Solving a Higgs optimization problem with quantum annealing for machine learning

The discovery of Higgs-boson decays in a background of standard-model processes was assisted by machine learning methods. The classifiers used to separate signals such as these from background are trained using highly unerring but not completely perfect simulations of the physical processes involved, often resulting in incorrect labelling of background processes or signals (label noise) and systematic errors. Here we use quantum and classical annealing (probabilistic techniques for approximating the global maximum or minimum of a given function) to solve a Higgs-signal-versus-background machine learning optimization problem, mapped to a problem of finding the ground state of a corresponding Ising spin model. We build a set of weak classifiers based on the kinematic observables of the Higgs decay photons, which we then use to construct a strong classifier. This strong classifier is highly resilient against overtraining and against errors in the correlations of the physical observables in the training data. We show that the resulting quantum and classical annealing-based classifier systems perform comparably to the state-of-the-art machine learning methods that are currently used in particle physics. However, in contrast to these methods, the annealing-based classifiers are simple functions of directly interpretable experimental parameters with clear physical meaning. The annealer-trained classifiers use the excited states in the vicinity of the ground state and demonstrate some advantage over traditional machine learning methods for small training datasets. Given the relative simplicity of the algorithm and its robustness to error, this technique may find application in other areas of experimental particle physics, such as real-time decision making in event-selection problems and classification in neutrino physics

Integrated genome and transcriptome sequencing identifies a noncoding mutation in the genome replication factor DONSON as the cause of microcephaly-micromelia syndrome

While next-generation sequencing has accelerated the discovery of human disease genes, progress has been largely limited to the "low hanging fruit" of mutations with obvious exonic coding or canonical splice site impact. In contrast, the lack of high-throughput, unbiased approaches for functional assessment of most noncoding variants has bottlenecked gene discovery. We report the integration of transcriptome sequencing (RNA-seq), which surveys all mRNAs to reveal functional impacts of variants at the transcription level, into the gene discovery framework for a unique human disease, microcephaly-micromelia syndrome (MMS). MMS is an autosomal recessive condition described thus far in only a single First Nations population and causes intrauterine growth restriction, severe microcephaly, craniofacial anomalies, skeletal dysplasia, and neonatal lethality. Linkage analysis of affected families, including a very large pedigree, identified a single locus on Chromosome 21 linked to the disease (LOD > 9). Comprehensive genome sequencing did not reveal any pathogenic coding or canonical splicing mutations within the linkage region but identified several nonconserved noncoding variants. RNA-seq analysis detected aberrant splicing in DONSON due to one of these noncoding variants, showing a causative role for DONSON disruption in MMS. We show that DONSON is expressed in progenitor cells of embryonic human brain and other proliferating tissues, is co-expressed with components of the DNA replication machinery, and that Donson is essential for early embryonic development in mice as well, suggesting an essential conserved role for DONSON in the cell cycle. Our results demonstrate the utility of integrating transcriptomics into the study of human genetic disease when DNA sequencing alone is not sufficient to reveal the underlying pathogenic mutation

The Farm, the city, and the emergence of social security

We study the social, demographic and economic origins of social security. The data for the U.S. and for a cross section of countries suggest that urbanization and industrialization are associated with the rise of social insurance. We describe an OLG model in which demographics, technology, and social security are linked together in a political economy equilibrium. In the model economy, there are two locations (sectors), the farm (agricultural) and the city (industrial) and the decision to migrate from rural to urban locations is endogenous and linked to productivity differences between the two locations and survival probabilities. Farmers rely on land inheritance for their old age and do not support a pay-as-you-go social security system. With structural change, people migrate to the city, the land loses its importance and support for social security arises. We show that a calibrated version of this economy, where social security taxes are determined by majority voting, is consistent with the historical transformation in the United States

Immigrant women’s experiences of maternity-care services in Canada: a systematic review using a narrative synthesis

