Brain imaging in dementia

The introduction of MRI and positron emission tomography (PET) brain imaging has contributed significantly to the understanding of different dementia syndromes. Over the past 20 years these imaging techniques have been increasingly used for clinical characterisation and differential diagnosis, and to provide insight into the effects on functional capacity of the brain, patterns of spatial distribution of different dementia syndromes and their natural history and evolution over time. Brain imaging is also increasingly used in clinical trials, as part of inclusion criteria and/or as a surrogate outcome measure. Here we review all the relatively specific findings that can be identified with different MRI and PET techniques in each of the most frequent dementing disorders

ToPoliNano: Nanoarchitectures Design Made Real

Many facts about emerging nanotechnologies are yet to be assessed. There are still major concerns, for instance, about maximum achievable device density, or about which architecture is best fit for a specific application. Growing complexity requires taking into account many aspects of technology, application and architecture at the same time. Researchers face problems that are not new per se, but are now subject to very different constraints, that need to be captured by design tools. Among the emerging nanotechnologies, two-dimensional nanowire based arrays represent promising nanostructures, especially for massively parallel computing architectures. Few attempts have been done, aimed at giving the possibility to explore architectural solutions, deriving information from extensive and reliable nanoarray characterization. Moreover, in the nanotechnology arena there is still not a clear winner, so it is important to be able to target different technologies, not to miss the next big thing. We present a tool, ToPoliNano, that enables such a multi-technological characterization in terms of logic behavior, power and timing performance, area and layout constraints, on the basis of specific technological and topological descriptions. This tool can aid the design process, beside providing a comprehensive simulation framework for DC and timing simulations, and detailed power analysis. Design and simulation results will be shown for nanoarray-based circuits. ToPoliNano is the first real design tool that tackles the top down design of a circuit based on emerging technologie

Integration of Simulated Quantum Annealing in Parallel Tempering and Population Annealing for Heterogeneous-Profile QUBO Exploration

Simulated Quantum Annealing (SQA) is a heuristic algorithm which can solve Quadratic Unconstrained Binary Optimization (QUBO) problems by emulating the exploration of the solution space done by a quantum annealer. It mimics the quantum superposition and tunnelling effects through a set of correlated replicas of the spins system representing the problem to be solved and performing Monte Carlo steps. However, the effectiveness of SQA over a classical algorithm strictly depends on the cost/energy profile of the target problem. In fact, quantum annealing only performs well in exploring functions with high and narrow peaks, while classical annealing is better in overcoming flat and wide energy-profile barriers. Unfortunately, real-world problems have a heterogeneous solution space and the probability of success of each solver depends on the size of the energy profile region compatible with its exploration mechanism. Therefore, significant advantages could be obtained by exploiting hybrid solvers, which combine SQA and classical algorithms. This work proposes four new quantum-classical algorithms: Simulated Quantum Parallel Tempering (SQPT), Simulated Quantum Population Annealing (SQPA), Simulated Quantum Parallel Tempering - Population Annealing v1 (SQPTPA1) and Simulated Quantum Parallel Tempering - Population Annealing v2 (SQPTPA2). They are obtained by combining SQA, Parallel Tempering (PT), and Population Annealing (PA). Their results are compared with those provided by SQA, considering benchmark QUBO problems, characterized by different profiles. Even though this work is preliminary, the obtained results are encouraging and prove hybrid solvers’ potential in solving a generic optimization problem

Towards Compact Modeling of Noisy Quantum Computers: A Molecular-Spin-Qubit Case of Study

Classical simulation of Noisy Intermediate Scale Quantum computers is a crucial task for testing the expected performance of real hardware. The standard approach, based on solving Schrödinger and Lindblad equations, is demanding when scaling the number of qubits in terms of both execution time and memory. In this article, attempts in defining compact models for the simulation of quantum hardware are proposed, ensuring results close to those obtained with standard formalism. Molecular Nuclear Magnetic Resonance quantum hardware is the target technology, where three non-ideality phenomena—common to other quantum technologies—are taken into account: decoherence, off-resonance qubit evolution, and undesired qubit-qubit residual interaction. A model for each non-ideality phenomenon is embedded into a MATLAB simulation infrastructure of noisy quantum computers. The accuracy of the models is tested on a benchmark of quantum circuits, in the expected operating ranges of quantum hardware. The corresponding outcomes are compared with those obtained via numeric integration of the Schrödinger equation and the Qiskit’s QASMSimulator. The achieved results give evidence that this work is a step forward towards the definition of compact models able to provide fast results close to those obtained with the traditional physical simulation strategies, thus paving the way for their integration into a classical simulator of quantum computers

