Long-range temporal correlations in scale-free neuromorphic networks

© 2020 Massachusetts Institute of Technology. Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing

Atomic Scale Dynamics Drive Brain-like Avalanches in Percolating Nanostructured Networks.

Self-assembled networks of nanoparticles and nanowires have recently emerged as promising systems for brain-like computation. Here, we focus on percolating networks of nanoparticles which exhibit brain-like dynamics. We use a combination of experiments and simulations to show that the brain-like network dynamics emerge from atomic-scale switching dynamics inside tunnel gaps that are distributed throughout the network. The atomic-scale dynamics emulate leaky integrate and fire (LIF) mechanisms in biological neurons, leading to the generation of critical avalanches of signals. These avalanches are quantitatively the same as those observed in cortical tissue and are signatures of the correlations that are required for computation. We show that the avalanches are associated with dynamical restructuring of the networks which self-tune to balanced states consistent with self-organized criticality. Our simulations allow visualization of the network states and detailed mechanisms of signal propagation

Molecular basis for the folding of β-helical autotransporter passenger domains

Bacterial autotransporters comprise a C-terminal β-barrel domain, which must be correctly folded and inserted into the outer membrane to facilitate translocation of the N-terminal passenger domain to the cell exterior. Once at the surface, the passenger domains of most autotransporters are folded into an elongated β-helix. In a cellular context, key molecules catalyze the assembly of the autotransporter β-barrel domain. However, how the passenger domain folds into its functional form is poorly understood. Here we use mutational analysis on the autotransporter Pet to show that the β-hairpin structure of the fifth extracellular loop of the β-barrel domain has a crucial role for passenger domain folding into a β-helix. Bioinformatics and structural analyses, and mutagenesis of a homologous autotransporter, suggest that this function is conserved among autotransporter proteins with β-helical passenger domains. We propose that the autotransporter β-barrel domain is a folding vector that nucleates folding of the passenger domain

Characterisation of proteins in excretory/secretory products collected from salmon lice, Lepeophtheirus salmonis

Background  The salmon louse, Lepeophtheirus salmonis, is an ectoparasitic copepod which feeds on the mucus, skin and blood of salmonid fish species. The parasite can persist on the surface of the fish without any effective control being exerted by the host immune system. Other ectoparasitic invertebrates produce compounds in their saliva, excretions and/or secretions which modulate the host immune responses allowing them to remain on or in the host during development. Similarly, compounds are produced in secretions of L. salmonis which are thought to be responsible for immunomodulation of the host responses as well as other aspects of crucial host-parasite interactions.  Methods  In this study we have identified and characterised the proteins in the excretory/secretory (E/S) products of L. salmonis using LC-ESI-MS/MS.  Results  In total 187 individual proteins were identified in the E/S collected from adult lice and pre-adult sea lice. Fifty-three proteins, including 13 serine-type endopeptidases, 1 peroxidase and 5 vitellogenin-like proteins were common to both adult and pre-adult E/S products. One hundred and seven proteins were identified in the adult E/S but not in the pre-adult E/S and these included serine and cysteine-type endopeptidases, vitellogenins, sphingomyelinase and calreticulin. A total of 27 proteins were identified in pre-adult E/S products but not in adult E/S.  Conclusions  The assigned functions of these E/S products and the potential roles they play in host-parasite interaction is discussed

Variational Methods for Biomolecular Modeling

Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrostatics and solvation that includes the curvature energy of the molecular surface, the formation of microdomains on lipid membrane due to the geometric and molecular mechanics at the lipid interface, and the mean curvature driven protein localization on membrane surfaces. By further implicitly representing the interface using a phase field function over the entire domain, one can simulate the dynamics of the interface and the corresponding energy variation by evolving the phase field function, achieving significant reduction of the number of degrees of freedom and computational complexity. Strategies for improving the efficiency of computational implementations and for extending applications to coarse-graining or multiscale molecular simulations are outlined.Comment: 36 page

Development and validation of high resolution melting assays for high-throughput screening of BDNF rs6265 and DAT1 rs40184

Introduction: One of the commonly used techniques for mutation screening is High Resolution Melting (HRM) analysis. HRM is a post PCR method that relies on the detection of the fluorescent signals acquired due to the release of DNA intercalated dyes upon the melting of dsDNA to ssDNA. The method is simple, inexpensive and does not require post PCR-handling, making it suitable for high throughput screening. Methods: This study aimed to develop and validate HRM technique for the screening of two disease-associated single nucleotide polymorphisms (SNPs) namely BDNF rs6265 and DAT1 rs40184 using a total of 30 gDNA samples. The obtained results were confirmed and validated by sequencing. Results: HRM analysis showed that the predicted genotypes of BDNF rs6265 and DAT1 rs40184 among all the gDNA samples were in 100% concordance with the sequencing results, making it an accurate and sensitive method for the detection of SNPs. Conclusions: The application of HRM can accurately determine the genotype of BDNF rs6265 and DAT1 rs40184 SNPs, making it a promising tool for rapid and high-throughput screening of targeted SNPs in a large population study

