6 research outputs found
Anti-entzündliche und ulzerogene Wirkungen von exogenen Substanzen und endogenen Mediatoren
Der von Lipoxygenasen (LOX) gebildete Mediator Lipoxin (LX) A4 ist an der Abheilung von Entzündungen beteiligt. In dieser Arbeit wurde die gastrale Mukosa von Ratten in den beiden Entzündungsmodellen Ischämie-Reperfusion und Ethanol-induzierter Schaden bei Gabe von LOX-Inhibitoren, einem LXA4-Rezeptorantagonisten bzw. exogenem LXA4 untersucht. Exogenes LXA4 konnte dabei als protektive Substanz gegen gastrale Schäden bei Ischämie-Reperfusion identifiziert werden. Es konnte außerdem gezeigt werden, dass über die einzelnen LOX gebildete Mediatoren, vermutlich LXA4, an der Protektion der gastralen Mukosa gegen ulzerogene Substanzen beteiligt sind. Auch potenziert die Hemmung einer LOX oder Blockade des LXA4-Rezeptors die Ulzerogenität bestimmter Substanzen. Zusammenfassend kann man sagen, dass bei Ratten in der Magenmukosa die LOX und der von ihnen gebildete Mediator LXA4 an der Aufrechterhaltung der Mukosaintegrität bei verschiedenen Entzündungsmodellen beteiligt sind.The mediator lipoxin (LX) A4 is a product of lipoxygenases (LOX) and is involved in the resolution of inflammation. In the present study the gastric mucosa of rats was subjected to two types of inflammation models, ischemia-reperfusion and an ethanol-induced damage with treatment with LOX inhibitors, a LXA4 receptor antagonist and/or exogenous LXA4. Exogenous LXA4 was found to be protective against ischemia-reperfusion induced gastric damage. Additional results demonstrate that mediators synthesised by LOX, probably LXA4, are involved in mucosal protection against ulcerogenic substances. Likewise, inhibition of LOX or blockade of the LXA4 receptor potentiates the ulcerogenicity of certain noxious agents. Taken together, LOX and their product LXA4 are involved in the maintenace of mucosal integrity during various inflammationary conditions in the stomach
A new hybrid record linkage process to make epidemiological databases interoperable: application to the GEMO and GENEPSO studies involving BRCA1 and BRCA2 mutation carriers
International audienceBackground: Linking independent sources of data describing the same individuals enable innovative epidemiological and health studies but require a robust record linkage approach. We describe a hybrid record linkage process to link databases from two independent ongoing French national studies, GEMO (Genetic Modifiers of BRCA1 and BRCA2), which focuses on the identification of genetic factors modifying cancer risk of BRCA1 and BRCA2 mutation carriers, and GENEPSO (prospective cohort of BRCAx mutation carriers), which focuses on environmental and lifestyle risk factors.Methods: To identify as many as possible of the individuals participating in the two studies but not registered by a shared identifier, we combined probabilistic record linkage (PRL) and supervised machine learning (ML). This approach (named "PRL + ML") combined together the candidate matches identified by both approaches. We built the ML model using the gold standard on a first version of the two databases as a training dataset. This gold standard was obtained from PRL-derived matches verified by an exhaustive manual review. Results The Random Forest (RF) algorithm showed a highest recall (0.985) among six widely used ML algorithms: RF, Bagged trees, AdaBoost, Support Vector Machine, Neural Network. Therefore, RF was selected to build the ML model since our goal was to identify the maximum number of true matches. Our combined linkage PRL + ML showed a higher recall (range 0.988-0.992) than either PRL (range 0.916-0.991) or ML (0.981) alone. It identified 1995 individuals participating in both GEMO (6375 participants) and GENEPSO (4925 participants).Conclusions: Our hybrid linkage process represents an efficient tool for linking GEMO and GENEPSO. It may be generalizable to other epidemiological studies involving other databases and registries