35 research outputs found

    Marine Bacterial Sialyltransferases

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    Sialyltransferases transfer N-acetylneuraminic acid (Neu5Ac) from the common donor substrate of these enzymes, cytidine 5â€Č-monophospho-N-acetylneuraminic acid (CMP-Neu5Ac), to acceptor substrates. The enzymatic reaction products including sialyl-glycoproteins, sialyl-glycolipids and sialyl-oligosaccharides are important molecules in various biological and physiological processes, such as cell-cell recognition, cancer metastasis, and virus infection. Thus, sialyltransferases are thought to be important enzymes in the field of glycobiology. To date, many sialyltransferases and the genes encoding them have been obtained from various sources including mammalian, bacterial and viral sources. During the course of our research, we have detected over 20 bacteria that produce sialyltransferases. Many of the bacteria we isolated from marine environments are classified in the genus Photobacterium or the closely related genus Vibrio. The paper reviews the sialyltransferases obtained mainly from marine bacteria

    La qualité de la mangue (Mangifera indica) : une étude du continuum pré et post-récolte par analyse expérimentale et modélisation

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    This thesis is part of a project initiated at CIRAD in 2000 (Lechaudel et al. 2004, Nodey et al. 2014) for the improvement of the quality of Cogshall mangoes produced in RĂ©union. The main objective of this study was to analyse the effect of agronomic practices and storage conditions on mango's quality considering the continuum between pre- and post-harvest. Then using those analysis to identify possible levers of controls to improve the quality of Cogshall mango. Three complementary approaches were used in this work. The first approach was an experimental study focused on the evolution of fruit quality according to agronomic practices (leaves to fruit ratio), harvest dates and storage conditions (temperature and storage duration). Quality was assessed using indicators of maturity (respiration and ethylene emissions), physical quality (fresh weight, dry weight, colour, etc.) and gustatory quality (sugar concentrations, acidity, etc.). The results showed the importance of the source-sink relationship between the fruit and the branch on the fruit’s growth. In addition, the quality of the fruit at harvest largely determines the quality of the fruit in storage at maturity. The harvest induces the maturation of harvested fruits. Storage practices are then used to control and optimize this harvest-induced ripening. Low temperatures used during storage can extend the storage duration and ensure an acceptable concentration of sugars even before the climacteric crisis. The second approach was designed to study the variations of sugars in fruits through a model. This model was calibrated using available data (Lechaudel et al., 2005b; Joas et al., 2009) and the data collected for the experimental approach. This 'sugar model' simulates the variations of the 4 main sugars (starch, sucrose, fructose, and glucose) during the growth and the maturation on-tree and stored fruits. This approach suggested a strong significance, in pre-harvest, of starch and sucrose synthesis metabolisms. While in post-harvest, the fluxes representing the sucrose synthesis, starch degradation and the transformation of glucose molecules into fructose molecules are the most significant ones. The third approach used a "virtual mango" model to identify potentially beneficial agronomic and storage practices to improve fruit quality. All models developed for the sugar model were added to existing growth models (Lechaudel et al., 2005a, 2007). This coupled model was then adapted to include the fruit’s weight loss during the storage phase. The 'virtual mango' model was used to simulate changes of quality (fresh weight, dry matter content and sweetness) according to multiple possible combinations of cultural practices and storage conditions. These simulations are in accordance with the observed significance of agronomical practices during the growth and harvest date on the quality of fully matured fruit. Non-limiting conditions (sufficient irrigation and light exposure with reasonable fruit load) would result in the best possible fruit quality. Harvest dates and storage practices would then be selected according to conditions during growth and selected markets. On the one hand, later harvests are more suitable for local markets with good quality fruit and a shelf life of a few days. On the