A single gene defect causing claustrophobia

Claustrophobia, the well-known fear of being trapped in narrow/closed spaces, is often considered a conditioned response to traumatic experience. Surprisingly, we found that mutations affecting a single gene, encoding a stress-regulated neuronal protein, can cause claustrophobia. Gpm6a-deficient mice develop normally and lack obvious behavioral abnormalities. However, when mildly stressed by single-housing, these mice develop a striking claustrophobia-like phenotype, which is not inducible in wild-type controls, even by severe stress. The human GPM6A gene is located on chromosome 4q32-q34, a region linked to panic disorder. Sequence analysis of 115 claustrophobic and non-claustrophobic subjects identified nine variants in the noncoding region of the gene that are more frequent in affected individuals (P=0.028). One variant in the 3′untranslated region was linked to claustrophobia in two small pedigrees. This mutant mRNA is functional but cannot be silenced by neuronal miR124 derived itself from a stress-regulated transcript. We suggest that loosing dynamic regulation of neuronal GPM6A expression poses a genetic risk for claustrophobia

The inner fluctuations of the brain in presymptomatic frontotemporal dementia: the chronnectome fingerprint

© 2019 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD. In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort. We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted. Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.This work was supported in part by grants from the NIH (R01REB020407, P20GM103472), NSF grant 1539067 and the Well- come Trust grant (JBR 103838).info:eu-repo/semantics/publishedVersio

Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia

Introduction This study evaluates the clinical value of a deep learning–based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons. Methods Fifty-five patients—17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls—underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance. Results AI significantly improved diagnostic accuracy for AD (area under the curve −AI: 0.800, +AI: 0.926, p < 0.05), with increased correct diagnoses (p < 0.01) and reduced errors (p < 0.03). BCR and RR showed notable performance gains (BCR: p < 0.04; RR: p < 0.02). For the diagnosis FTD, overall consensus (p < 0.01), BCNR (p < 0.02), and BCR (p < 0.05) recorded significantly more correct diagnoses. Discussion AI-assisted volumetry improves diagnostic performance in differentiating AD and FTD, benefiting all reader groups, including BCNR. Highlights Artificial intelligence (AI)-supported brain volumetry significantly improved the diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), with notable performance gains across radiologists of varying expertise levels. The presented AI tool is readily clinically available and reduces brain volumetry processing time from 12 to 24 hours to under 5 minutes, with full integration into picture archiving and communication systems, streamlining the workflow and facilitating real-time clinical decision making. AI-supported rapid brain volumetry has the potential to improve early diagnosis and to improve patient management

Antirealism and the Roles of Truth

Geschiedenis van Antieke en Middeleeuwse Semantie

Quantitative and integrative proteome analysis of peripheral nerve myelin identifies novel myelin proteins and candidate neuropathy loci

Peripheral nerve myelin facilitates rapid impulse conduction and normal motor and sensory functions. Many aspects of myelin biogenesis, glia-axonal interactions, and nerve homeostasis are poorly understood at the molecular level. We therefore hypothesized that only a fraction of all relevant myelin proteins has been identified so far. Combining gel-based and gel-free proteomic approaches, we identified 545 proteins in purified mouse sciatic nerve myelin, including 36 previously known myelin constituents. By mass spectrometric quantification, the predominant P0, periaxin, and myelin basic protein constitute 21, 16, and 8% of the total myelin protein, respectively, suggesting that their relative abundance was previously misestimated due to technical limitations regarding protein separation and visualization. Focusing on tetraspan-transmembrane proteins, we validated novel myelin constituents using immuno-based methods. Bioinformatic comparison with mRNA-abundance profiles allowed the categorization in functional groups coregulated during myelin biogenesis and maturation. By differential myelin proteome analysis, we found that the abundance of septin 9, the protein affected in hereditary neuralgic amyotrophy, is strongly increased in a novel mouse model of demyelinating neuropathy caused by the loss of prion protein. Finally, the systematic comparison of our compendium with the positions of human disease loci allowed us to identify several candidate genes for hereditary demyelinating neuropathies. These results illustrate how the integration of unbiased proteome, transcriptome, and genome data can contribute to a molecular dissection of the biogenesis, cell biology, metabolism, and pathology of myelin

Ion beam sputter deposition of epitaxial Ag films on native oxide covered Si (100) substrates

Epitaxial Ag films were grown on native oxide covered Si(1 0 0) substrates by an ion beam sputter deposition process at elevated deposition temperatures. At RT, films were observed to be non-epitaxial but with preferred (1 1 1) orientation. However, elevated substrate temperatures and under highly energetic sputter deposition process assist the growth of Ag films, that exhibit an epitaxial relationship with the underlying Si(1 0 0) substrates. With increasing deposition temperature an increase in the crystalline quality was observed with a narrowing mosaic distribution of crystallites and a decrease in the fraction of 1st order twins. The lowest epitaxial growth temperature was observed to be as low as 100 °C