Dynamical simulation via quantum machine learning with provable generalization

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we develop a framework for using QML methods to simulate quantum dynamics on near-term quantum hardware. We use generalization bounds, which bound the error a machine learning model makes on unseen data, to rigorously analyze the training data requirements of an algorithm within this framework. This provides a guarantee that our algorithm is resource-efficient, both in terms of qubit and data requirements. Our numerics exhibit efficient scaling with problem size, and we simulate 20 times longer than Trotterization on IBMQ-Bogota.Comment: Main text: 5 pages & 3 Figures. Supplementary Information: 12 pages & 2 Figure

Out-of-distribution generalization for learning quantum dynamics

Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees for in-distribution generalization of quantum neural networks (QNNs), where training and testing data are assumed to be drawn from the same data distribution. However, there are currently no results on out-of-distribution generalization in QML, where we require a trained model to perform well even on data drawn from a distribution different from the training distribution. In this work, we prove out-of-distribution generalization for the task of learning an unknown unitary using a QNN and for a broad class of training and testing distributions. In particular, we show that one can learn the action of a unitary on entangled states using only product state training data. We numerically illustrate this by showing that the evolution of a Heisenberg spin chain can be learned using only product training states. Since product states can be prepared using only single-qubit gates, this advances the prospects of learning quantum dynamics using near term quantum computers and quantum experiments, and further opens up new methods for both the classical and quantum compilation of quantum circuits.Comment: 7 pages (main body) + 14 pages (references and appendix); 4+1 figure

Delayed Toxicity Associated with Soluble Anthrax Toxin Receptor Decoy-Ig Fusion Protein Treatment

Soluble receptor decoy inhibitors, including receptor-immunogloubulin (Ig) fusion proteins, have shown promise as candidate anthrax toxin therapeutics. These agents act by binding to the receptor-interaction site on the protective antigen (PA) toxin subunit, thereby blocking toxin binding to cell surface receptors. Here we have made the surprising observation that co-administration of receptor decoy-Ig fusion proteins significantly delayed, but did not protect, rats challenged with anthrax lethal toxin. The delayed toxicity was associated with the in vivo assembly of a long-lived complex comprised of anthrax lethal toxin and the receptor decoy-Ig inhibitor. Intoxication in this system presumably results from the slow dissociation of the toxin complex from the inhibitor following their prolonged circulation. We conclude that while receptor decoy-Ig proteins represent promising candidates for the early treatment of B. anthracis infection, they may not be suitable for therapeutic use at later stages when fatal levels of toxin have already accumulated in the bloodstream

Cationic polyamines inhibit anthrax lethal factor protease

BACKGROUND: Anthrax is a human disease that results from infection by the bacteria, Bacillus anthracis and has recently been used as a bioterrorist agent. Historically, this disease was associated with Bacillus spore exposure from wool or animal carcasses. While current vaccine approaches (targeted against the protective antigen) are effective for prophylaxis, multiple doses must be injected. Common antibiotics that block the germination process are effective but must be administered early in the infection cycle. In addition, new therapeutics are needed to specifically target the proteolytic activity of lethal factor (LF) associated with this bacterial infection. RESULTS: Using a fluorescence-based assay to identify and characterize inhibitors of anthrax lethal factor protease activity, we identified several chemically-distinct classes of inhibitory molecules including polyamines, aminoglycosides and cationic peptides. In these studies, spermine was demonstrated for the first time to inhibit anthrax LF with a K(i )value of 0.9 ± 0.09 μM (mean ± SEM; n = 3). Additional linear polyamines were also active as LF inhibitors with lower potencies. CONCLUSION: Based upon the studies reported herein, we chose linear polyamines related to spermine as potential lead optimization candidates and additional testing in cell-based models where cell penetration could be studied. During our screening process, we reproducibly demonstrated that the potencies of certain compounds, including neomycin but not neamine or spermine, were different depending upon the presence or absence of nucleic acids. Differential sensitivity to the presence/absence of nucleic acids may be an additional point to consider when comparing various classes of active compounds for lead optimization