other hand, earlier harvests allow for longer storage durations (export, longer time to market, etc.) at the cost of a slight decrease in fruit quality at maturity. Even though the "virtual mango" model can only predict variations in fresh weight, dry matter content and sugar concentrations throughout the growth and ripening of mangoes. All the analysis and models produced in this work are relevant tools for studying and monitoring the development of mango quality throughout the pre- and post-harvest continuum.Cette thĂšse s’inscrit dans le cadre d’un projet initiĂ© au CIRAD en 2000 (Lechaudel et al. 2004, Nodey et al. 2014) pour l’amĂ©lioration de la qualitĂ© des mangues Cogshall produites Ă  la RĂ©union. Cette Ă©tude a Ă©tĂ© construite autour de l’analyse des pratiques agronomiques et de conservations sur la qualitĂ© de la mangue tout au long du continuum entre le prĂ© et le post-rĂ©colte afin d’identifier des leviers d’amĂ©lioration de la qualitĂ© des mangues Cogshall. Trois approches complĂ©mentaires ont Ă©tĂ© rĂ©alisĂ©es lors de ce travail. La premiĂšre approche a Ă©tĂ© une Ă©tude expĂ©rimentale centrĂ©e autour de l’évolution de la qualitĂ© des fruits en fonction des pratiques agronomiques (rapport feuilles/fruits), des dates de rĂ©colte et des conditions de conservation (tempĂ©rature et temps de conservation). La qualitĂ© a Ă©tĂ© Ă©valuĂ©e en utilisant des indicateurs de maturitĂ© (respiration et Ă©missions d’éthylĂšne), de qualitĂ© physique (poids frais, poids sec, couleur, etc.) et de qualitĂ© gustative (concentrations des sucres, aciditĂ©, etc.). Les rĂ©sultats ont montrĂ© l’importance de la relation source-puits entre le fruit et le rameau sur la croissance. De plus, la qualitĂ© Ă  la rĂ©colte dĂ©termine en grande partie la qualitĂ© potentielle des fruits en conservation. La rĂ©colte induit la maturation de tous les fruits rĂ©coltĂ©s. Les pratiques de conservation sont alors utilisĂ©es pour contrĂŽler et optimiser cette maturation aprĂšs la rĂ©colte. La deuxiĂšme approche a Ă©tĂ© construite pour Ă©tudier les variations des sucres dans les fruits au travers d’un modĂšle mĂ©caniste. Ce modĂšle a Ă©tĂ© calibrĂ© en utilisant des donnĂ©es existantes (Lechaudel et al., 2005b ; Joas et al., 2009) et les donnĂ©es rĂ©coltĂ©es lors de l’approche expĂ©rimentale. Ce « modĂšle sucres » simule les variations des 4 sucres majeurs (amidon, sucrose, fructose et glucose) durant la croissance et la maturation sur l’arbre ainsi qu’en chambre froide. Cette approche a suggĂ©rĂ© une forte importance, en prĂ©-rĂ©colte, des mĂ©tabolismes de synthĂšse de l’amidon et du saccharose. Alors qu’en post-rĂ©colte, les flux les plus important seraient ceux responsable de la synthĂšse du saccharose, de la dĂ©gradation de l’amidon ainsi que le flux reprĂ©sentant transformation des molĂ©cules de glucose en molĂ©cules de fructose. La troisiĂšme approche a utilisĂ© un modĂšle « mangue virtuelle » pour identifier des pratiques agronomiques et de conservation potentiellement avantageuse pour amĂ©liorer la qualitĂ© des fruits. Le modĂšle « sucre » a Ă©tĂ© ajoutĂ© aux modĂšles de croissances existants (Lechaudel et al., 2005a, 2007). Ce couplage de modĂšle a Ă©tĂ© ensuite adaptĂ© pour estimer la perte en masse des fruits lors de la phase de conservation. Le modĂšle « mangue virtuelle » a Ă©tĂ© utilisĂ© pour simuler les Ă©volutions de la qualitĂ© en fonction de multiples scĂ©narios possibles de pratiques culturales et de conditions de conservation. Ces simulations appuient l’importance des conditions de croissance et de la date de la rĂ©colte sur la qualitĂ© des fruits observĂ©es dans les analyses expĂ©rimentales. Des conditions non-limitantes (bonne irrigation et exposition lumineuse avec une charge en fruit raisonnable) permettraient d’obtenir la meilleure qualitĂ© possible. Les dates de rĂ©colte ainsi que les pratiques de conservation seraient alors sĂ©lectionnĂ©es en fonction des conditions de croissance et des marchĂ©s souhaitĂ©s. Les rĂ©coltes tardives sont adaptĂ©es pour une vente locale avec des fruits de bonne qualitĂ© mais avec un temps de conservation court. Alors que des rĂ©coltes prĂ©coces assurent des durĂ©es de conservation longues au prix d’une lĂ©gĂšre diminution de la qualitĂ© des fruits Ă  maturitĂ©. MĂȘme si le modĂšle « mangue virtuelle » ne permet de prĂ©dire que quelques indicateurs de qualitĂ©s lors de la croissance et de la maturation des mangues. L’ensemble des analyses et des modĂšles produits se prĂ©sentent comme des outils pertinents pour l’étude et le pilotage de l’élaboration de la qualitĂ© des mangues tout au long du continuum prĂ©- et post-rĂ©colte

