Continuous taurocholic acid exposure promotes esophageal squamous cell carcinoma progression due to reduced cell loss resulting from enhanced vascular development.

Background:Refluxogenic effects of smoking and alcohol abuse may be related to the risk of esophageal squamous cell carcinoma (ESCC). The present study attempts to clarify the effects of continuous taurocholic acid (TCA) exposure, which is neither mutagenic nor genotoxic, on ESCC progression.Methods:A squamous carcinoma cell line (ESCC-DR) was established from a tumor induced in a rat model of gastroduodenal reflux. ESCC-DR cells were incubated with 2 mM TCA for ≥2 months. The effects of continuous TCA exposure were evaluated in vitro on cell morphology, growth, and invasion and in vivo on xenograft tumor growth in nude mice. Moreover, the mean level of secreted transforming growth factor (TGF)-β1 and vascular endothelial growth factor (VEGF) proteins in cell culture supernatants and mRNA synthesis of TGF-β1 and VEGF-A of ESCC cells were measured. The angiogenic potential was further examined by a migration assay using human umbilical vein endothelial cells (HUVECs).Results:Continuous TCA exposure induced marked formation of filopodia in vitro. Expression levels of angiogenic factors were significantly higher in the cells treated with TCA than in control cells. Tumor xenografts derived from cells pre-exposed to TCA were larger and more vascularized than those derived from control cells. In addition, TCA exposure increased HUVEC migration.Conclusion:Continuous TCA exposure enhanced ESCC progression due to reduced cell loss in vivo. Cell loss was inhibited by TCA-induced vascular endothelial cell migration, which was mediated by TGF-β1 and VEGF-A released from ESCC cells.滋賀医科大学平成27年

Remarques sur les exploitations rurales en Touraine au haut Moyen Âge

La Touraine reste toujours un champ de recherche largement inculte, sinon vierge, pour l’histoire agraire du haut moye âge comme tant d’autres régions qui souffrent également de la rareté du document disponible. Nous avons lancé notre propre recherche en appliquant une question-critère bien connue : propagation ou absence du régime domanial classique dans ces terres situées à la croisée de plusieurs civilisations agraires ? Notre enquête montre qu’il ne suffit pas de trouver les termes comme mansus indominicatus, curtis dominica etc. dans les documents pour constater une vraie introduction de ce régime, mais qu’il faut analyser de plus près en quoi consistaient de tels mansus indominicatus et curtis dominica. Un testament daté de 818 nous a permis de lancer l’hypothèse selon laquelle la Touraine n’a pas vu l’arrivée de ce régime en tant que tel et qu’elle resta largement un pays d’exploitation colongère.The Touraine has been a research field that calls for much progress to be done, for rural and agricultural history of the early middle ages as other regions which uffered from the scarcity of documents. We launched into our own investigation for discovering the main features in land ownings and exploitations with a criterion: if the so-called bipartite classical manor did succeed to establish itself as rural organization on the soil of the Touraine, or not? Our investigations revealed that it was not enough to find out such terms as mansus indominicatus, curtis dominica for exemple, in the documents for asserting an installation of classical manor there, but to come to light with thorough investigations the entities which were qualified by the words mansus indominicatus and curtis dominica. A written will made in 818 permits us to make an assumption that the Touraine remained to be a virgin soil for the classical manor system and it prevailed there rather the colonical land ownings and exploitation during the early middle ages

An Accurate Graph Generative Model with Tunable Features

A graph is a very common and powerful data structure used for modeling communication and social networks. Models that generate graphs with arbitrary features are important basic technologies in repeated simulations of networks and prediction of topology changes. Although existing generative models for graphs are useful for providing graphs similar to real-world graphs, graph generation models with tunable features have been less explored in the field. Previously, we have proposed GraphTune, a generative model for graphs that continuously tune specific graph features of generated graphs while maintaining most of the features of a given graph dataset. However, the tuning accuracy of graph features in GraphTune has not been sufficient for practical applications. In this paper, we propose a method to improve the accuracy of GraphTune by adding a new mechanism to feed back errors of graph features of generated graphs and by training them alternately and independently. Experiments on a real-world graph dataset showed that the features in the generated graphs are accurately tuned compared with conventional models.Comment: This paper was presented at the 32nd International Conference on Computer Communications and Networks (ICCCN 2023) Poster Trac