Placental Uric Acid Transport System: Glucose Transporter 9 (SLC2A9)

Placental Uric Acid Transport System: Glucose Transporter 9 (SLC2A9). INTRODUCTION: Pre-eclampsia, a pregnancy-specific disease, contributes substantially to perinatal morbidity and mortality of both the mother and her child. Pre-eclampsia is often associated with high maternal urate serum levels, which in turn has been shown to play a role in the pathogenesis of this disease. The aim of this study was to investigate the glucose transporter GLUT9-mediated placental uric acid transport system. METHODS: In this study western blot, immunofluorescence techniques as well as a transepithelial transport (Transwell) model were used to assess GLUT9 protein expression and, respectively, uric acid transport activity. Electrophysiological techniques and transmission electron microscopy (TEM) were used to characterize the properties and the structure of GLUT9. RESULTS: Uric acid is transported across a BeWo choriocarcinoma cell monolayer with 530 pmol/min. We could successfully overexpress and for the first time purify the GLUT9b isoform using the Xenopus laevis oocytes expression system. Chloride seems to modulate the urate transport system. TEM revealed that GLUT9b isoform is present as monomer and dimmer in the Xenopus laevis overexpression model. A class average of all the particles allowed us to develop a first model of human GLUT9b structure, which was derived from the published crystal structure of the bacterial homologue of GLUT1-4. CONCLUSIONS: In vitro the “materno-fetal” transport of uric acid is slow indicating that in vivo the fetus might be protected from short-term fluctuations of maternal urate serum levels. The low-resolution structure obtained from TEM validates the proposed homology model regarding the structure of human GLUT9b. In ongoing studies this model is used to perform virtual screening to identify novel modulators of the urate transport system enabling the development of novel therapies in pregnancy complications.

Benchmarking analogue models of brittle thrust wedges

We performed a quantitative comparison of brittle thrust wedge experiments to evaluate the variability among analogue models and to appraise the reproducibility and limits of model interpretation. Fifteen analogue modeling laboratories participated in this benchmark initiative. Each laboratory received a shipment of the same type of quartz and corundum sand and all laboratories adhered to a stringent model building protocol and used the same type of foil to cover base and sidewalls of the sandbox. Sieve structure, sifting height, filling rate, and details on off-scraping of excess sand followed prescribed procedures. Our analogue benchmark shows that even for simple plane-strain experiments with prescribed stringent model construction techniques, quantitative model results show variability, most notably for surface slope, thrust spacing and number of forward and backthrusts. One of the sources of the variability in model results is related to slight variations in how sand is deposited in the sandbox. Small changes in sifting height, sifting rate, and scraping will result in slightly heterogeneous material bulk densities, which will affect the mechanical properties of the sand, and will result in lateral and vertical differences in peak and boundary friction angles, as well as cohesion values once the model is constructed. Initial variations in basal friction are inferred to play the most important role in causing model variability. Our comparison shows that the human factor plays a decisive role, and even when one modeler repeats the same experiment, quantitative model results still show variability. Our observations highlight the limits of up-scaling quantitative analogue model results to nature or for making comparisons with numerical models. The frictional behavior of sand is highly sensitive to small variations in material state or experimental set-up, and hence, it will remain difficult to scale quantitative results such as number of thrusts, thrust spacing, and pop-up width from model to nature.