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Nutritional, structural and functional properties of proteins from tiger nut seed meal (TNPF) were investigated in this study. Four kinds of TNPF, albumin (ALB), globulin (GLO), glutelin (GLU), and prolamin (PRO) were obtained through Osborne extraction method, comprising 42.37%, 6.23%, 31.25%, and 5.10% of the total TNPF, respectively. The ratios of essential amino acids to total amino acids in ALB, GLO, GLU and PRO were 43.60%, 38.29%, 42.39%, and 42.82%, respectively. Our results revealed that GLO exhibited the highest in vitro protein digestibility (86.51%), followed by ALB (81.68%), PRO (75.73%), and GLU (60.52%). Further, the analysis of Fourier transform infrared spectroscopy, intrinsic fluorescence spectra, and surface hydrophobicity indicated that the secondary structure and ternary conformation of the four kinds of TNPF were significantly different. Moreover, four kinds of TNPF exhibited their highest solubility, foaming capacity and emulsifying stability under alkaline condition (pH = 12.0) and the lowest near the isoelectric points. Additionally, GLU exhibited the highest foaming ability, emulsification property, and water/oil holding capacity, while ALB showed the highest thermal stability. These findings suggested that GLU extracted from tiger nut seed meal demonstrated excellent nutritional and functional properties, making it a promising food additive to enhance food quality.

Background Vertebral Hounsfield unit (HU) were regarded as a new way to predict fragility fracture. However, HU values were measured in a single plane, which is not accurate for the entire vertebral body. This study aimed to create a new CT-based metric for assessing bone mineral density, three-dimensional Hounsfield unit value (3D-HU), and to evaluate its effect in independently predicting new vertebral fracture (NVF) after percutaneous vertebral augmentation (PVA) in postmenopausal women. Methods This study reviewed female patients with osteoporotic vertebral compression fracture (OVCF) who were treated at our hospital. Patients were divided into NVF and control groups according to whether they had NVF. 3D-HU of the L1-4 vertebrae was measured using preoperative computed tomography (CT) scanning of the lumbar spine. Demographics, procedure-related data, and radiological data were collected. Pearson correlation test was used to determine the correlation between 3D-HU and BMD T-score. The independent risk factors of NVF were determined by multivariate logistic regression analyses. Receiver operating characteristic curve (ROC) was used to evaluate the predictive performance of 3D-HU. Results This study involved 349 postmenopausal women who were treated with PVA between January 2017 and August 2022. Among them, 61 people suffered the NVF following PVA. The mean 3D-HU was 40.64 ± 22.43 in the NVF group and 79.93 ± 25.69 in the without NVF group ( p  < 0.001). Multivariate analysis showed that lower 3D-HU (OR = 0.927; 95%CI = 0.906–0.945; p  < 0.001) was the only independent predictor of NVF following PVA. The predictive accuracy of 3D-HU was 87.7%, which was higher than that of the HU value (82.3%), and it was highly positively correlated with BMD T-score ( r  = 0.628, p  < 0.001). Conclusions Lower 3D-HU was significantly associated with NVF following PVA in postmenopausal women. In addition, vertebral 3D-HU had better predictive power than HU values. 3D-HU assessment prior to PVA may provide insight into a patient’ s risk for NVF.

Vertebral Hounsfield unit (HU) were regarded as a new way to predict fragility fracture. However, HU values were measured in a single plane, which is not accurate for the entire vertebral body. This study aimed to create a new CT-based metric for assessing bone mineral density, three-dimensional Hounsfield unit value (3D-HU), and to evaluate its effect in independently predicting new vertebral fracture (NVF) after percutaneous vertebral augmentation (PVA) in postmenopausal women. This study reviewed female patients with osteoporotic vertebral compression fracture (OVCF) who were treated at our hospital. Patients were divided into NVF and control groups according to whether they had NVF. 3D-HU of the L1-4 vertebrae was measured using preoperative computed tomography (CT) scanning of the lumbar spine. Demographics, procedure-related data, and radiological data were collected. Pearson correlation test was used to determine the correlation between 3D-HU and BMD T-score. The independent risk factors of NVF were determined by multivariate logistic regression analyses. Receiver operating characteristic curve (ROC) was used to evaluate the predictive performance of 3D-HU. This study involved 349 postmenopausal women who were treated with PVA between January 2017 and August 2022. Among them, 61 people suffered the NVF following PVA. The mean 3D-HU was 40.64 ± 22.43 in the NVF group and 79.93 ± 25.69 in the without NVF group (p < 0.001). Multivariate analysis showed that lower 3D-HU (OR = 0.927; 95%CI = 0.906-0.945; p < 0.001) was the only independent predictor of NVF following PVA. The predictive accuracy of 3D-HU was 87.7%, which was higher than that of the HU value (82.3%), and it was highly positively correlated with BMD T-score (r = 0.628, p < 0.001). Lower 3D-HU was significantly associated with NVF following PVA in postmenopausal women. In addition, vertebral 3D-HU had better predictive power than HU values. 3D-HU assessment prior to PVA may provide insight into a patient' s risk for NVF.