    Quality of mangoes (Mangifera indica) : a study of the pre- and post-harvest continuum through experimental analysis and modelling

    No full text
    Cette thĂšse s’inscrit dans le cadre d’un projet initiĂ© au CIRAD en 2000 (Lechaudel et al. 2004, Nodey et al. 2014) pour l’amĂ©lioration de la qualitĂ© des mangues Cogshall produites Ă  la RĂ©union. Cette Ă©tude a Ă©tĂ© construite autour de l’analyse des pratiques agronomiques et de conservations sur la qualitĂ© de la mangue tout au long du continuum entre le prĂ© et le post-rĂ©colte afin d’identifier des leviers d’amĂ©lioration de la qualitĂ© des mangues Cogshall. Trois approches complĂ©mentaires ont Ă©tĂ© rĂ©alisĂ©es lors de ce travail. La premiĂšre approche a Ă©tĂ© une Ă©tude expĂ©rimentale centrĂ©e autour de l’évolution de la qualitĂ© des fruits en fonction des pratiques agronomiques (rapport feuilles/fruits), des dates de rĂ©colte et des conditions de conservation (tempĂ©rature et temps de conservation). La qualitĂ© a Ă©tĂ© Ă©valuĂ©e en utilisant des indicateurs de maturitĂ© (respiration et Ă©missions d’éthylĂšne), de qualitĂ© physique (poids frais, poids sec, couleur, etc.) et de qualitĂ© gustative (concentrations des sucres, aciditĂ©, etc.). Les rĂ©sultats ont montrĂ© l’importance de la relation source-puits entre le fruit et le rameau sur la croissance. De plus, la qualitĂ© Ă  la rĂ©colte dĂ©termine en grande partie la qualitĂ© potentielle des fruits en conservation. La rĂ©colte induit la maturation de tous les fruits rĂ©coltĂ©s. Les pratiques de conservation sont alors utilisĂ©es pour contrĂŽler et optimiser cette maturation aprĂšs la rĂ©colte. La deuxiĂšme approche a Ă©tĂ© construite pour Ă©tudier les variations des sucres dans les fruits au travers d’un modĂšle mĂ©caniste. Ce modĂšle a Ă©tĂ© calibrĂ© en utilisant des donnĂ©es existantes (Lechaudel et al., 2005b ; Joas et al., 2009) et les donnĂ©es rĂ©coltĂ©es lors de l’approche expĂ©rimentale. Ce « modĂšle sucres » simule les variations des 4 sucres majeurs (amidon, sucrose, fructose et glucose) durant la croissance et la maturation sur l’arbre ainsi qu’en chambre froide. Cette approche a suggĂ©rĂ© une forte importance, en prĂ©-rĂ©colte, des mĂ©tabolismes de synthĂšse de l’amidon et du saccharose. Alors qu’en post-rĂ©colte, les flux les plus important seraient ceux responsable de la synthĂšse du saccharose, de la dĂ©gradation de l’amidon ainsi que le flux reprĂ©sentant transformation des molĂ©cules de glucose en molĂ©cules de fructose. La troisiĂšme approche a utilisĂ© un modĂšle « mangue virtuelle » pour identifier des pratiques agronomiques et de conservation potentiellement avantageuse pour amĂ©liorer la qualitĂ© des fruits. Le modĂšle « sucre » a Ă©tĂ© ajoutĂ© aux modĂšles de croissances existants (Lechaudel et al., 2005a, 2007). Ce couplage de modĂšle a Ă©tĂ© ensuite adaptĂ© pour estimer la perte en masse des fruits lors de la phase de conservation. Le modĂšle « mangue virtuelle » a Ă©tĂ© utilisĂ© pour simuler les Ă©volutions de la qualitĂ© en fonction de multiples scĂ©narios possibles de pratiques culturales et de conditions de conservation. Ces simulations appuient l’importance des conditions de croissance et de la date de la rĂ©colte sur la qualitĂ© des fruits observĂ©es dans les analyses expĂ©rimentales. Des conditions non-limitantes (bonne irrigation et exposition lumineuse avec une charge en fruit raisonnable) permettraient d’obtenir la meilleure qualitĂ© possible. Les dates de rĂ©colte ainsi que les pratiques de conservation seraient alors sĂ©lectionnĂ©es en fonction des conditions de croissance et des marchĂ©s souhaitĂ©s. Les rĂ©coltes tardives sont adaptĂ©es pour une vente locale avec des fruits de bonne qualitĂ© mais avec un temps de conservation court. Alors que des rĂ©coltes prĂ©coces assurent des durĂ©es de conservation longues au prix d’une lĂ©gĂšre diminution de la qualitĂ© des fruits Ă  maturitĂ©. MĂȘme si le modĂšle « mangue virtuelle » ne permet de prĂ©dire que quelques indicateurs de qualitĂ©s lors de la croissance et de la maturation