Anti-TEK monoclonal antibody, clone TEK4

Endothelial cells participate in the pathophysiology of ischemic AKI by increasing the expression of cell adhesion molecules and by recruiting inflammatory cells. We previously showed that endothelial Kruppel-like factor 4 (Klf4) regulates vascular cell adhesion molecule 1 (Vcam1) expression and neointimal formation after carotid injury. In this study, we determined whether endothelial Klf4 is involved in ischemic AKI using endothelial Klf4 conditional knockout (Klf4cKO) mice generated by breeding Tek-Cre mice and Klf4floxed mice. Klf4 cKO mice were phenotypically normal before surgery. However, after renal ischemia-reperfusion injury, Klf4 cKO mice exhibited elevated serum levels of urea nitrogen and creatinine and aggravated renal histology compared with those of Klf4 floxed controls. Moreover, Klf4 cKO mice exhibited enhanced accumulation of neutrophils and lymphocytes and elevated expression of cell adhesion molecules, including Vcam1 and Icam1, in injured kidneys. Notably, statins ameliorated renal ischemia-reperfusion injury in control mice but not in Klf4 cKO mice. Mechanistic analyses in cultured endothelial cells revealed that statins increased KLF4 expression and that KLF4 mediated the suppressive effect of statins on TNF-alpha-induced VCAM1 expression by reducing NF-kappa B binding to the VCAM1 promoter. These results provide evidence that endothelial Klf4 is renoprotective and mediates statin-induced protection against ischemic AKI by regulating the expression of cell adhesion molecules and concomitant recruitment of inflammatory cells.

The research project "Teilenergiekennwerte von Nichtwohngebauden (TEK)" (partial characteristic energy values of non-residential buildings) within the EnOB research program of the German Federal Ministry for Economic Affairs and Energy (BMWi), delivered a database consisting of 93 existing non-residential buildings. The database contains detailed information on properties of the building envelope, energy efficiency of technical installations, user behaviour, measured energy consumptions and calculated energy demands. With these data the commonly observed gap between calculated energy demand for heating and domestic hot water and actual energy consumption will be examined. Generally it is observed, that for energy efficient buildings, the calculated demand tends to underestimate the actual consumption, whilst it tends to overestimate the consumption for older buildings not yet refurbished. This tendency, arising by simple linear regression, however is superimposed by a significant distribution. Hence an extended examination approach seems to be necessary. As further important impact factors for energy demand calculations, usage parameters will be examined by use of the methodology of multiple linear regression. The identified impact factors describe the observed distribution better, although still not completely. Based on the obtained insights of the regression analysis, functions for an estimated energy consumption with standard error are derived in order to diminish the gap towards the actual energy consumption with a certain probability. This methodological approach is suitable especially for the energy assessment of building portfolios or districts, but also for empirical correction of energy saving predictions of individual buildings.