375 research outputs found

    Patch-level instance-group discrimination with pretext-invariant learning for colitis scoring

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    Inflammatory bowel disease (IBD), in particular ulcerative colitis (UC), is graded by endoscopists and this assessment is the basis for risk stratification and therapy monitoring. Presently, endoscopic characterisation is largely operator dependant leading to sometimes undesirable clinical outcomes for patients with IBD. We focus on the Mayo Endoscopic Scoring (MES) system which is widely used but requires the reliable identification of subtle changes in mucosal inflammation. Most existing deep learning classification methods cannot detect these fine-grained changes which make UC grading such a challenging task. In this work, we introduce a novel patch-level instance-group discrimination with pretext-invariant representation learning (PLD-PIRL) for self-supervised learning (SSL). Our experiments demonstrate both improved accuracy and robustness compared to the baseline supervised network and several state-of-the-art SSL methods. Compared to the baseline (ResNet50) supervised classification our proposed PLD-PIRL obtained an improvement of 4.75% on hold-out test data and 6.64% on unseen center test data for top-1 accuracy.Comment: 1

    Postpartum Prolapsed Leiomyoma with Uterine Inversion Managed by Vaginal Hysterectomy

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    Background. Uterine inversion is a rare, but life threatening, obstetrical emergency which occurs when the uterine fundus collapses into the endometrial cavity. Various conservative and surgical therapies have been outlined in the literature for the management of uterine inversions. Case. We present a case of a chronic, recurrent uterine inversion, which was diagnosed following spontaneous vaginal delivery and recurred seven weeks later. The uterine inversion was likely due to a leiomyoma. This late-presenting, chronic, recurring uterine inversion was treated with a vaginal hysterectomy. Conclusion. Uterine inversions can occur in both acute and chronic phases. Persistent vaginal bleeding with the appearance of a prolapsing fibroid should prompt further investigation for uterine inversion and may require surgical therapy. A vaginal hysterectomy may be an appropriate management option in select populations and may be considered in women who do not desire to maintain reproductive function

    Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data: population based cohort study

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    Objective: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. Design: Population based cohort study. Setting: Data from the UK Biobank study, collected between March 2006 and July 2010. Participants: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. Main outcome measures: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. Results: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. Conclusions: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population

    New Measurements of the Motion of the Zodiacal Dust

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    Using the Wisconsin H-Alpha Mapper (WHAM), we have measured at high spectral resolution and high signal-to-noise the profile of the scattered solar Mg I 5184 absorption line in the zodiacal light. The observations were carried out toward 49 directions that sampled the ecliptic equator from solar elongations of 48\dg (evening sky) to 334\dg (morning sky) plus observations near +47\dg and +90\dg ecliptic latitude. The spectra show a clear prograde kinematic signature that is inconsistent with dust confined to the ecliptic plane and in circular orbits influenced only by the sun's gravity. In particular, the broadened widths of the profiles, together with large amplitude variations in the centroid velocity with elongation angle, indicate that a significant population of dust is on eccentric orbits. In addition, the wide, flat-bottomed line profile toward the ecliptic pole indicates a broad distribution of orbital inclinations extending up to about 30\dg - 40\dg with respect to the ecliptic plane. The absence of pronounced asymmetries in the shape of the profiles limits the retrograde population to less than 10% of the prograde population and also places constraints on the scattering phase function of the particles. These results do not show the radial outflow or evening--morning velocity amplitude asymmetry reported in some earlier investigations. The reduction of the spectra included the discovery and removal of extremely faint, unidentified terrestrial emission lines that contaminate and distort the underlying Mg I profile. This atmospheric emission is too weak to have been seen in earlier, lower signal-to-noise observations, but it probably affected the line centroid measurements of previous investigations.Comment: 24 pages, 8 figures, 1 table, to appear in ApJ v612; figures appear low-res only on scree