Background: Canada’s diverse society and its statutory commitment to multiculturalism means that a synthesis of knowledge related to the healthcare experiences of immigrants is essential to realise the health potential for future Canadians. Although concerns about the maternity experiences of immigrants in Canada are relatively new, recent national guidelines explicitly call for the tailoring of services to user needs. We therefore assessed the experiences of immigrant women accessing maternity-care services in Canada. In particular, we investigated the experiences of immigrant women in Canada in accessing and navigating maternity and related healthcare services from conception to 6 months postpartum in Canada. Our focus was on (a) the accessibility and acceptability of maternity-care services for immigrant women and (b) the effects of the perceptions and experiences of these women on their birth and postnatal outcomes. Methods: We conducted a systematic review using a systematic search and narrative synthesis of peer-reviewed and non-peer-reviewed reports of empirical research, with the aim of providing stakeholders with perspectives on maternity-care services as experienced by immigrant women. We partnered with key stakeholders (‘integrated knowledge users’) to ensure the relevancy of topics and to tailor recommendations for effective translation into future policy, practice and programming. Two search phases and a three-stage selection process for published and grey literature were conducted prior to appraisal of literature quality and narrative synthesis of the findings. Results: Our knowledge synthesis of maternity care among immigrants to Canada provided a coherent evidence base for (a) eliciting a better understanding of the factors that generate disparities in accessibility, acceptability and outcomes during maternity care; and (b) improving culturally based competency in maternity care. Our synthesis also identified pertinent issues in multiple sectors that should be addressed to configure maternity services and programs appropriately. Conclusions: Although immigrant women in Canada are generally given the opportunity to obtain necessary services, they face many barriers in accessing and utilising these services. These barriers include lack of information about or awareness of the services, insufficient supports to access these services and discordant expectations between the women and their service providers. Systematic review registration: PROSPERO registration number: CRD42012002185

Co-Expression of α9β1 Integrin and VEGF-D Confers Lymphatic Metastatic Ability to a Human Breast Cancer Cell Line MDA-MB-468LN

INTRODUCTION AND OBJECTIVES: Lymphatic metastasis is a common occurrence in human breast cancer, mechanisms remaining poorly understood. MDA-MB-468LN (468LN), a variant of the MDA-MB-468GFP (468GFP) human breast cancer cell line, produces extensive lymphatic metastasis in nude mice. 468LN cells differentially express α9β1 integrin, a receptor for lymphangiogenic factors VEGF-C/-D. We explored whether (1) differential production of VEGF-C/-D by 468LN cells provides an autocrine stimulus for cellular motility by interacting with α9β1 and a paracrine stimulus for lymphangiogenesis in vitro as measured with capillary-like tube formation by human lymphatic endothelial cells (HMVEC-dLy); (2) differential expression of α9 also promotes cellular motility/invasiveness by interacting with macrophage derived factors; (3) stable knock-down of VEGF-D or α9 in 468LN cells abrogates lymphangiogenesis and lymphatic metastasis in vivo in nude mice. RESULTS: A comparison of expression of cyclo-oxygenase (COX)-2 (a VEGF-C/-D inducer), VEGF-C/-D and their receptors revealed little COX-2 expression by either cells. However, 468LN cells showed differential VEGF-D and α9β1 expression, VEGF-D secretion, proliferative, migratory/invasive capacities, latter functions being stimulated further with VEGF-D. The requirement of α9β1 for native and VEGF-D-stimulated proliferation, migration and Erk activation was demonstrated by treating with α9β1 blocking antibody or knock-down of α9. An autocrine role of VEGF-D in migration was shown by its impairment by silencing VEGF-D and restoration with VEGF-D. 468LN cells and their soluble products stimulated tube formation, migration/invasiveness of HMVEC-dLy cell in a VEGF-D dependent manner as indicated by the loss of stimulation by silencing VEGF-D in 468LN cells. Furthermore, 468LN cells showed α9-dependent stimulation of migration/invasiveness by macrophage products. Finally, capacity for intra-tumoral lymphangiogenesis and lymphatic metastasis in nude mice was completely abrogated by stable knock-down of either VEGF-D or α9 in 468LN cells. CONCLUSION: Differential capacity for VEGF-D production and α9β1 integrin expression by 468LN cells jointly contributed to their lymphatic metastatic phenotype

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study

The IceCube Neutrino Observatory - Contributions to ICRC 2017 Part VI: IceCube-Gen2, the Next Generation Neutrino Observatory

Papers on research & development towards IceCube-Gen2, the next generation neutrino observatory at South Pole, submitted to the 35th International Cosmic Ray Conference (ICRC 2017, Busan, South Korea) by the IceCube-Gen2 Collaboration

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta