Evaluating beauty care provided by the hospital to women suffering from breast cancer: qualitative aspects

International audienceGOALS OF WORK: Cancer patients are offered more and more access to beauty care during their stay in the hospital. This kind of intervention has not been evaluated yet. Primary objective of our research was to determine what type of evaluation strategy to be implemented (as a supportive care with quality of life and/or medical benefits; as a service providing immediate comfort); intermediate objective was to investigate in scientific terms (psychological, sociological) the experience of beauty care by patients. PATIENTS AND METHODS: Sixty patients (all users of beauty care provided by hospital, 58 female, most of them treated for breast cancer, two male, mean age 53 years) and 11 nurses and physicians, from four French cancer centres were included. We used direct observation and semi-structured interviews, conducted by a sociologist and a psychologist; different types of beauty care were concerned. RESULTS: All the interviewed patients were satisfied. Patients appreciated acquiring savoir-faire on how to use make-up and on personal image enhancement. Psychological and social well-being benefits were mentioned. The beauty care was not alleged to be reducing the side effects of the treatments, but it had helped patients to accept or bear the burden of them. Providing care beyond that which is directly curative was appreciated by the patients as a sign that they were treated as a "whole" person. CONCLUSION: The survey brings valuable clues concerning beauty care experience by cancer patients; it suggests the relevance of quantitative evaluation of the immediate and long-term effects on the quality of life

T84-intestinal epithelial exosomes bear MHC class II/peptide complexes potentiating antigen presentation by dendritic cells: Function of intestinal epithelial exosomes

International audienceBackground and aims: Intestinal epithelial cells release antigen presenting vesicles (exosomes) bearing MHC class II/peptide complexes stimulating specific immune responses in vivo. To further characterize the role of human epithelial exosomes in antigen presentation, their capacity to load antigenic peptides, to bind immune target cells and to induce T cell activation was analyzed in vitro. Methods: The capacity of exosomes derived from the HLA-DR4 expressing, intestinal epithelial cell line T84, to load the HLA-DR4-specific peptide 3H-HSA 64-76 and to activate a HLA-DR4-restricted T cell hybridoma, was tested in the presence or absence of human monocyte-derived dendritic cells (DCs). Interaction of FITC-labeled exosomes with T cells and DCs was analyzed by flow cytometry and confocal microscopy. Results: T84-derived exosomes, enriched in CD9, CD81, CD82 and A33 antigen, were capable of binding specifically HSA 64-76 peptide on HLA-DR4 molecules and of interacting preferentially with DCs. HSA-loaded exosomes were unable to activate the T cell hybridoma directly, but induced a productive T cell activation through DCs. When HSA peptide was bound to exosomal HLA-DR4 molecules instead of in a soluble form, the threshold of peptide presentation by DCs was markedly decreased (x10-3). Conclusions: Exosomes released by intestinal epithelial cells bear exogenous peptides complexed to MHC class II molecules and interact preferentially with DCs, strongly potentiating peptide presentation to T cells. Epithelial exosomes constitute a powerful link between luminal antigens and local immune cells by mediating the transfer of tiny amounts of luminal antigenic information and facilitating immune surveillance at mucosal surfaces

Secretory IgA mediates retrotranscytosis of intact gliadin peptides via the transferrin receptor in celiac disease

Celiac disease (CD) is an enteropathy resulting from an abnormal immune response to gluten-derived peptides in genetically susceptible individuals. This immune response is initiated by intestinal transport of intact peptide 31-49 (p31-49) and 33-mer gliadin peptides through an unknown mechanism. We show that the transferrin receptor CD71 is responsible for apical to basal retrotranscytosis of gliadin peptides, a process during which p31-49 and 33-mer peptides are protected from degradation. In patients with active CD, CD71 is overexpressed in the intestinal epithelium and colocalizes with immunoglobulin (Ig) A. Intestinal transport of intact p31-49 and 33-mer peptides was blocked by polymeric and secretory IgA (SIgA) and by soluble CD71 receptors, pointing to a role of SIgA–gliadin complexes in this abnormal intestinal transport. This retrotranscytosis of SIgA–gliadin complexes may promote the entry of harmful gliadin peptides into the intestinal mucosa, thereby triggering an immune response and perpetuating intestinal inflammation. Our findings strongly implicate CD71 in the pathogenesis of CD

Closed Patterns Meet n-ary Relations

Set pattern discovery from binary relations has been extensively studied during the last decade. In particular, many complete and efficient algorithms for frequent closed set mining are now available. Generalizing such a task to n-ary relations (n ≥ 2) appears as a timely challenge. It may be important for many applications, for example, when adding the time dimension to the popular objects × features binary case. The generality of the task (no assumption being made on the relation arity or on the size of its attribute domains) makes it computationally challenging. We introduce an algorithm called DATA-PEELER. From an n-ary relation, it extracts all closed n-sets satisfying given piecewise (anti) monotonic constraints. This new class of constraints generalizes both monotonic and antimonotonic constraints. Considering the special case of ternary relations, DATA-PEELER outperforms the state-of-the-art algorithms CUBEMINER and TRIAS by orders of magnitude. These good performances must be granted to a new clever enumeration strategy allowing to efficiently enforce the closeness property. The relevance of the extracted closed n-sets is assessed on real-life 3-and 4-ary relations. Beyond natural 3-or 4-ary relations, expanding a relation with an additional attribute can help in enforcing rather abstract constraints such as the robustness with respect to binarization. Furthermore, a collection of closed n-sets is shown to be an excellent starting poin

