Prediction of lymph node metastasis in patients with papillary thyroid cancer based on radiomics analysis and intraoperative frozen section analysis: A retrospective study.

INTRODUCTION: To evaluate the diagnostic efficiency among the clinical model, the radiomics model and the nomogram that combined radiomics features, frozen section (FS) analysis and clinical characteristics for the prediction of lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC). METHODS: A total of 208 patients were randomly divided into two groups randomly with a proportion of 7:3 for the training groups (n = 146) and the validation groups (n = 62). The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for the selection of radiomics features extracted from ultrasound (US) images. Univariate and multivariate logistic analyses were used to select predictors associated with the status of LN. The clinical model, radiomics model and nomogram were subsequently established by logistic regression machine learning. The area under the curve (AUC), sensitivity and specificity were used to evaluate the diagnostic performance of the different models. The Delong test was used to compare the AUC of the three models. RESULTS: Multivariate analysis indicated that age, size group, Adler grade, ACR score and the psammoma body group were independent predictors of lymph node metastasis (LNM). The results showed that in both the training and validation groups, the nomogram showed better performance than the clinical model, albeit not statistically significant (p > .05), and significantly outperformed the radiomics model (p < .05). However, the nomogram exhibits a slight improvement in sensitivity that could reduce the incidence of false negatives. CONCLUSION: We propose that the nomogram holds substantial promise as an effective tool for predicting LNM in patients with PTC.

Ultrasound-assisted complex enzyme extraction, structural characterization, and biological activity of polysaccharides from Ligustrum robustum.

Ligustrum robustum is one of the traditional teas in China with a long history of drinking and medicinal use. Through Response surface optimization, the yield of polysaccharides extracted by ultrasonic-assisted complex enzyme (UAE-EN) method was increased to 14.10 ±â€¯0.56 %. Neutral homogeneous polysaccharide (LRNP) and acidic homogeneous polysaccharide (LRAP-1, LRAP-2, LRAP-3) from L. robustum were purified. The molecular weights of them were 5894, 4256, 4621 and 3915 Da. LRNP was composed of glucose (Glc), galactose (Gal), arabinose (Ara) with molar percentage of 24.97, 42.38 and 30.80. Structure analysis revealed that the backbone of LRNP consisted of 1,5-linked α-Araf, 1,4-linked ß-Galp, 1,6-linked ß-Galp, and 1,4-linked ß-Glcp with the branches of 1,2-linked α-Araf, 1,3-linked α-Araf, 1,3-linked ß-Glcp and 1,6-linked ß-Galp residues, some terminal residues of α-Araf, ß-Glcp and α-Galp were also included. In vitro experiments showed that the four polysaccharides possessed excellent antioxidant, antitumor and hypoglycemic activities. LRNP possessed the protective effect against oxidative stress. The studies provide a basis for further exploitation of L. robustum.