The neural bases for devaluing radical political statements revealed by penetrating traumatic brain injury

Given the determinant role of ventromedial prefrontal cortex (vmPFC) in valuation, we examined whether vmPFC lesions also modulate how people scale political beliefs. Patients with penetrating traumatic brain injury (pTBI; N1/4102) and healthy controls (HCs; N1/431) were tested on the political belief task, where they rated 75 statements expressing political opinions concerned with welfare, economy, political involvement, civil rights, war and security. Each statement was rated for level of agreement and scaled along three dimensions: radicalism, individualism and conservatism. Voxel-based lesionsymptom mapping (VLSM) analysis showed that diminished scores for the radicalism dimension (i.e. statements were rated as less radical than the norms) were associated with lesions in bilateral vmPFC. After dividing the pTBI patients into three groups, according to lesion location (i.e. vmPFC, dorsolateral prefrontal cortex [dlPFC] and parietal cortex), we found that the vmPFC, but not the dlPFC, group had reduced radicalism scores compared with parietal and HC groups. These findings highlight the crucial role of the vmPFC in appropriately valuing political behaviors and may explain certain inappropriate social judgments observed in patients with vmPFC lesions

Virtual Clocking for NanoMagnet Logic

Among emerging technologies nanomagnet logic (NML) has recently received particular attention. NML uses magnets as constitutive elements, and this leads to logic circuits where there is no need of an external power supply to maintain their logic state. As a consequence, a system with intrinsic memory and zero stand-by power consumption can be envisioned. Despite the interesting nature of NML, a fundamental open problem still calls for a solution that could really boost the NML technology: the clock system. It constrains the layout of circuits and leads to a potentially high dynamic power consumption if not carefully conceived. The first clock system developed was based on the generation of a magnetic field through an on-chip current. After that other types of NML, based on several different types of clock systems, were proposed to improve clocking. We present here our proposal for a new clock delivery method. We named this system “virtual clock.” It offers several important advantages over previous solutions. First, it notably simplifies the clock generation network, reducing the complexity of the fabrication process. It improves the efficiency of circuits layout, substantially reducing interconnections overhead and boosting the reliability of the majority voter. It enables the fabrication of in-plane NML circuits with two layers, while they were confined to one single layer up to now. Finally, it allows to globally reduce dynamic power consumption by considerably shrinking circuits area. Overall the “virtual clock” system that we propose represents an important step forward in the development of the NML technology

Octantis: An Exploration Tool for Beyond von Neumann architectures

Nowadays, the modern electronic systems are facing an important limitation in terms of performance, known as von Neumann bottleneck. It affects the communications between two crucial elements, the CPU and the memory, which suffer from a saturation in bandwidth. Many solutions are currently under investigation and among them the concept of Logic-in-Memory (LiM) has been introduced: a memory enriched in its array of computational elements which enable the implementation of a flexible distributed processing system. The current work introduces Octantis, a High-Level Synthesizer useful for the exploration of LiM architectures. The proposed software analyzes an input algorithm described in standard C language and identifies which LiM architecture would implement it better. At its output, the synthesized solution is provided together with a test-bench, to properly characterize it, in terms of performance, spatial occupation and power consumption. Many algorithms have been successfully synthesized by Octantis and some of the results achieved will be discussed along the document

