183 research outputs found

    Narratives of Young Women Athletes’ Experiences of Emotional Pain and Self-compassion

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    Self-compassion is an adaptive way of relating to the self kindly when experiencing personal failure and difficult life experiences. However, there is little research in the area of self-compassion and sport even though recent investigation shows it might act as a potential buffer to painful emotions for athletes. The purpose of this qualitative study was to explore and present narratives of six young women athletes (15-24 years) from a variety of sports, about their experiences of emotional pain associated with failure and the role of self-compassion. Each woman took part in two individual interviews, one of which involved reflexive photography. They were asked to reflect on a difficult experience with a personal percieved failure in sport, followed by discussions around the potential role of self-compassion in their experiences. The interviews, combined with reflexive photography, helped build a rich narrative organized around the following themes: (1) Broken bodies, wilted spirits, (2) Why couldn’t it have been someone else?, (3) I should have, I could have, I would have, (4) You are going to make me ugly over this and, (5) Fall down seven, stand up eight. Their narratives also suggested that self-compassion can potentially be beneficial for athletes if developed and learned properly. In addition, some women saw self-compassion as another tool athletes could use to help improve their mental game; something that might not be needed all the time, but could be very useful during specific situations. While self-compassion might buffer painful emotions experienced in sport, concerns were expressed that being too self-compassion may lead to mediocrity. Further research is needed on young women athletes' difficult emotional experiences in sport, and more specifically on the role that self-compassion plays as both a potential facilitator and barrier to emotional health and performance success in sport

    Attention mechanisms in the CHREST cognitive architecture

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    In this paper, we describe the attention mechanisms in CHREST, a computational architecture of human visual expertise. CHREST organises information acquired by direct experience from the world in the form of chunks. These chunks are searched for, and verified, by a unique set of heuristics, comprising the attention mechanism. We explain how the attention mechanism combines bottom-up and top-down heuristics from internal and external sources of information. We describe some experimental evidence demonstrating the correspondence of CHREST’s perceptual mechanisms with those of human subjects. Finally, we discuss how visual attention can play an important role in actions carried out by human experts in domains such as chess

    Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

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    We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10–7.67, Cox P = 2.63e−05) and PFS (HR = 3.72, 95% CI 2.06–6.73, Cox P = 1.38e−05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24–6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16–3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2–3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08–3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH.</p

    Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

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    We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10–7.67, Cox P = 2.63e−05) and PFS (HR = 3.72, 95% CI 2.06–6.73, Cox P = 1.38e−05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24–6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16–3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2–3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08–3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH.</p

    Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

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    A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

    Generation of human vascular smooth muscle subtypes provides insight into embryological origin-dependent disease susceptibility.

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    Heterogeneity of embryological origins is a hallmark of vascular smooth muscle cells (SMCs) and may influence the development of vascular disease. Differentiation of human pluripotent stem cells (hPSCs) into developmental origin-specific SMC subtypes remains elusive. Here we describe a chemically defined protocol in which hPSCs were initially induced to form neuroectoderm, lateral plate mesoderm or paraxial mesoderm. These intermediate populations were further differentiated toward SMCs (>80% MYH11(+) and ACTA2(+)), which displayed contractile ability in response to vasoconstrictors and invested perivascular regions in vivo. Derived SMC subtypes recapitulated the unique proliferative and secretory responses to cytokines previously documented in studies using aortic SMCs of distinct origins. Notably, this system predicted increased extracellular matrix degradation by SMCs derived from lateral plate mesoderm, which was confirmed using rat aortic SMCs from corresponding origins. This differentiation approach will have broad applications in modeling origin-dependent disease susceptibility and in developing bioengineered vascular grafts for regenerative medicine

    RAS and BRAF mutations in cell-free DNA are predictive for outcome of cetuximab monotherapy in patients with tissue-tested RAS wild-type advanced colorectal cancer

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    In metastatic colorectal cancer, RAS and BRAF mutations cause resistance to anti-EGFR therapies, such as cetuximab. Heterogeneity in RAS and BRAF mutations might explain nonresponse in a subset of patients receiving cetuximab. Analyzing mutations in plasma-derived circulating tumor DNA (ctDNA) could provide a more comprehensive overview of the mutational landscape as compared to analyses of primary and/or metastatic tumor tissue. Therefore

    Reproducible radiomics through automated machine learning validated on twelve clinical applications

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    Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study

    Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

    Get PDF
    We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10-7.67, Cox P = 2.63e-05) and PFS (HR = 3.72, 95% CI 2.06-6.73, Cox P = 1.38e-05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24-6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16-3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2-3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08-3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH

    Correlation of RET somatic mutations with clinicopathological features in sporadic medullary thyroid carcinomas

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    Screening of REarranged during Transfection (RET) gene mutations has been carried out in different series of sporadic medullary thyroid carcinomas (MTC). RET-positive tumours seem to be associated to a worse clinical outcome. However, the correlation between the type of RET mutation and the patients' clinicopathological data has not been evaluated yet
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