Hépatoblastome de l'adulte (à propos d'un cas)

MONTPELLIER-BU Médecine (341722104) / SudocMONTPELLIER-BU Médecine UPM (341722108) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

The transcriptomic analytical level determines the human monocyte-derived macrophage response toward either the infectious agent or the host

Macrophages exhibit multifunctional activity and play a central role in the response toinfectious agents. It is commonly accepted that the plasticity of the response of macrophagesdepends on the type of stimuli. Here we re-evaluate whether the macrophage response isonly dependent on the stimulus. We analyzed the transcriptomic profile of monocyte-derivedmacrophages (MDMs) that were activated with several pathogens and multiple in vitrostimulations.The transcriptomic data were normalized using matched-pair analysis. Furtheranalysis showed a clustering association with (i) specific signatures of the infectious agentand its strategy as well as (ii) a preponderance of MDM overall responses related toindividuals. Currently, the null hypothesis H0 is that the innate MDM response is globallyassociated with the pathogen. Our results reveal that the global innate MDM response isintrinsically and predominantly associated with the individual. Thus, the hypothesis issupported or negated depending on the transcriptomic analytical level

A Novel 8-Predictors Signature to Predict Complicated Disease Course in Pediatric-onset Crohn’s Disease: A Population-based Study

International audienceBackground The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohn’s disease (CD). Our objective was to evaluate a combination of clinical, serological, and genetic factors to predict complicated disease course in pediatric-onset CD. Methods Data for pediatric-onset CD patients, diagnosed before 17 years of age between 1988 and 2004 and followed more than 5 years, were extracted from the population-based EPIMAD registry. The main outcome was defined by the occurrence of complicated behavior (stricturing or penetrating) and/or intestinal resection within the 5 years following diagnosis. Lasso logistic regression models were used to build a predictive model based on clinical data at diagnosis, serological data (ASCA, pANCA, anti-OmpC, anti-Cbir1, anti-Fla2, anti-Flax), and 369 candidate single nucleotide polymorphisms. Results In total, 156 children with an inflammatory (B1) disease at diagnosis were included. Among them, 35% (n = 54) progressed to a complicated behavior or an intestinal resection within the 5 years following diagnosis. The best predictive model (PREDICT-EPIMAD) included the location at diagnosis, pANCA, and 6 single nucleotide polymorphisms. This model showed good discrimination and good calibration, with an area under the curve of 0.80 after correction for optimism bias (sensitivity, 79%, specificity, 74%, positive predictive value, 61%, negative predictive value, 87%). Decision curve analysis confirmed the clinical utility of the model. Conclusions A combination of clinical, serotypic, and genotypic variables can predict disease progression in this population-based pediatric-onset CD cohort. Independent validation is needed before it can be used in clinical practice