Crystallization behavior and IR structure of yttrium aluminosilicate glasses

The crystallization of four Y2O3-Al2O3-SiO2 (YAS) glasses were investigated to prepare YAS glass ceramics precipitated singly/mainly Y2Si2O7 or Y4.67(SiO4)3O apatite, and to explore the crystallization difference between the stoichiometric parent glass (SPG) and non-stoichiometric parent glass (NSPG). The DSC results revealed that glass locating at the higher liquidus surface temperature has lower crystallization peak temperature, which indicating that the corresponding glass has higher crystallization potential to crystallize easily. Crystallization of the NSPG samples is along surface and caused by phase separation, while SPG sample is the surface crystallization at the first exothermic peak temperature and overall crystallization at the second exothermic peak temperature. Glass ceramics only containing y-Y2Si2O7 or Y4.67(SiO4)3O apatite are obtained successfully, and which are illustrated by fitting FTIR spectra. These results can provide technical guide for controlling the crystallization process and the types of precipitated crystals in YAS glass for different application potentials

Novel model based on ultrasound predict axillary lymph node metastasis in breast cancer

Abstract Background Whether there is axillary lymph node metastasis is crucial for formulating the treatment plan for breast cancer. Currently, invasive methods are still used for preoperative evaluation of lymph nodes. If non-invasive preoperative evaluation can be achieved, it will effectively improve the treatment plan. Objective Constructed a predict model based on ultrasound examination, which forest axillary lymph node metastasis in breast cancer, and validated this model. Method Patients admitted to Xiamen First Hospital from April 2018 to August 2021 with complete case data were included in this study. Patients who had undergone breast cancer resection and axillary lymph node dissection or sentinel lymph node biopsy were divided into a training and validation cohort in a 7:3 ratio. In the training cohort, patients were divided into metastatic and non-metastatic groups based on whether axillary lymph nodes had metastasis. The parameters of the two groups were compared, and statistically significant parameters were included in multivariate analysis. Then, a Nomogram model was constructed, named Lymph metastasis predict model (LMPM). Calibration curves, receiver operating curve (ROC), and decision curve analysis (DCA) were plotted between the training and validation cohort, calculate the risk score of each patient, identify the optimal cutoff value, and test the predictive efficacy of LMPM. Result Two hundred seventy-three patients were enrolled in final study, the average age 49.7 ± 8.7, training cohort included 191 patients, the diameter of breast cancer, the lymph node peak systolic flow velocity (LNPS) and the cortex area hilum ratio (CH) of lymph node were exist significant difference in metastatic and non-metastatic group. Multivariate analysis showed cancer diameter, LNPS and CH included in LMPM, the cutoff value was 95, the calibration curve, ROC, DCA in training and validation cohort show satisfactory result. Conclusion The predict model-LMPM, can predict axillary lymph node metastasis in breast cancer, which is useful for developing personalized treatment plans. However, further validation of the model is required by incorporating a larger number of patients