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Analysis on the relationship between plasma adhesion molecules, free amino acids and ovarian cancer / 中国医师杂志
Journal of Chinese Physician ; (12): 385-387, 2017.
Article in Chinese | WPRIM | ID: wpr-513631
ABSTRACT
Objective To analyze and study the relationship between plasma adhesion molecules,free amino acids and ovarian cancer.Methods A total of 67 patients with ovarian cancer in our hospital during the time of March 2015 to May 2016 were selected as the observation group,and 67 healthy women at the same time were selected as the control group.The plasma adhesion molecules and free amino acids levels of two groups were detected and compared,The detection levels of observation group with different stages and degree of differentiation of ovarian cancers were compared.The relationship between plasma adhesion molecules,free amino acids and ovarian cancer were analyzed by the Logistic analysis.Results The plasma adhesion molecules levels of observation group were all higher than those of control group (P < 0.05),the plasma free amino acids levels were all lower than those of control group (P < 0.05),and the detection levels of observation group with different stages and degree of differentiation of ovarian cancer plasma adhesion molecules and free amino acid levels had significant differences (P < 0.05).The Logistic analysis showed that the plasma adhesion molecules and free amino acids had close relationship to the ovarian cancer (all P < 0.05).Conclusions The plasma adhesion molecules and free amino acids of the patients with ovarian cancer show abnormal expression state,and the expression levels of patients with different stages and degree of differentiation of ovarian cancer have certain differences,so the detection value of those indexes in the patients with ovarian cancer is higher.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Journal of Chinese Physician Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Journal of Chinese Physician Year: 2017 Type: Article