Active and passive smoking and the risk of breast cancer in women aged 36–45 years: a population based case–control study in the UK

Active smoking has little or no effect on breast cancer risk but some investigators have suggested that passive smoking and its interaction with active smoking may be associated with an increased risk. In a population based case–control study of breast cancer in women aged 36–45 years at diagnosis, information on active smoking, passive smoking in the home, and other factors, was collected at interview from 639 cases and 640 controls. Women were categorised jointly by their active and passive smoking exposure. Among never smoking controls, women who also reported no passive smoking exposure were significantly more likely to be nulliparous and to be recent users of oral contraceptives. Among those never exposed to passive smoking, there was no significant association between active smoking and breast cancer, relative risk (RR) of 1.12 (95% confidence interval (CI) 0.72–1.73) for past smokers and RR of 1.19 (95% CI 0.72–1.95) for current smokers, nor was there an association with age started, duration or intensity of active smoking. Compared with women who were never active nor passive smokers, there was no significant association between passive smoking in the home and breast cancer risk in never smokers, RR of 0.89 (95% CI 0.64–1.25), in past smokers, RR of 1.09 (95% CI 0.75–1.56), or in current smokers, RR of 0.93 (95% CI 0.67–1.30). There was no trend with increasing duration of passive smoking and there was no heterogeneity among any of the subgroups examined. In this study, there was no evidence of an association between either active smoking or passive smoking in the home and risk of breast cancer

Neuroimaging in Dementia

Dementia is a common illness with an incidence that is rising as the aged population increases. There are a number of neurodegenerative diseases that cause dementia, including Alzheimer’s disease, dementia with Lewy bodies, and frontotemporal dementia, which is subdivided into the behavioral variant, the semantic variant, and nonfluent variant. Numerous other neurodegenerative illnesses have an associated dementia, including corticobasal degeneration, Creutzfeldt–Jakob disease, Huntington’s disease, progressive supranuclear palsy, multiple system atrophy, Parkinson’s disease dementia, and amyotrophic lateral sclerosis. Vascular dementia and AIDS dementia are secondary dementias. Diagnostic criteria have relied on a constellation of symptoms, but the definite diagnosis remains a pathologic one. As treatments become available and target specific molecular abnormalities, differentiating amongst the various primary dementias early on becomes essential. The role of imaging in dementia has traditionally been directed at ruling out treatable and reversible etiologies and not to use imaging to better understand the pathophysiology of the different dementias. Different brain imaging techniques allow the examination of the structure, biochemistry, metabolic state, and functional capacity of the brain. All of the major neurodegenerative disorders have relatively specific imaging findings that can be identified. New imaging techniques carry the hope of revolutionizing the diagnosis of neurodegenerative disease so as to obtain a complete molecular, structural, and metabolic characterization, which could be used to improve diagnosis and to stage each patient and follow disease progression and response to treatment. Structural and functional imaging modalities contribute to the diagnosis and understanding of the different dementias

Reproductive factors and breast cancer risk according to joint estrogen and progesterone receptor status: a meta-analysis of epidemiological studies

INTRODUCTION: Although reproductive factors have been known for decades to be associated with breast cancer risk, it is unclear to what extent these associations differ by estrogen and progesterone receptor (ER/PR) status. This report presents the first meta-analysis of results from epidemiological studies that have investigated parity, age at first birth, breastfeeding, and age at menarche in relation to ER(+)PR(+ )and ER(-)PR(- )cancer risk. MATERIALS AND METHODS: We calculated summary relative risks (RRs) and corresponding 95% confidence intervals (CIs) using a fixed effects model. RESULTS: Each birth reduced the risk of ER(+)PR(+ )cancer by 11% (RR per birth = 0.89, 95% CI = 0.84–0.94), and women who were in the highest age at first birth category had, on average, 27% higher risk of ER(+)PR(+ )cancer compared with women who were in the youngest age at first birth category (RR = 1.27, 95% CI = 1.07–1.50). Neither parity nor age at first birth was associated with the risk of ER(-)PR(- )cancer (RR per birth = 0.99, 95% CI = 0.94–1.05; RR of oldest versus youngest age at first birth category = 1.01, 95% CI = 0.85–1.20). Breastfeeding and late age at menarche decreased the risk of both receptor subtypes of breast cancer. The protective effect of late age at menarche was statistically significantly greater for ER(+)PR(+ )than ER(-)PR(- )cancer (RR = 0.72 for ER(+)PR(+ )cancer; RR = 0.84 for ER(-)PR(- )cancer, p for homogeneity = 0.006). CONCLUSION: Our findings suggest that breastfeeding (and age at menarche) may act through different hormonal mechanisms than do parity and age at first birth