143174 research outputs found
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An automated method for finding the most distant quasars
No full textUpcoming surveys such as Euclid, the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) and the Nancy Grace Roman Telescope (Roman) will detect hundreds of high-redshift (z ≳ 7) quasars, but distinguishing them from the billions of other sources in these catalogues represents a significant data analysis challenge. We address this problem by extending existing selection methods by using both i) Bayesian model comparison on measured fluxes and ii) a likelihood-based goodness-of-fit test on images, which are then combined using the Fβ statistic (where β is a parameter which can be tuned to prioritise completeness). The result is an automated, reproduceable and objective high-redshift quasar selection pipeline. We test this on both simulations and real data from the cross-matched Sloan Digital Sky Survey (SDSS) and UKIRT Infrared Deep Sky Survey (UKIDSS) catalogues. On this cross-matched dataset we achieve an area under the curve (AUC) score of up to 0.81 and an F3 score of up to 0.79 ; or, if the completeness is fixed to be 0.9 then we can obtain an efficiency of 0.15. This is sufficient to be applied to the Euclid, LSST and Roman data when available
Early-life exposome and health-related immune signatures in childhood
No full textBackground
Early-life environmental exposures are suspected to modify important immune processes related to child health. Yet, no study has investigated immunotoxicity in relation to the exposome and multiple health domains simultaneously.
Methods
Among 845 children (median age 8) from six European birth cohorts included in the Human Early-Life Exposome (HELIX) project, we identified immune signatures of a health score covering cardiometabolic, respiratory/allergic and neurodevelopmental health in children. Those signatures were identified from blood samples in three biological layers (white blood cell (WBC) composition, plasma proteins concentrations, DNA methylation of WBCs) using an advanced factorial analysis supervised on the child health score. Second, we estimated the association between the identified signatures and 91 pre- and postnatal environmental exposures.
Results
Three key immune signatures were associated with a better health score in children: a first protein signature characterizing a low inflammatory profile (R2 = 17 %), a second protein signature characterizing a low inflammatory profile with balanced antiviral Th response (R2 = 2 %), and a WBC signature characterizing an immuno-regulatory and naïve profile (R2 = 2 %). In childhood, less exposure to indoor air pollutants, proximity to blue spaces and public transport, healthy dietary habits and higher social capital were associated with the three immune signatures related to a better health score (regression p-values < 0.05). One signature was identified from DNA methylation, but was not significantly associated with the health score nor with the exposome.
Conclusions
These findings highlight the influence of early-life environmental exposures on key inflammatory processes associated with the cardiometabolic, respiratory and neurodevelopmental health of children
The effect of music and distraction on pain and anxiety during colonoscopy: a systematic review and meta-analysis
No full textAn approach to robust Bayesian regression in astronomy
No full textModel mis-specification (e.g. the presence of outliers) is commonly encountered in astronomical analyses, often requiring the use of ad hoc algorithms which are sensitive to arbitrary thresholds (e.g. sigma-clipping). For any given data set, the optimal approach will be to develop a bespoke statistical model of the data generation and measurement processes, but these come with a development cost; there is hence utility in having generic modelling approaches that are both principled and robust to model mis-specification. Here we develop and implement a generic Bayesian approach to linear regression, based on Student’s t-distributions, that is robust to outliers and mis-specification of the noise model. Our method is validated using simulated data sets with various degrees of model mis-specification; the derived constraints are shown to be systematically less biased than those from a similar model using normal distributions. We demonstrate that, for a data set without outliers, a worst-case inference using t-distributions would give unbiased results with