    Alterations in cellular metabolism modulate CD1d-mediated NKT-cell responses

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    Natural killer T (NKT) cells play a critical role in the host's innate immune response. CD1d-mediated presentation of glycolipid antigens to NKT cells has been established; however, the mechanisms by which NKT cells recognize infected or cancerous cells remain unclear. 5′-AMP activated protein kinase (AMPK) is a master regulator of lipogenic pathways. We hypothesized that activation of AMPK during infection and malignancy could alter the repertoire of antigens presented by CD1d and serve as a danger signal to NKT cells. In this study, we examined the effect of alterations in metabolism on CD1d-mediated antigen presentation to NKT cells and found that an infection with lymphocytic choriomeningitis virus rapidly increased CD1d-mediated antigen presentation. Hypoxia inducible factors (HIF) enhance T-cell effector functions during infection, therefore antigen presenting cells pretreated with pharmacological agents that inhibit glycolysis, induce HIF and activate AMPK were assessed for their ability to induce NKT-cell responses. Pretreatment with 2-deoxyglucose, cobalt chloride, AICAR and metformin significantly enhanced CD1d-mediated NKT-cell activation. In addition, NKT cells preferentially respond to malignant B cells and B-cell lymphomas express HIF-1α. These data suggest that targeting cellular metabolism may serve as a novel means of inducing innate immune responses

    Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank

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    OBJECTIVE: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. DESIGN: Population based cohort study. SETTING: Data from the UK Biobank study, collected between March 2006 and July 2010. PARTICIPANTS: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. MAIN OUTCOME MEASURES: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. RESULTS: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. CONCLUSIONS: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population

    Cassini VIMS observations of H3+ emission on the nightside of Jupiter

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    We present the first detailed analysis of H3+ nightside emission from Jupiter, using Visual and Infrared Mapping Spectrometer (VIMS) data from the Cassini flyby in 2000–2001, producing the first Jovian maps of nightside H3+ emission, temperature, and column density. Using these, we identify and characterize regions of H3+ nightside emission, compared against past observations of H3+ emission on the dayside. We focus our investigation on the region previously described as “mid-to-low latitude emission,” the source for which has been controversial. We find that the brightest of this emission is generated at Jovigraphic latitudes similar to the most equatorward extent of the main auroral emission but concentrated at longitudes eastward of this emission. The emission is produced by enhanced H3+ density, with temperatures dropping away in this region. This emission has a loose association with the predicted location of diffuse aurora produced by pitch angle scattering in the north, but not in the south. This emission also lays in the path of subrotating winds flowing from the aurora, suggesting a transport origin. Some differences are seen between dayside and nightside subauroral emissions, with dayside emission extending more equatorward, perhaps caused by the lack of sunlight ionization on the nightside, and unmeasured changes in temperature. Ionospheric temperatures are hotter in the polar region (~1100–1500 K), dropping away toward the equator (as low as 750 K), broadly similar to values on the dayside, highlighting the dominance of auroral effects in the polar region. No equatorial emission is observed, suggesting that very little particle precipitation occurs away from the polar regions

    Conceptualizing Ecological Responses to Dam Removal: If You Remove It, What’s to Come?

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    One of the desired outcomes of dam decommissioning and removal is the recovery of aquatic and riparian ecosystems. To investigate this common objective, we synthesized information from empirical studies and ecological theory into conceptual models that depict key physical and biological links driving ecological responses to removing dams. We define models for three distinct spatial domains: upstream of the former reservoir, within the reservoir, and downstream of the removed dam. Emerging from these models are response trajectories that clarify potential pathways of ecological transitions in each domain. We illustrate that the responses are controlled by multiple causal pathways and feedback loops among physical and biological components of the ecosystem, creating recovery trajectories that are dynamic and nonlinear. In most cases, short-term effects are typically followed by longer-term responses that bring ecosystems to new and frequently predictable ecological condition, which may or may not be similar to what existed prior to impoundment
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