Skin3D: Detection and longitudinal tracking of pigmented skin lesions in 3D total-body textured meshes

We present an automated approach to detect and longitudinally track skin lesions on 3D total-body skin surface scans. The acquired 3D mesh of the subject is unwrapped to a 2D texture image, where a trained objected detection model, Faster R-CNN, localizes the lesions within the 2D domain. These detected skin lesions are mapped back to the 3D surface of the subject and, for subjects imaged multiple times, we construct a graph-based matching procedure to longitudinally track lesions that considers the anatomical correspondences among pairs of meshes and the geodesic proximity of corresponding lesions and the inter-lesion geodesic distances.We evaluated the proposed approach using 3DBodyTex, a publicly available dataset composed of 3D scans imaging the coloured skin (textured meshes) of 200 human subjects. We manually annotated locations that appeared to the human eye to contain a pigmented skin lesion as well as tracked a subset of lesions occurring on the same subject imaged in different poses. Our results, when compared to three human annotators, suggest that the trained Faster R-CNN detects lesions at a similar performance level as the human annotators. Our lesion tracking algorithm achieves an average matching accuracy of 88% on a set of detected corresponding pairs of prominent lesions of subjects imaged in different poses, and an average longitudinal accuracy of 71% when encompassing additional errors due to lesion detection. As there currently is no other large-scale publicly available dataset of 3D total-body skin lesions, we publicly release over 25,000 3DBodyTex manual annotations, which we hope will further research on total-body skin lesion analysis.     

Intestinal Dysbiosis in the Infant and the Future of Lacto-Engineering to Shape the Developing Intestinal Microbiome

PurposeThe goal of this study was to review the role of human milk in shaping the infant intestinal microbiota and the potential of human milk bioactive molecules to reverse trends of increasing intestinal dysbiosis and dysbiosis-associated diseases.MethodsThis narrative review was based on recent and historic literature.FindingsHuman milk immunoglobulins, oligosaccharides, lactoferrin, lysozyme, milk fat globule membranes, and bile salt–stimulating lipase are complex multifunctional bioactive molecules that, among other important functions, shape the composition of the infant intestinal microbiota.ImplicationsThe co-evolution of human milk components and human milk–consuming commensal anaerobes many thousands of years ago resulted in a stable low-diversity infant microbiota. Over the past century, the introduction of antibiotics and modern hygiene practices plus changes in the care of newborns have led to significant alterations in the intestinal microbiota, with associated increases in risk of dysbiosis-associated disease. A better understanding of mechanisms by which human milk shapes the intestinal microbiota of the infant during a vulnerable period of development of the immune system is needed to alter the current trajectory and decrease intestinal dysbiosis and associated diseases.