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        Factors that influence the success of surgery on portosystemic shunts in the dog

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        Factors that influence the succes of surgery on portosystemic shunts in the dog - V1.0.doc (1.402Mb)
        Publication date
        2008
        Author
        Dijkema, Joost
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        Summary
        BACKGROUND: Portosystemic shunts in dogs often require surgical intervention which brings along high costs for the owner. Especially in the case of intrahepatic shunting the outcome of surgery is most uncertain due to complications or an inability of the liver to regenerate after surgery. Our goal was to determine growth factors that are crucial for the outcome of surgery and accordingly to develop a prognostic model to predict outcome of surgery. METHODS: We took liver biopsies from the livers of 46 dogs that were presented at the University clinic for shunt surgery. The group of dogs had a lot of variety in breed, weight, age, shunt type and surgery success. First, RNA was extracted from the liver samples and with this RNA we conducted quantitative polymerase chain reaction (Q-PCR) tests for 21 possible candidate genes for influencing surgery success. Second, proteins were extracted from the liver samples and we performed Western blot tests to establish the data found with the Q-PCR tests. RESULTS: After univariable analysis of the Q-PCR data of all dogs, HGF activator was significant (0,037) with respects to outcome of surgery and c-MET, IGFBP-3 and ABCG2 showed a tendency towards significance. Inside the intrahepatic group, HGF activator was again significant (0,043) and c-MET showed a tendency. Western blots of HGF-pathway proteins PKB-Akt, ERK 1/2, P38MAPK and their phosphorized forms needed significant longer exposure times in the dogs with unsuc-cessful surgery compared to the successful surgery group. Multivariable analysis produced a prediction model with a predictive value of 82,9% CONCLUSIONS: The HGF-pathway seems to play an important role in recovery after shunt surgery. Our prediction model is a step in the right direction but the model needs to be perfected to reach a higher predictive value and it should be tested with larger groups to see if it holds up.
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        https://studenttheses.uu.nl/handle/20.500.12932/2419
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