Digital Quantum Simulation of the Statistical Mechanics of a Frustrated Magnet

Many interesting problems in physics, chemistry, and computer science are equivalent to problems of interacting spins. However, most of these problems require computational resources that are out of reach by classical computers. A promising solution to overcome this challenge is to exploit the laws of quantum mechanics to perform simulation. Several "analog" quantum simulations of interacting spin systems have been realized experimentally. However, relying on adiabatic techniques, these simulations are limited to preparing ground states only. Here we report the first experimental results on a "digital" quantum simulation on thermal states; we simulated a three-spin frustrated magnet, a building block of spin ice, with an NMR quantum information processor, and we are able to explore the phase diagram of the system at any simulated temperature and external field. These results serve as a guide for identifying the challenges for performing quantum simulation on physical systems at finite temperatures, and pave the way towards large scale experimental simulations of open quantum systems in condensed matter physics and chemistry.Comment: 7 pages for the main text plus 6 pages for the supplementary material

Medical Conditions of Nursing Home Admissions

<p>Abstract</p> <p>Background</p> <p>As long-term nursing home care is likely to increase with the aging of the population, identifying chronic medical conditions is of particular interest. Although need factors have a strong impact on nursing home (NH) admission, the diseases causing these functional disabilities are lacking or unclear in the residents' file. We investigated the medical reason (primary diagnosis) of a nursing home admission with respect to the underlying disease.</p> <p>Methods</p> <p>This study is based on two independent, descriptive and comparative studies in Belgium and was conducted at two time points (1993 and 2005) to explore the evolution over twelve years. Data from the subjects were extracted from the resident's file; additional information was requested from the general practitioner, nursing home physician or the head nurse in a face-to-face interview. In 1993 we examined 1332 residents from 19 institutions, and in 2005 691 residents from 7 institutions. The diseases at the time of admission were mapped by means of the International Classification of Diseases - 9th edition (ICD-9). Longitudinal changes were assessed and compared by a chi-square test.</p> <p>Results</p> <p>The main chronic medical conditions associated with NH admission were dementia and stroke. Mental disorders represent 48% of all admissions, somatic disorders 43% and social/emotional problems 8%. Of the somatic disorders most frequently are mentioned diseases of the circulatory system (35%) [2/3 sequels of stroke and 1/5 heart failure], followed by diseases of the nervous system (15%) [mainly Parkinson's disease] and the musculoskeletal system (14%) [mainly osteoarthritis]. The most striking evolution from 1993 to 2005 consisted in complicated diabetes mellitus (from 4.3 to 11.4%; p < 0.0001) especially with amputations and blindness. Symptoms (functional limitations without specific disease) like dizziness, impaired vision and frailty are of relevance as an indicator of admission.</p> <p>Conclusion</p> <p>Diseases like stroke, diabetes and mobility problems are only important for institutionalisation if they cause functional disability. Diabetes related complications as cause of admission increased almost three-fold between 1993 and 2005.</p

History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron “sees” through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types

MicroRNA-mediated drug resistance in breast cancer

Chemoresistance is one of the major hurdles to overcome for the successful treatment of breast cancer. At present, there are several mechanisms proposed to explain drug resistance to chemotherapeutic agents, including decreased intracellular drug concentrations, mediated by drug transporters and metabolic enzymes; impaired cellular responses that affect cell cycle arrest, apoptosis, and DNA repair; the induction of signaling pathways that promote the progression of cancer cell populations; perturbations in DNA methylation and histone modifications; and alterations in the availability of drug targets. Both genetic and epigenetic theories have been put forward to explain the mechanisms of drug resistance. Recently, a small non-coding class of RNAs, known as microRNAs, has been identified as master regulators of key genes implicated in mechanisms of chemoresistance. This article reviews the role of microRNAs in regulating chemoresistance and highlights potential therapeutic targets for reversing miRNA-mediated drug resistance. In the future, microRNA-based treatments, in combination with traditional chemotherapy, may be a new strategy for the clinical management of drug-resistant breast cancers

Systems microscopy approaches to understand cancer cell migration and metastasis

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration