-mediated disease with no known cure and insufficient evidence to support a special therapeutic diet to alter symptom management or disease progression. Several studies have reported dietary changes made by people with MS, but there has been limited investigation into experiences surrounding diet in those recently diagnosed. This study explored responses to diet after a recent diagnosis of MS in people living in Western Australia. Subjects/methods: Eleven adults with MS (mean time since diagnosis 8 months) participated in semi-structured interviews focusing on responses to diet since MS diagnosis. Interviews were transcribed, coded and analysed using grounded theory principles. Results: Three theme responses emerged; (1) the perceived incompatibility of lack of/or generalised dietary advice with disease seriousness at the time of diagnosis; (2) extensive personal research and information seeking with difficulty judging credibility, and (3) self-experimentation with diet to either control MS symptoms or to cure MS. Conclusions: Given the seriousness of the disease, there is a perceived gap in dietary information provided at the time of diagnosis. Healthcare professionals should address concerns with alternative therapeutic diets advertised to treat or cure MS, and clearly convey the reasoning for the general healthy dietary recommendations. This would better align advice with the perceptions about the role of diet in MS, assist people with MS in need of information and minimise dietary self-experimentation. Future research should explore the importance of diet for those who have had MS for a longer period of time

Polymorphisms near TBX5 and GDF7 are associated with increased risk for Barrett's esophagus.

BACKGROUND & AIMS: Barrett's esophagus (BE) increases the risk of esophageal adenocarcinoma (EAC). We found the risk to be BE has been associated with single nucleotide polymorphisms (SNPs) on chromosome 6p21 (within the HLA region) and on 16q23, where the closest protein-coding gene is FOXF1. Subsequently, the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) identified risk loci for BE and esophageal adenocarcinoma near CRTC1 and BARX1, and within 100 kb of FOXP1. We aimed to identify further SNPs that increased BE risk and to validate previously reported associations. METHODS: We performed a genome-wide association study (GWAS) to identify variants associated with BE and further analyzed promising variants identified by BEACON by genotyping 10,158 patients with BE and 21,062 controls. RESULTS: We identified 2 SNPs not previously associated with BE: rs3072 (2p24.1; odds ratio [OR] = 1.14; 95% CI: 1.09-1.18; P = 1.8 × 10(-11)) and rs2701108 (12q24.21; OR = 0.90; 95% CI: 0.86-0.93; P = 7.5 × 10(-9)). The closest protein-coding genes were respectively GDF7 (rs3072), which encodes a ligand in the bone morphogenetic protein pathway, and TBX5 (rs2701108), which encodes a transcription factor that regulates esophageal and cardiac development. Our data also supported in BE cases 3 risk SNPs identified by BEACON (rs2687201, rs11789015, and rs10423674). Meta-analysis of all data identified another SNP associated with BE and esophageal adenocarcinoma: rs3784262, within ALDH1A2 (OR = 0.90; 95% CI: 0.87-0.93; P = 3.72 × 10(-9)). CONCLUSIONS: We identified 2 loci associated with risk of BE and provided data to support a further locus. The genes we found to be associated with risk for BE encode transcription factors involved in thoracic, diaphragmatic, and esophageal development or proteins involved in the inflammatory response

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

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