To improve the water solubility of daidzein, solid inclusion complexes of daidzein with two amino-modified β-cyclodextrins (ACDs), i.e., mono-6-amino-6-deoxy-β-cyclodextrin (NCD) and mono-6-ethylenediamino-6-deoxy-β-cyclodextrin (ENCD), were prepared by the saturated solution method in water under the preparation conditions as follows: the ratio of daidzein/ACD was 3∶1 and the stirring time was 72 h (83% and 67% yields, respectively).The formation of two inclusion complexes was confirmed by x-ray diffractometry (XRD) and themogravimetric (TG) analysis.The inclusion stoichiometry of the inclusion complexes was 1∶1 from the Job plot and their complexation stability constants (KS) were 899.2 and 203.8 L/mol from fluorescence titration, respectively.After formation of inclusion complexes with NCD and ENCD, the water solubility of daidzein was dramatically raised from 8.31 μg/mL to 15.2 and 13.2 mg/mL at 25℃, increasing by 1800-fold and 1500-fold.

Objective To evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) uhrasonographic stratification and 3D contrast-enhanced ultrasonography (3D-CEUS) in identifying malignant lesions from benign ovarian masses.Methods Both of 2D ultrasound (2D-US) and 3D-CEUS were performed on 102 patients with ovarian masses.The perfusion characteristics of ovarian masses were observed with 3D-CEUS,and the 2D-US features of ovarian masses were analyzed based on GI-RADS.Simple and multiple Logistic regression analysis were used to investigate whether the independent risk predictors in differential diagnosis of benign and malignant ovarian could be confirmed.In addition,ROC curves were drawn.The diagnostic efficacy of GI-RADS combined with 3D-CEUS scoring system was evaluated and compared with that of only GI-RADS.Results Simple and multiple Logistic regression analysis confirmed that there were 8 independent predictors of malignant masses,including large papillary projections (≥7 mm),separated or wall thickness ≥3 mm,central blood flow,the proportion of solid part ≥50％,combination of ascites,high level enhancement,uneven distribution of contrast media in enhanced solid part and the vascular with characteristics as dense,tortuous and anfractuous.When using 4 points as the cut-off,the area under the curve (AUC) of GI-RADS combined with 3D-CEUS scoring system in identifying malignant ovarian masses was 0.969,higher than that of only GI-RADS (0.839;Z=1.64,P=0.029).Furthermore,the scoring system showed higher sensitivity,specificity,positive predictive value,negative predictive value and accuracy (all P＜0.001).Conclusion The combination of GI-RADS with 3D-CEUS can be more effective to distinguish malignant lesions from benign ovarian masses.