des mangues. L’ensemble des analyses et des modĂšles produits se prĂ©sentent comme des outils pertinents pour l’étude et le pilotage de l’élaboration de la qualitĂ© des mangues tout au long du continuum prĂ©- et post-rĂ©colte.This thesis is part of a project initiated at CIRAD in 2000 (Lechaudel et al. 2004, Nodey et al. 2014) for the improvement of the quality of Cogshall mangoes produced in RĂ©union. The main objective of this study was to analyse the effect of agronomic practices and storage conditions on mango's quality considering the continuum between pre- and post-harvest. Then using those analysis to identify possible levers of controls to improve the quality of Cogshall mango. Three complementary approaches were used in this work. The first approach was an experimental study focused on the evolution of fruit quality according to agronomic practices (leaves to fruit ratio), harvest dates and storage conditions (temperature and storage duration). Quality was assessed using indicators of maturity (respiration and ethylene emissions), physical quality (fresh weight, dry weight, colour, etc.) and gustatory quality (sugar concentrations, acidity, etc.). The results showed the importance of the source-sink relationship between the fruit and the branch on the fruit’s growth. In addition, the quality of the fruit at harvest largely determines the quality of the fruit in storage at maturity. The harvest induces the maturation of harvested fruits. Storage practices are then used to control and optimize this harvest-induced ripening. Low temperatures used during storage can extend the storage duration and ensure an acceptable concentration of sugars even before the climacteric crisis. The second approach was designed to study the variations of sugars in fruits through a model. This model was calibrated using available data (Lechaudel et al., 2005b; Joas et al., 2009) and the data collected for the experimental approach. This 'sugar model' simulates the variations of the 4 main sugars (starch, sucrose, fructose, and glucose) during the growth and the maturation on-tree and stored fruits. This approach suggested a strong significance, in pre-harvest, of starch and sucrose synthesis metabolisms. While in post-harvest, the fluxes representing the sucrose synthesis, starch degradation and the transformation of glucose molecules into fructose molecules are the most significant ones. The third approach used a "virtual mango" model to identify potentially beneficial agronomic and storage practices to improve fruit quality. All models developed for the sugar model were added to existing growth models (Lechaudel et al., 2005a, 2007). This coupled model was then adapted to include the fruit’s weight loss during the storage phase. The 'virtual mango' model was used to simulate changes of quality (fresh weight, dry matter content and sweetness) according to multiple possible combinations of cultural practices and storage conditions. These simulations are in accordance with the observed significance of agronomical practices during the growth and harvest date on the quality of fully matured fruit. Non-limiting conditions (sufficient irrigation and light exposure with reasonable fruit load) would result in the best possible fruit quality. Harvest dates and storage practices would then be selected according to conditions during growth and selected markets. On the one hand, later harvests are more suitable for local markets with good quality fruit and a shelf life of a few days. On the other hand, earlier harvests allow for longer storage durations (export, longer time to market, etc.) at the cost of a slight decrease in fruit quality at maturity. Even though the "virtual mango" model can only predict variations in fresh weight, dry matter content and sugar concentrations throughout the growth and ripening of mangoes. All the analysis and models produced in this work are relevant tools for studying and monitoring the development of mango quality throughout the pre- and post-harvest continuum