Factors affecting the implementation of complex and evolving technologies: multiple case study of intensity-modulated radiation therapy (IMRT) in Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>Research regarding the decision to adopt and implement technological innovations in radiation oncology is lacking. This is particularly problematic since these technologies are often complex and rapidly evolving, requiring ongoing revisiting of decisions regarding which technologies are the most appropriate to support. Variations in adoption and implementation decisions for new radiation technologies across cancer centres can impact patients' access to appropriate and innovative forms of radiation therapy. This study examines the key steps in the process of adopting and implementing intensity modulated radiation therapy (IMRT) in publicly funded cancer centres and identifies facilitating or impeding factors.</p> <p>Methods</p> <p>A multiple case study design, utilizing document analysis and key informant interviews was employed. Four cancer centres in Ontario, Canada were selected and interviews were conducted with radiation oncologists, medical physicists, radiation therapists, and senior administrative leaders.</p> <p>Results</p> <p>Eighteen key informants were interviewed. Overall, three centres made fair to excellent progress in the implementation of IMRT, while one centre achieved only limited implementation as of 2009. Key factors that influenced the extent of IMRT implementation were categorized as: 1) leadership, 2) training, expertise and standardization, 3) collaboration, 4) resources, and 5) resistance to change.</p> <p>Conclusion</p> <p>A framework for the adoption and implementation of complex and evolving technologies is presented. It identifies the key factors that should be addressed by decision-makers at specific stages of the adoption/implementation process.</p

IsoBED: a tool for automatic calculation of biologically equivalent fractionation schedules in radiotherapy using IMRT with a simultaneous integrated boost (SIB) technique

<p>Abstract</p> <p>Background</p> <p>An advantage of the Intensity Modulated Radiotherapy (IMRT) technique is the feasibility to deliver different therapeutic dose levels to PTVs in a single treatment session using the Simultaneous Integrated Boost (SIB) technique. The paper aims to describe an automated tool to calculate the dose to be delivered with the SIB-IMRT technique in different anatomical regions that have the same Biological Equivalent Dose (BED), i.e. IsoBED, compared to the standard fractionation.</p> <p>Methods</p> <p>Based on the Linear Quadratic Model (LQM), we developed software that allows treatment schedules, biologically equivalent to standard fractionations, to be calculated. The main radiobiological parameters from literature are included in a database inside the software, which can be updated according to the clinical experience of each Institute. In particular, the BED to each target volume will be computed based on the alpha/beta ratio, total dose and the dose per fraction (generally 2 Gy for a standard fractionation). Then, after selecting the reference target, i.e. the PTV that controls the fractionation, a new total dose and dose per fraction providing the same isoBED will be calculated for each target volume.</p> <p>Results</p> <p>The IsoBED Software developed allows: 1) the calculation of new IsoBED treatment schedules derived from standard prescriptions and based on LQM, 2) the conversion of the dose-volume histograms (DVHs) for each Target and OAR to a nominal standard dose at 2Gy per fraction in order to be shown together with the DV-constraints from literature, based on the LQM and radiobiological parameters, and 3) the calculation of Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) curve versus the prescribed dose to the reference target.</p

Contextualizing students' alcohol use perceptions and practices within French culture: an analysis of gender and drinking among sport-science college students

Although research has examined alcohol consumption and sport in a variety of contexts, there is a paucity of research on gender and gender dynamics among French college students. The present study addresses this gap in the literature by examining alcohol use practices by men and women among a non-probability sample of French sport science students from five different universities in Northern France. We utilized both survey data (N = 534) and in-depth qualitative interviews (n = 16) to provide empirical and theoretical insight into a relatively ubiquitous health concern: the culture of intoxication. Qualitative data were based on students’ perceptions of their own alcohol use; analysis were framed by theoretical conceptions of gender. Survey results indicate gender differences in alcohol consumption wherein men reported a substantially higher frequency and quantity of alcohol use compared to their female peers. Qualitative findings confirm that male privilege and women’s concern for safety, masculine embodiment via alcohol use, gendering of alcohol type, and gender conformity pressures shape gender disparities in alcohol use behavior. Our findings also suggest that health education policy and educational programs focused on alcohol-related health risks need to be designed to take into account gender category and gender orientation

Rugged Single Domain Antibody Detection Elements for Bacillus anthracis Spores and Vegetative Cells

Significant efforts to develop both laboratory and field-based detection assays for an array of potential biological threats started well before the anthrax attacks of 2001 and have continued with renewed urgency following. While numerous assays and methods have been explored that are suitable for laboratory utilization, detection in the field is often complicated by requirements for functionality in austere environments, where limited cold-chain facilities exist. In an effort to overcome these assay limitations for Bacillus anthracis, one of the most recognizable threats, a series of single domain antibodies (sdAbs) were isolated from a phage display library prepared from immunized llamas. Characterization of target specificity, affinity, and thermal stability was conducted for six sdAb families isolated from rounds of selection against the bacterial spore. The protein target for all six sdAb families was determined to be the S-layer protein EA1, which is present in both vegetative cells and bacterial spores. All of the sdAbs examined exhibited a high degree of specificity for the target bacterium and its spore, with affinities in the nanomolar range, and the ability to refold into functional antigen-binding molecules following several rounds of thermal denaturation and refolding. This research demonstrates the capabilities of these sdAbs and their potential for integration into current and developing assays and biosensors