Determinants of Caregiver Burden in Early-Onset Dementia

Caregivers of patients with early-onset dementia (EOD) experience high levels of burden, which is known to be affected by caregivers’ psychological features as well as by patients’ and caregivers’ demographical and social variables. Although potential clinical, demographical, and social determinants have been separately examined, it is not known how they reciprocally interact. Methods: Ninety- two consecutive patient-caregiver dyads were recruited from the Cognitive Neurology Clinics of Modena, Northern Italy. Caregivers were asked to fill in questionnaires regarding their burden, psychological distress, and family economic status. Data were analyzed with multivariable regression models and then entered in a mediation model. Results: Caregiver burden was positively related to female caregiver sex, spousal relationship to the patient, severity of patient’s behavioral symptoms, diagnostic delay, and financial distress of the family. It was negatively related to disease duration, patient’s education, region of birth, caregiver age, number of caregiver’s days off work, number of offspring, and caregiver perception of patient’s quality of life. While the effect of caregiver age, diagnostic delay, and of proxies of family or social network directly impacted on caregiver’s burden, the effect of patient’s disease duration, being a wife caregiver, financial distress, and number of caregiver’s days off work was entirely mediated by the level of caregiver psychological distress. Conclusions: Both direct actions (such as increasing social networks and shortening diagnostic delay) and indirect actions aimed at reducing psychological distress (such as increasing the number of caregiver’s days off work and financial support) should be planned to reduce caregiver’s burden

C6orf10 low-frequency and rare variants in italian multiple sclerosis patients

In light of the complex nature of multiple sclerosis (MS) and the recently estimated contribution of low-frequency variants into disease, decoding its genetic risk components requires novel variant prioritization strategies. We selected, by reviewing MS Genome Wide Association Studies (GWAS), 107 candidate loci marked by intragenic single nucleotide polymorphisms (SNPs) with a remarkable association (p-value <= 5 x 10(-6)). A whole exome sequencing (WES)-based pilot study of SNPs with minor allele frequency (MAF) <= 0.04, conducted in three Italian families, revealed 15 exonic low-frequency SNPs with affected parent-child transmission. These variants were detected in 65/120 Italian unrelated MS patients, also in combination (22 patients). Compared with databases (controls gnomAD, dbSNP150, ExAC, Tuscany-1000 Genome), the allelic frequencies of C6orf10 rs 16870005 and IL2RA rs12722600 were significantly higher (i.e., controls gnomAD, p = 9.89 x 10(-7) and p < 1 x 10(-20)). TET2 rs61744960 and TRAF3 rs138943371 frequencies were also significantly higher, except in Tuscany-1000 Genome. Interestingly, the association of C6orf10 rs16870005 (Ala431Thr) with MS did not depend on its linkage disequilibrium with the HLA-DRB1 locus. Sequencing in the MS cohort of the C6orf10 3' region revealed 14 rare mutations (10 not previously reported). Four variants were null, and significantly more frequent than in the databases. Further, the C6orf10 rare variants were observed in combinations, both intra-locus and with other low-frequency SNPs. The C6orf10 Ser389Xfr was found homozygous in a patient with early onset of the MS. Taking into account the potentially functional impact of the identified exonic variants, their expression in combination at the protein level could provide functional insights in the heterogeneous pathogenetic mechanisms contributing to MS.In light of the complex nature of multiple sclerosis (MS) and the recently estimated contribution of low-frequency variants into disease, decoding its genetic risk components requires novel variant prioritization strategies. We selected, by reviewing MS Genome Wide Association Studies (GWAS), 107 candidate loci marked by intragenic single nucleotide polymorphisms (SNPs) with a remarkable association (p-value ≤ 5 × 10−6). A whole exome sequencing (WES)-based pilot study of SNPs with minor allele frequency (MAF) ≤ 0.04, conducted in three Italian families, revealed 15 exonic low-frequency SNPs with affected parent-child transmission. These variants were detected in 65/120 Italian unrelated MS patients, also in combination (22 patients). Compared with databases (controls gnomAD, dbSNP150, ExAC, Tuscany-1000 Genome), the allelic frequencies of C6orf10 rs16870005 and IL2RA rs12722600 were significantly higher (i.e., controls gnomAD, p = 9.89 × 10−7 and p < 1 × 10−20). TET2 rs61744960 and TRAF3 rs138943371 frequencies were also significantly higher, except in Tuscany-1000 Genome. Interestingly, the association of C6orf10 rs16870005 (Ala431Thr) with MS did not depend on its linkage disequilibrium with the HLA-DRB1 locus. Sequencing in the MS cohort of the C6orf10 3′ region revealed 14 rare mutations (10 not previously reported). Four variants were null, and significantly more frequent than in the databases. Further, the C6orf10 rare variants were observed in combinations, both intra-locus and with other low-frequency SNPs. The C6orf10 Ser389Xfr was found homozygous in a patient with early onset of the MS. Taking into account the potentially functional impact of the identified exonic variants, their expression in combination at the protein level could provide functional insights in the heterogeneous pathogenetic mechanisms contributing to MS