    Immune-checkpoint inhibition for digestive cancers

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    IF 33.900International audienc

    ÉpidĂ©miologie du cancer du pancrĂ©as

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    IF 0.853International audienceActually, pancreatic cancer is a major challenge in digestive oncology. Its prognosis remains very poor with a five-year net survival less than 10%. Although if pancreatic cancer incidence was low, data from French digestive cancer registries show a dramatic increase in recent years, more marked in women (annual variation of +3.6% between 1982 and 2012) than in men (+2.3%). The currently recognized risk factors like tobacco or obesity cannot explain this evolving epidemiology. Moreover, progress in understanding pancreatic carcinogenesis is still insufficient. Except for familial aggregation, systematic screening couldn’t be proposed.Le cancer du pancrĂ©as reprĂ©sente aujourd’hui un challenge important en oncologie digestive. Son pronostic est trĂšs sombre avec une survie nette Ă  5 ans infĂ©rieure Ă  10 % tous stades confondus. MĂȘme si son incidence reste faible, les donnĂ©es issues des registres des cancers digestifs français montrent une augmentation au cours des derniĂšres annĂ©es. Cette incidence croissante, plus marquĂ©e chez les femmes (variation annuelle de +3,6 % entre 1982 et 2012) que chez les hommes (+2,3 %), reste aujourd’hui mal expliquĂ©e. Les facteurs de risque actuellement reconnus que sont le tabac et l’obĂ©sitĂ© ne permettent pas Ă  eux seuls d’expliquer cette Ă©volution Ă©pidĂ©miologique. Par ailleurs, les progrĂšs dans la connaissance de la carcinogenĂšse pancrĂ©atique restent encore insuffisants. En dehors des formes familiales pour lesquelles des recommandations de surveillance commencent Ă  Ă©merger, il n’y a pas de place pour le dĂ©pistage des personnes asymptomatiques

    Nutrition entérale en cancérologie digestive

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    International audienceProtein-energy malnutrition, is estimated between 35 and 67% depending on digestive tumor locations, significantly worsens the morbidity and mortality. Nutritional status should be assessed regularly during hospitalization and at each visit. If the diagnosis of undernutrition is retained according to HAS criteria, adapted and personalized nutritional support is essential for an optimal oncological management. The nutritional prescription is often approximate. The evaluation of ingesta, by a dietician or a visual analogical scale, is a necessary prerequisite. Thus, in case of moderate undernutrition with a low intake or in case of severe undernutrition with a functional digestive tract, enteral nutrition appears as the optimal support. This enteral nutrition can be administered through a nasogastric tube, gastrostomy or even jejunostomy depending on the duration of nutrition, the need for upper gastrointestinal surgery or gastroparesis. Nutritional intake, with a standard solution as first line, must be done with caution if the patient is at risk of refeeding syndrome until a target of 30 to 35 kcal/kg/d is reached with 1.2 to 1.5 g/kg/d of protein. Nutrition should be re-evaluated regularly and continued until the nutritional goals set with the patient are achieved
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