per cent increase in the reported parameter uncertainties. We also compare with existing analyses of real-world data sets, finding qualitatively different results where normal distributions have been used and agreement where more robust methods have been applied. A Python implementation of this model, t-cup, is made available for others to use
CMIP6 models agree on similar carbon cycle feedbacks between enhancing terrestrial and marine carbon sinks
No full textCarbon dioxide removal (CDR) is a crucial component of climate mitigation required to reach international climate targets. However, gaps exist in our understanding of the responses and feedbacks of the Earth system to the deployment of CDR. In this study, we compare two complementary approaches that enhance the terrestrial and marine carbon sinks with afforestation and reforestation (A/R) and ocean alkalinity enhancement (OAE), respectively, under the high emission scenario SSP5-8.5. Eight CMIP6 Earth system models are utilized, enabling a quantification of both inter-model and internal variability. By mid-century, simulated large-scale deployment of A/R and OAE individually reduces atmospheric CO2 concentrations by up to 20 ppm. For both methods, while carbon removal from the atmosphere is robust, it is difficult to detect the effects on global mean temperature, posing challenges for monitoring, reporting and verification of mitigation efforts. To quantify the carbon cycle feedbacks, we define the carbon cycle feedback ratio of A/R (OAE) as the ratio of changes in the marine (terrestrial) sink to changes in the terrestrial (marine) sink. We show that the carbon cycle feedback ratios of A/R and OAE have similar magnitudes, which are −16% and −13%, respectively. Moreover, although inter-model differences of the simulated amounts of carbon removal due to A/R are large, the corresponding carbon cycle feedback ratios of A/R are similar
Minimal vs specialized exercise equipment for pulmonary rehabilitation
No full textImportance: Pulmonary rehabilitation (PR) improves exercise tolerance, symptom burden, and health-related quality of life for people with chronic respiratory conditions. However, demand for PR outstrips supply. Traditionally, PR has been delivered using specialist, gym-based exercise equipment.
Objective: To investigate whether PR using minimal equipment (PR-min) is noninferior to PR using specialist gym exercise equipment (PR-gym).
Design, Settings, and Participants: This parallel, 2-group, assessor- and statistician-blinded, noninferiority randomized clinical trial compared PR-min with PR-gym. Eligible participants were people with chronic respiratory disease referred for PR to the Regional Pulmonary Rehabilitation Unit in northwest London, UK. Recruitment occurred from October 15, 2018, to December 21, 2021, with a final follow-up to December 14, 2022. Randomization was by an independent web-based system using minimization with 1:1 allocation. Data analysis was performed from May 2023 to January 2025.
Interventions: Both PR programs comprised 2 in-person, outpatient supervised sessions per week for 8 weeks. PR-min used minimal equipment (eg, walking circuit and body weight exercises), whereas PR-gym used specialist exercise equipment (eg, treadmills and weights machines).
Main Outcomes and Measures: The primary outcome was change in incremental shuttle walk (ISW) distance after PR (ie, at 8 weeks; with a predefined noninferiority margin of −24 m). Secondary outcomes included dyspnea, health-related quality of life, costs, and adverse events.
Results: A total of 436 participants (median [IQR] age, 71.7 [63.2-77.7] years; 239 [54.8%] male) were enrolled, with 218 randomized to PR-min and 218 to PR-gym. At 8 weeks, PR-min (n = 136) and PR-gym (n = 130) demonstrated significant improvements in ISW distance with no significant between-group difference in ISW distance change (mean, 1.7 m; 1-sided 97.5% CI lower bound, −16.8), which was within the −24-m noninferiority margin. The intention-to-treat analysis and a robust range of sensitivity analyses all demonstrated that PR-min was noninferior to PR-gym. Similar findings were observed for dyspnea and health-related quality of life. No excess adverse events or costs were seen with intervention.
Conclusions and Relevance: This randomized clinical trial found that PR-min demonstrated noninferiority to PR-gym for exercise capacity, dyspnea, and health-related quality of life. PR-min can expand the number of settings where PR can be provided, thus improving patient accessibility.
