GMC Collisions as Triggers of Star Formation. I. Parameter Space Exploration with 2D Simulations

We utilize magnetohydrodynamic (MHD) simulations to develop a numerical model for GMC-GMC collisions between nearly magnetically critical clouds. The goal is to determine if, and under what circumstances, cloud collisions can cause pre-existing magnetically subcritical clumps to become supercritical and undergo gravitational collapse. We first develop and implement new photodissociation region (PDR) based heating and cooling functions that span the atomic to molecular transition, creating a multiphase ISM and allowing modeling of non-equilibrium temperature structures. Then in 2D and with ideal MHD, we explore a wide parameter space of magnetic field strength, magnetic field geometry, collision velocity, and impact parameter, and compare isolated versus colliding clouds. We find factors of ~2-3 increase in mean clump density from typical collisions, with strong dependence on collision velocity and magnetic field strength, but ultimately limited by flux-freezing in 2D geometries. For geometries enabling flow along magnetic field lines, greater degrees of collapse are seen. We discuss observational diagnostics of cloud collisions, focussing on 13CO(J=2-1), 13CO(J=3-2), and 12CO(J=8-7) integrated intensity maps and spectra, which we synthesize from our simulation outputs. We find the ratio of J=8-7 to lower-J emission is a powerful diagnostic probe of GMC collisions

Human induced pluripotent stem cells for modelling metabolic perturbations and impaired bioenergetics underlying cardiomyopathies

Normal cardiac contractile and relaxation function are critically dependent on a continuous energy supply. Accordingly, metabolic perturbations and impaired mitochondrial bioenergetics with subsequent disruption of ATP production underpin a wide variety of cardiac diseases, including diabetic cardiomyopathy, dilated cardiomyopathy, hypertrophic cardiomyopathy, anthracycline cardiomyopathy, peripartum cardiomyopathy, and mitochondrial cardiomyopathies. Crucially, there are no specific treatments for preventing the onset or progression of these cardiomyopathies to heart failure, one of the leading causes of death and disability worldwide. Therefore, new treatments are needed to target the metabolic disturbances and impaired mitochondrial bioenergetics underlying these cardiomyopathies in order to improve health outcomes in these patients. However, investigation of the underlying mechanisms and the identification of novel therapeutic targets have been hampered by the lack of appropriate animal disease models. Furthermore, interspecies variation precludes the use of animal models for studying certain disorders, whereas patient-derived primary cell lines have limited lifespan and availability. Fortunately, the discovery of human induced pluripotent stem cells (hiPSCs) has provided a promising tool for modelling cardiomyopathies via human heart tissue in a dish. In this review article, we highlight the use of patient-derived iPSCs for studying the pathogenesis underlying cardiomyopathies associated with metabolic perturbations and impaired mitochondrial bioenergetics, as the ability of iPSCs for self-renewal and differentiation makes them an ideal platform for investigating disease pathogenesis in a controlled in vitro environment. Continuing progress will help elucidate novel mechanistic pathways, and discover novel therapies for preventing the onset and progression of heart failure, thereby advancing a new era of personalised therapeutics for improving health outcomes in patients with cardiomyopathy

Rmi1 stimulates decatenation of double Holliday junctions during dissolution by Sgs1-Top3

double Holliday junction (dHJ) is a central intermediate of homologous recombination that can be processed to yield crossover or non-crossover recombination products. To preserve genomic integrity, cells possess mechanisms to avoid crossing over. We show that Saccharomyces cerevisiae Sgs1 and Top3 proteins are sufficient to migrate and disentangle a dHJ to produce exclusively non-crossover recombination products, in a reaction termed "dissolution." We show that Rmi1 stimulates dHJ dissolution at low Sgs1-Top3 protein concentrations, although it has no effect on the initial rate of Holliday junction (HJ) migration. Rmi1 serves to stimulate DNA decatenation, removing the last linkages between the repaired and template DNA molecules. Dissolution of a dHJ is a highly efficient and concerted alternative to nucleolytic resolution that prevents crossing over of chromosomes during recombinational DNA repair in mitotic cells and thereby contributes to genomic integrity

Parton Distributions for Event Generators

In this paper, conventional Global QCD analysis is generalized to produce parton distributions optimized for use with event generators at the LHC. This optimization is accomplished by combining the constraints due to existing hard-scattering experimental data with those from anticipated cross sections for key representative SM processes at LHC (by the best available theory) as joint input to the global analyses. The PDFs obtained in these new type of global analyses using matrix elements calculated in any given order will be best suited to work with event generators of that order, for predictions at the LHC. This is most useful for LO event generators at present. Results obtained from a few candidate PDF sets (labeled as CT09MCS, CT09MC1 and CT09MC2) for LO event generators produced in this way are compared with those from other approaches.Comment: 35 pages, 19 figures, and 4 table

