Prion Uptake in the Gut: Identification of the First Uptake and Replication Sites

After oral exposure, prions are thought to enter Peyer's patches via M cells and accumulate first upon follicular dendritic cells (FDCs) before spreading to the nervous system. How prions are actually initially acquired from the gut lumen is not known. Using high-resolution immunofluorescence and cryo-immunogold electron microscopy, we report the trafficking of the prion protein (PrP) toward Peyer's patches of wild-type and PrP-deficient mice. PrP was transiently detectable at 1 day post feeding (dpf) within large multivesicular LAMP1-positive endosomes of enterocytes in the follicle-associated epithelium (FAE) and at much lower levels within M cells. Subsequently, PrP was detected on vesicles in the late endosomal compartments of macrophages in the subepithelial dome. At 7–21 dpf, increased PrP labelling was observed on the plasma membranes of FDCs in germinal centres of Peyer's patches from wild-type mice only, identifying FDCs as the first sites of PrP conversion and replication. Detection of PrP on extracellular vesicles displaying FAE enterocyte-derived A33 protein implied transport towards FDCs in association with FAE-derived vesicles. By 21 dpf, PrP was observed on the plasma membranes of neurons within neighbouring myenteric plexi. Together, these data identify a novel potential M cell-independent mechanism for prion transport, mediated by FAE enterocytes, which acts to initiate conversion and replication upon FDCs and subsequent infection of enteric nerves

Perceived spirituality, mindfulness and quality of life in psychiatric patients

There is some evidence of the relationship between spirituality and quality of life, but there are few bibliographic references on these constructs for patients suffering from mental illness; thus, this study was aimed at revealing the possible role of spiritual outlooks as a protective factor in these individuals. The sample consisted of 96 Portuguese psychiatric patients, selected from a psychiatric hospital and assessed based on parameters for quality of life, spirituality and mindfulness. The data support some theories about the nature of the spirituality. Spiritual beliefs are poorly correlated with the quality of life index, and there is a moderate association between these beliefs and some aspects of mindfulness. It is suggested that a spiritual outlook of psychiatric patients should be taken into account in psychological interventions

A century of trends in adult human height

Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5-22.7) and 16.5 cm (13.3-19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8-144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries

Prediction of recurrence after surgery in colorectal cancer patients using radiomics from diagnostic contrast-enhanced computed tomography: a two-center study

International audienc

Performance comparison of modified ComBat for harmonization of radiomic features for multicenter studies

International audienceMulticenter studies are needed to demonstrate the clinical potential value of radiomics as a prognostic tool. However, variability in scanner models, acquisition protocols and reconstruction settings are unavoidable and radiomic features are notoriously sensitive to these factors, which hinders pooling them in a statistical analysis. A statistical harmonization method called ComBat was developed to deal with the "batch effect" in gene expression microarray data and was used in radiomics studies to deal with the "center-effect". Our goal was to evaluate modifications in ComBat allowing for more flexibility in choosing a reference and improving robustness of the estimation. Two modified ComBat versions were evaluated M-ComBat allows to transform all features distributions to a chosen reference, instead of the overall mean, providing more flexibility. B-ComBat adds bootstrap and Monte Carlo for improved robustness in the estimation. BM-ComBat combines both modifications. The four versions were compared regarding their ability to harmonize features in a multicenter context in two different clinical datasets. The first contains 119 locally advanced cervical cancer patients from 3 centers, with magnetic resonance imaging and positron emission tomography imaging. In that case ComBat was applied with 3 labels corresponding to each center. The second one contains 98 locally advanced laryngeal cancer patients from 5 centers with contrast-enhanced computed tomography. In that specific case, because imaging settings were highly heterogeneous even within each of the five centers, unsupervised clustering was used to determine two labels for applying ComBat. The impact of each harmonization was evaluated through three different machine learning pipelines for the modelling step in predicting the clinical outcomes, across two performance metrics (balanced accuracy and Matthews correlation coefficient). Before harmonization, almost all radiomic features had significantly different distributions between labels. These differences were successfully removed with all ComBat versions. The predictive ability of the radiomic models was always improved with harmonization and the improved ComBat provided the best results. This was observed consistently in both datasets, through all machine learning pipelines and performance metrics. The proposed modifications allow for more flexibility and robustness in the estimation. They also slightly but consistently improve the predictive power of resulting radiomic models