Trial Registration: isrctn.org Identifier: ISRCTN1619676
Bone health in a U.K. cohort of youth living with perinatally acquired HIV-1: a longitudinal study
No full textINTRODUCTION: Low bone mineral density (BMD) has been described in children and young people with perinatally acquired HIV (PHIV), which may be related to both traditional (e.g. low body mass index and malnutrition) and HIV-related risk factors (e.g. longstanding exposure to HIV and antiretroviral therapy [ART], with immune suppression, chronic immune activation and inflammation). Here, we evaluate BMD in a U.K. cohort of young people with PHIV by age and ART. METHODS: This longitudinal, observational study was conducted at a U.K. tertiary PHIV service between November 2018 and March 2022. Bone health was assessed in 130 individuals aged 15-19 (n = 50), 20-24 (n = 50) and 25 years and older (n = 30) by dual-energy X-ray absorptiometry, bone mineralization and turnover markers. Low BMD was defined as lumbar spine (LS) and/or femur-BMD z-score below -2, relative to age, sex and ethnicity-matched U.K. population-based normative controls. Two-year follow-up evaluation was performed in those aged 15-19 (n = 42) and 20-24 years (n = 43) at enrolment, which included a group who switched from tenofovir disoproxil fumarate (TDF) to tenofovir alafenamide (TAF) ART at baseline. Bayesian logistic regression models examined predictors of low BMD and the effect of ART-backbone on BMD accrual. RESULTS: At baseline, 57% were female and 82% of black ethnicity, with 31 (24%) on TDF-ART. Sixteen (12%) had low baseline BMD. Over a median follow-up duration of 26 (interquartile range [IQR] 25-29) months, BMD accrual was lower-than-expected in those aged 15-19 years (mean change LS-BMD z-score -0.15 (standard deviation [SD] 0.44)), when compared to normative controls. No associations were seen with HIV parameters or the ART regimen. Participants who switched to TAF-ART had similar BMD accrual 26 (IQR 24-32) months post switch, when compared to those on non-TAF/TDF-ART (mean change LS-BMD z-score TAF -0.01 [SD 0.41] vs. non-TAF/TDF -0.03 [SD 0.54]). CONCLUSIONS: While rates of low BMD were reassuringly low in this cohort, lower-than-expected BMD accrual was observed in younger individuals, relative to normative controls. Overall, BMD accrual on TAF-ART was non-inferior to non-TAF/TDF-ART
An introduction to costing and the types of costs used within health economic studies
No full textThe number of published health economic analyses, especially economic evaluations, has rapidly expanded globally since the 1990s, and costs are an essential component of such studies. Cost is a general term that refers to the value of the resources/inputs used to produce a good or service. However, within health economics, there are several different types of costs (such as financial, economic, unit, average, etc). The terminology and application of these cost types often differ, leading to inconsistencies in the health economics literature. These inconsistencies create challenges in comparing studies and hinder the use of health economic analyses to effectively inform policy decisions. This paper aims to provide an up-to-date overview of the cost types, key cost terms, and definitions of different cost measures used within health economics, while highlighting key inconsistencies in the literature. We also discuss common adjustments made to cost data, such as accounting for inflation, discounting, and currency conversions, as well as the influence of economies of scale and scope on cost estimates. We highlight the different definitions/categories for the different types of costs are not mutually exclusive and that the type of cost that should be used will depend on the purpose of the study, highlighting recommendations of what to do in practice where relevant. The content was tailored to be relevant across both high-income and low and middle-income (LMIC) country contexts
Topology optimization in medical image segmentation with fast χ Euler Characteristic
No full textDeep learning-based medical image segmentation techniques have shown promising results when evaluated based on conventional metrics such as the Dice score or Intersection-over-Union. However, these fully automatic methods often fail to meet clinically acceptable accuracy, especially when topological constraints should be observed, e.g., continuous boundaries or closed surfaces. In medical image segmentation, the correctness of a segmentation in terms of the required topological genus sometimes is even more important than the pixel-wise accuracy. Existing topology-aware approaches commonly estimate and constrain the topological structure via the concept of persistent homology (PH). However, these methods are difficult to implement for high dimensional data due to their polynomial computational complexity. To overcome this problem, we propose a novel and fast approach for topology-aware segmentation based on the Euler Characteristic (χ). First, we propose a fast formulation for χ computation in both 2D and 3D. The scalar χ error between the prediction and ground-truth serves as the topological evaluation metric. Then we estimate the spatial topology correctness of any segmentation network via a so-called topological violation map, i.e., a detailed map that highlights regions with χ errors. Finally, the segmentation results from the arbitrary network are refined based on the topological violation maps by a topology-aware correction network. Our experiments are conducted on both 2D and 3D datasets and show that our method can significantly improve topological correctness while preserving pixel-wise segmentation accuracy