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- Pantazis, N, et al.
(författare)
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Determining the likely place of HIV acquisition for migrants in Europe combining subject-specific information and biomarkers data
- 2019
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Ingår i: Statistical methods in medical research. - : SAGE Publications. - 1477-0334 .- 0962-2802. ; 28:7, s. 1979-1997
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Tidskriftsartikel (refereegranskat)abstract
- In most HIV-positive individuals, infection time is only known to lie between the time an individual started being at risk for HIV and diagnosis time. However, a more accurate estimate of infection time is very important in certain cases. For example, one of the objectives of the Advancing Migrant Access to Health Services in Europe (aMASE) study was to determine if HIV-positive migrants, diagnosed in Europe, were infected pre- or post-migration. We propose a method to derive subject-specific estimates of unknown infection times using information from HIV biomarkers’ measurements, demographic, clinical, and behavioral data. We assume that CD4 cell count (CD4) and HIV-RNA viral load trends after HIV infection follow a bivariate linear mixed model. Using post-diagnosis CD4 and viral load measurements and applying the Bayes’ rule, we derived the posterior distribution of the HIV infection time, whereas the prior distribution was informed by AIDS status at diagnosis and behavioral data. Parameters of the CD4–viral load and time-to-AIDS models were estimated using data from a large study of individuals with known HIV infection times (CASCADE). Simulations showed substantial predictive ability (e.g. 84% of the infections were correctly classified as pre- or post-migration). Application to the aMASE study ( n = 2009) showed that 47% of African migrants and 67% to 72% of migrants from other regions were most likely infected post-migration. Applying a Bayesian method based on bivariate modeling of CD4 and viral load, and subject-specific information, we found that the majority of HIV-positive migrants in aMASE were most likely infected after their migration to Europe.
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- Tschandl, P., et al.
(författare)
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Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study
- 2019
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Ingår i: The Lancet Oncology. - 1470-2045 .- 1474-5488. ; 20:7, s. 938-947
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Tidskriftsartikel (refereegranskat)abstract
- Background: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human readers for all clinically relevant types of benign and malignant pigmented skin lesions. Methods: For this open, web-based, international, diagnostic study, human readers were asked to diagnose dermatoscopic images selected randomly in 30-image batches from a test set of 1511 images. The diagnoses from human readers were compared with those of 139 algorithms created by 77 machine-learning labs, who participated in the International Skin Imaging Collaboration 2018 challenge and received a training set of 10 015 images in advance. The ground truth of each lesion fell into one of seven predefined disease categories: intraepithelial carcinoma including actinic keratoses and Bowen's disease; basal cell carcinoma; benign keratinocytic lesions including solar lentigo, seborrheic keratosis and lichen planus-like keratosis; dermatofibroma; melanoma; melanocytic nevus; and vascular lesions. The two main outcomes were the differences in the number of correct specific diagnoses per batch between all human readers and the top three algorithms, and between human experts and the top three algorithms. Findings: Between Aug 4, 2018, and Sept 30, 2018, 511 human readers from 63 countries had at least one attempt in the reader study. 283 (55·4%) of 511 human readers were board-certified dermatologists, 118 (23·1%) were dermatology residents, and 83 (16·2%) were general practitioners. When comparing all human readers with all machine-learning algorithms, the algorithms achieved a mean of 2·01 (95% CI 1·97 to 2·04; p<0·0001) more correct diagnoses (17·91 [SD 3·42] vs 19·92 [4·27]). 27 human experts with more than 10 years of experience achieved a mean of 18·78 (SD 3·15) correct answers, compared with 25·43 (1·95) correct answers for the top three machine algorithms (mean difference 6·65, 95% CI 6·06–7·25; p<0·0001). The difference between human experts and the top three algorithms was significantly lower for images in the test set that were collected from sources not included in the training set (human underperformance of 11·4%, 95% CI 9·9–12·9 vs 3·6%, 0·8–6·3; p<0·0001). Interpretation: State-of-the-art machine-learning classifiers outperformed human experts in the diagnosis of pigmented skin lesions and should have a more important role in clinical practice. However, a possible limitation of these algorithms is their decreased performance for out-of-distribution images, which should be addressed in future research. Funding: None. © 2019 Elsevier Ltd
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- Gomez-Velazquez, Melisa, et al.
(författare)
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CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart
- 2017
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Ingår i: PLOS Genetics. - : PUBLIC LIBRARY SCIENCE. - 1553-7390 .- 1553-7404. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- Cardiac progenitors are specified early in development and progressively differentiate and mature into fully functional cardiomyocytes. This process is controlled by an extensively studied transcriptional program. However, the regulatory events coordinating the progression of such program from development to maturation are largely unknown. Here, we show that the genome organizer CTCF is essential for cardiogenesis and that it mediates genomic interactions to coordinate cardiomyocyte differentiation and maturation in the developing heart. Inactivation of Ctcf in cardiac progenitor cells and their derivatives in vivo during development caused severe cardiac defects and death at embryonic day 12.5. Genome wide expression analysis in Ctcf mutant hearts revealed that genes controlling mitochondrial function and protein production, required for cardiomyocyte maturation, were upregulated. However, mitochondria from mutant cardiomyocytes do not mature properly. In contrast, multiple development regulatory genes near predicted heart enhancers, including genes in the IrxA cluster, were downregulated in Ctcf mutants, suggesting that CTCF promotes cardiomyocyte differentiation by facilitating enhancer-promoter interactions. Accordingly, loss of CTCF disrupts gene expression and chromatin interactions as shown by chromatin conformation capture followed by deep sequencing. Furthermore, CRISPR-mediated deletion of an intergenic CTCF site within the IrxA cluster alters gene expression in the developing heart. Thus, CTCF mediates local regulatory interactions to coordinate transcriptional programs controlling transitions in morphology and function during heart development.
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- Polley, Craig M., et al.
(författare)
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Fragility of the Dirac Cone Splitting in Topological Crystalline Insulator Heterostructures
- 2018
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Ingår i: ACS Nano. - : AMER CHEMICAL SOC. - 1936-0851 .- 1936-086X. ; 12:1, s. 617-626
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Tidskriftsartikel (refereegranskat)abstract
- The "double Dirac cone" 2D topological interface states found on the (001) faces of topological crystalline insulators such as Pb1-xSnxSe feature degeneracies located away from time reversal invariant momenta and are a manifestation of both mirror symmetry protection and valley interactions. Similar shifted degeneracies in 1D interface states have been highlighted as a potential basis for a topological transistor, but realizing such a device will require a detailed understanding of the intervalley physics involved. In addition, the operation of this or similar devices outside of ultrahigh vacuum will require encapsulation, and the consequences of this for the topological interface state must be understood. Here we address both topics for the case of 2D surface states using angle-resolved photoemission spectroscopy. We examine bulk Pb1-xSnxSe(001) crystals overgrown with PbSe, realizing trivial/topological heterostructures. We demonstrate that the valley interaction that splits the two Dirac cones at each (X) over bar is extremely sensitive to atomic-scale details of the surface, exhibiting non-monotonic changes as PbSe deposition proceeds. This includes an apparent total collapse of the splitting for sub-monolayer coverage, eliminating the Lifshitz transition. For a large overlayer thickness we observe quantized PbSe states, possibly reflecting a symmetry confinement mechanism at the buried topological interface.
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