High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry

published_or_final_versio

Speeding up Simplification of Polygonal Curves using Nested Approximations

We develop a multiresolution approach to the problem of polygonal curve approximation. We show theoretically and experimentally that, if the simplification algorithm A used between any two successive levels of resolution satisfies some conditions, the multiresolution algorithm MR will have a complexity lower than the complexity of A. In particular, we show that if A has a O(N2/K) complexity (the complexity of a reduced search dynamic solution approach), where N and K are respectively the initial and the final number of segments, the complexity of MR is in O(N).We experimentally compare the outcomes of MR with those of the optimal "full search" dynamic programming solution and of classical merge and split approaches. The experimental evaluations confirm the theoretical derivations and show that the proposed approach evaluated on 2D coastal maps either shows a lower complexity or provides polygonal approximations closer to the initial curves.Comment: 12 pages + figure

Parents’ experiences of health visiting for children with Down syndrome

© MA Healthcare Limited.Children with Down syndrome have an increased likelihoodof experiencing serious health conditions. Health visitors canhave an important role in monitoring and promoting healthand development for young children with Down syndrome.This study aimed to explore parents’ experiences of healthvisiting services for children with Down syndrome. Twentyfour parents of children with Down syndrome aged 0–5 yearscompleted a brief questionnaire about the number and natureof visits from health visitors in the previous 12 months andtheir support needs. Some parents commented that otherprofessionals met the needs of their child, whereas others saidthat they would like more advice and support from healthvisitors. A further exploration of broader health serviceprovision, including health visiting, for young children withDown syndrome is needed.Peer reviewedFinal Accepted Versio

Interstellar Plunging Waves: ALMA Resolves the Physical Structure of Nonstationary MHD Shocks

Magnetohydrodynamic (MHD) shocks are violent events that inject large amounts of energy in the interstellar medium dramatically modifying its physical properties and chemical composition. Indirect evidence for the presence of such shocks has been reported from the especial chemistry detected toward a variety of astrophysical shocked environments. However, the internal physical structure of these shocks remains unresolved since their expected spatial scales are too small to be measured with current instrumentation. Here we report the first detection of a fully spatially resolved, MHD shock toward the infrared dark cloud (IRDC) G034.77-00.55. The shock, probed by silicon monoxide (SiO) and observed with the Atacama Large Millimeter/submillimeter Array (ALMA), is associated with the collision between the dense molecular gas of the cloud and a molecular gas flow pushed toward the IRDC by the nearby supernova remnant (SNR) W44. The interaction is occurring on subparsec spatial scales thanks to the enhanced magnetic field of the SNR, making the dissipation region of the MHD shock large enough to be resolved with ALMA. Our observations suggest that molecular flow–flow collisions can be triggered by stellar feedback, inducing shocked molecular gas densities compatible with those required for massive star formation

Evaluating semi-supervision methods for medical image segmentation: applications in cardiac magnetic resonance imaging

PURPOSE: Purpose Neural networks have potential to automate medical image segmentation but require expensive labeling efforts. While methods have been proposed to reduce the labeling burden, most have not been thoroughly evaluated on large, clinical datasets or clinical tasks. We propose a method to train segmentation networks with limited labeled data and focus on thorough network evaluation. APPROACH: We propose a semi-supervised method that leverages data augmentation, consistency regularization, and pseudolabeling and train four cardiac magnetic resonance (MR) segmentation networks. We evaluate the models on multiinstitutional, multiscanner, multidisease cardiac MR datasets using five cardiac functional biomarkers, which are compared to an expert’s measurements using Lin’s concordance correlation coefficient (CCC), the within-subject coefficient of variation (CV), and the Dice coefficient. RESULTS: The semi-supervised networks achieve strong agreement using Lin’s CCC (>0.8), CV similar to an expert, and strong generalization performance. We compare the error modes of the semi-supervised networks against fully supervised networks. We evaluate semi-supervised model performance as a function of labeled training data and with different types of model supervision, showing that a model trained with 100 labeled image slices can achieve a Dice coefficient within 1.10% of a network trained with 16,000+ labeled image slices. CONCLUSION: We evaluate semi-supervision for medical image segmentation using heterogeneous datasets and clinical metrics. As methods for training models with little labeled data become more common, knowledge about how they perform on clinical tasks, how they fail, and how they perform with different amounts of labeled data is useful to model developers and users