Constrained-Based Closed Pattern Mining in n-ary Relations

National audienceMany complete and efficient algorithms for frequent closed set mining are now available. Generalizing such a task to n-ary relations may be important for many applications, e.g., when adding the time dimension to the popular objects X features binary case. The generality of the task - no assumption being made on the relation arity or on the size of its attribute domains - makes it computationally challenging. From a n-ary relation, our algorithm extracts all closed n-sets satisfying given piecewise (anti)-monotonic constraints

Data-Peeler: Constraint-Based Closed Pattern Mining in n-ary Relations

Set pattern discovery from binary relations has been extensively studied during the last decade. In particular, many complete and efficient algorithms which extract frequent closed sets are now available. Generalizing such a task to n-ary relations (n ≥ 2) appears as a timely challenge. It may be important for many applications, e.g., when adding the time dimension to the popular objects × features binary case. The generality of the task — no assumption being made on the relation arity or on the size of its attribute domains — makes it computationally challenging. We introduce an algorithm called Data-Peeler. From a n-ary relation, it extracts all closed n-sets satisfying given piecewise (anti)-monotonic constraints. This new class of constraints generalizes both monotonic and anti-monotonic constraints. Considering the special case of ternary relations, Data-Peeler outperforms the state-of-the-art algorithms CubeMiner and Trias by orders of magnitude. These good performances must be granted to a new clever enumeration strategy allowing an efficient closeness checking. An original application on a real-life 4-ary relation is used to assess the relevancy of closed n-sets constraint-based mining

Extraction d'hyper-rectangles fermés sous contraintes

National audienceDans le cadre de ce résumé étendu, nous présentons l'extension des calculs de concepts formels sous contraintes (et donc celui du calcul d'ensembles fermés pour des données à deux dimensions) au cas de données n-aires

Closed patterns meet n-ary relations

International audienceSet pattern discovery from binary relations has been extensively studied during the last decade. In particular, many complete and efficient algorithms for frequent closed set mining are now available. Generalizing such a task to n-ary relations (n ≥ 2) appears as a timely challenge. It may be important for many applications, for example, when adding the time dimension to the popular objects × features binary case. The generality of the task (no assumption being made on the relation arity or on the size of its attribute domains) makes it computationally challenging. We introduce an algorithm called Data-Peeler. From an n-ary relation, it extracts all closed n-sets satisfying given piecewise (anti) monotonic constraints. This new class of constraints generalizes both monotonic and antimonotonic constraints. Considering the special case of ternary relations, Data-Peeler outperforms the state-of-the-art algorithms CubeMiner and Trias by orders of magnitude. These good performances must be granted to a new clever enumeration strategy allowing to efficiently enforce the closeness property. The relevance of the extracted closed n-sets is assessed on real-life 3-and 4-ary relations. Beyond natural 3-or 4-ary relations, expanding a relation with an additional attribute can help in enforcing rather abstract constraints such as the robustness with respect to binarization. Furthermore, a collection of closed n-sets is shown to be an excellent starting point to compute a tiling of the dataset

Extraction d'hyper-rectangles fermés sous contraintes

National audienceDans le cadre de ce résumé étendu, nous présentons l'extension des calculs de concepts formels sous contraintes (et donc celui du calcul d'ensembles fermés pour des données à deux dimensions) au cas de données n-aires

Data-Peeler: Constraint-based Closed Pattern Mining in n-ary Relations

International audienceSet pattern discovery from binary relations has been extensively studied during the last decade. In particular, many complete and efficient algorithms which extract frequent closed sets are now available. Generalizing such a task to n-ary relations (n > 2) appears as a timely challenge. It may be important for many applications, e.g., when adding the time dimension to the popular objects x features binary case. The generality of the task -- no assumption being made on the relation arity or on the size of its attribute domains -- makes it computationally challenging. We introduce an algorithm called Data-Peeler. From a n-ary relation, it extracts all closed patterns satisfying given piecewise (anti)-monotonic constraints. This new class of constraints generalizes both monotonic and anti-monotonic constraints. Considering the special case of ternary relations, Data-Peeler outperforms the state-of-the-art algorithms CubeMiner and Trias by orders of magnitude. These good performances must be granted to a new clever enumeration strategy allowing an efficient closeness checking. An original application on a real-life 4-ary relation is used to assess the relevancy of closed {\pattern s} constraint-based mining