IL-15 modulates the effect of retinoic acid, promoting inflammation rather than oral tolerance to dietary antigens

3 páginas.-- Evaluation of: DePaolo RW, Abadie V, Tang F et al. Co-adjuvant effects of retinoic acid and IL-15 induce inflammatory immunity to dietary antigens. Nature 471(7337), 220–224 (2011).The physiological immune response in the intestine against dietary proteins and commensal flora is characterized by regulatory mechanisms (tolerance) that prevent harmful consequences. Intestinal dendritic cells (DCs) have a central role in the development of immunosuppressive regulatory T cells owing to their ability to produce TGF-b and retinoic acid (RA). However, the article under evaluation shows an unexpected effect of RA – that of promoting a proinflammatory phenotype in intestinal DCs involved in the generation of inflammatory immune responses to dietary antigens. By using a double transgenic murine model that resembles human celiac disease, it was demonstrated that RA synergizes with IL‑15 in promoting the breakdown of gluten tolerance and the development of enteropathy. The tissue microenvironment modulates DC function, and immune therapies that are based on RA aiming to restore oral tolerance should be used with caution because the presence of IL‑15 (and/or other proinflammatory cytokines) may have undesirable effects.Peer reviewe

Strategies for feeding the world more sustainably with organic agriculture

The authors are grateful for the inputs from Caterina Batello, Jan Breithaupt, Carlo Cafiero, Marianna Campeanu, Reto Cumani, Rich Conant, Piero Conforti, Marie-Aude Even, Karen Franken, Andreas Gattinger, Pierre Gerber, Frank Hayer, Jippe Hoogeven, Stefan Hörtenhuber, Mathilde Iweins, John Lantham, Robert Mayo, Eric Meili, Soren Moller, Jamie Morrison, Alexander Müller, Noemi Nemes, Monica Petri, Tim Robinson, Nicolas Sagoff, Henning Steinfeld, Francesco Tubiello, Helga Willer, and thank Robert Home for checking the language. KHE gratefully acknowledges funding from ERC-2010-Stg-263522 (LUISE). The input of PS contributes to the DEVIL project (NE/M021327/1), funded under the Belmont Forum / FACCE-JPI. This paper contributes to the Global Land Project (www.globallandproject.org). The authors acknowledge funding for open access publication by the Institute of Environmental Decisions, Federal Institutes of Technology, Zurich.Peer reviewedPublisher PD

Impacts of feeding less food-competing feedstuffs to livestock on global food system sustainability

Funding Christian Schader, Adrian Muller, Nadia El-Hage Scialabba, Judith Hecht, Anne Isensee, Harinder P.S. Makkar, Peter Klocke, Florian Leiber, Matthias Stolze, Urs Niggli thank FAO for funding this research. K.E. gratefully acknowledges funding from ERC-2010-Stg-263522 LUISE. Additional data and method details are provided in the supplementary materials. The contribution of P.S. is supported by funding from the Belmont Forum-FACCE-JPI Project ‘Delivering Food on Limited Land’ (DEVIL), with the UK contribution supported by NERC (NE/M021327/1).Peer reviewedPublisher PD

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology:a multicentre, retrospective cohort study

International audienceBackground Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. Methods In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. Interpretation Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.Comment: conferenc

Sex-specific pathways in early cardiac response to pressure overload in mice

Pressure overload (PO) first causes cardiac hypertrophy and then heart failure (HF), which are associated with sex differences in cardiac morphology and function. We aimed to identify genes that may cause HF-related sex differences. We used a transverse aortic constriction (TAC) mouse model leading to hypertrophy without sex differences in cardiac function after 2 weeks, but with sex differences in hypertrophy 6 and 9 weeks after TAC. Cardiac gene expression was analyzed 2 weeks after surgery. Deregulated genes were classified into functional gene ontology (GO) categories and used for pathway analysis. Classical marker genes of hypertrophy were similarly upregulated in both sexes (α-actin, ANP, BNP, CTGF). Thirty-five genes controlling mitochondrial function (PGC-1, cytochrome oxidase, carnitine palmitoyl transferase, acyl-CoA dehydrogenase, pyruvate dehydrogenase kinase) had lower expression in males compared to females after TAC. Genes encoding ribosomal proteins and genes associated with extracellular matrix remodeling exhibited relative higher expression in males (collagen 3, matrix metalloproteinase 2, TIMP2, and TGFβ2, all about twofold) after TAC. We confirmed 87% of the gene expression by real-time polymerase chain reaction. By GO classification, female-specific genes were related to mitochondria and metabolism and males to matrix and biosynthesis. Promoter studies confirmed the upregulation of PGC-1 by E2. Less downregulation of metabolic genes in female hearts and increased protein synthesis capacity and deregulation of matrix remodeling in male hearts characterize the sex-specific early response to PO. These differences could contribute to subsequent sex differences in cardiac function and HF

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Reward Versus Nonreward Sensitivity of the Medial Versus Lateral Orbitofrontal Cortex Relates to the Severity of Depressive Symptoms

BackgroundThe orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.MethodsActivations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.ResultsThe medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).ConclusionsActivations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores