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Chinese jujube (Ziziphus jujuba Mill.), an economically significant species in the Rhamnaceae family, is a popular fruit tree in Asia. The sugar and acid concentrations in jujube are considerably higher than those in other plants. Due to the low kernel rate, it is extremely difficult to establish hybrid populations. Little is known about jujube evolution and domestication, particularly with regard to the role of the sugar and acid components of jujube. Therefore, we used cover net control as a hybridization technique for the cross-breeding of Ziziphus jujuba Mill and ‘JMS2’ and (Z. acido jujuba) ‘Xing16’ to obtain an F1 population (179 hybrid progeny). The sugar and acid levels in the F1 and parent fruit were determined by HPLC. The coefficient of variation ranged from 28.4 to 93.9%. The sucrose and quinic acid levels in the progeny were higher than those in the parents. The population showed continuous distributions with transgressive segregation on both sides. Analysis by the mixed major gene and polygene inheritance model was performed. It was found that glucose is controlled by one additive-dominant major gene and polygenes, malic acid is controlled by two additive-dominant major genes and polygenes, and oxalic acid and quinic acid are controlled by two additive-dominant-epistatic major genes and polygenes. The results of this study provide insights into the genetic predisposition and molecular mechanisms underlying the role of sugar acids in jujube fruit.

Limited data are published regarding changes in the physicochemical properties of rice flours from germinated de-hulled rice treated by ultrasound. This work was undertaken to evaluate the effect of ultrasound treatment (25 kHz, 16 W/L, 5 min) on starch hydrolysis and functional properties of rice flours produced from ultrasound-treated red rice and brown rice germinated for up to 36 h. Environmental Scanning Electron Microscopy (ESEM) microimages showed that the ultrasound treatment altered the surface microstructure of rice, which helped to improve moisture transfer during steam-cooking. The flours from sonicated germinated de-hulled rice exhibited significantly ( p  < .05) enhanced starch hydrolysis, increased the glucose content, and decreased falling number values and viscosities determined by a Rapid Visco Analyzer. The amylase activity of the germinating red rice and brown rice displayed different sensitivity to ultrasonic treatment. The ultrasonic pre-treatment resulted in a significant reduction in energy use during germination with a potential to further reduce energy use in germinated rice cooking process. The present study indicated that ultrasound could be a low-power consumption method to modify the rheological behavior of germinated rice flour, as well as an efficient approach to improve the texture, flavor, and nutrient properties of steam-cooked germinated rice. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate a radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma (GA)., Methods: This retrospective study enrolled 592 patients with clinicopathologically confirmed GA (low-grade: n=154; high-grade: n=438) from January 2008 to March 2018 who were divided into training (n=450) and validation (n=142) sets according to the time of computed tomography (CT) examination. Radiomic features were extracted from the portal venous phase CT images. The Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) regression model were used for feature selection, data dimension reduction and radiomics signature construction. Multivariable logistic regression analysis was applied to develop the prediction model. The radiomics signature and independent clinicopathologic risk factors were incorporated and presented as a radiomics nomogram. The performance of the nomogram was assessed with respect to its calibration and discrimination., Results: A radiomics signature containing 12 selected features was significantly associated with the histologic grade of GA (P<0.001 for both training and validation sets). A nomogram including the radiomics signature and tumor location as predictors was developed. The model showed both good calibration and good discrimination, in which C-index in the training set, 0.752 [95% confidence interval (95% CI): 0.701-0.803]; C-index in the validation set, 0.793 (95% CI: 0.711-0.874)., Conclusions: This study developed a radiomics nomogram that incorporates tumor location and radiomics signatures, which can be useful in facilitating preoperative individualized prediction of histologic grade of GA., (Copyright © 2021 Chinese Journal of Cancer Research. All rights reserved.)

Objective: To develop and validate a computed tomography (CT)-based radiomics nomogram for predicting human epidermal growth factor receptor 2 (HER2) status in patients with gastric cancer., Methods: This retrospective study included 134 patients with gastric cancer (HER2-negative: n=87; HER2-positive: n=47) from April 2013 to March 2018, who were then randomly divided into training (n=94) and validation (n=40) cohorts. Radiomics features were obtained from the CT images showing gastric cancer. Least absolute shrinkage and selection operator (LASSO) regression analysis was utilized for building the radiomics signature. A multivariable logistic regression method was applied to develop a prediction model incorporating the radiomics signature and independent clinicopathologic risk predictors, which were then visualized as a radiomics nomogram. The predictive performance of the nomogram was assessed in the training and validation cohorts., Results: The radiomics signature was significantly associated with HER2 status in both training (P<0.001) and validation (P=0.023) cohorts. The prediction model that incorporated the radiomics signature and carcinoembryonic antigen (CEA) level demonstrated good discriminative performance for HER2 status prediction, with an area under the curve (AUC) of 0.799 [95% confidence interval (95% CI): 0.704-0.894] in the training cohort and 0.771 (95% CI: 0.607-0.934) in the validation cohort. The calibration curve of the radiomics nomogram also showed good calibration. Decision curve analysis showed that the radiomics nomogram was useful., Conclusions: We built and validated a radiomics nomogram with good performance for HER2 status prediction in gastric cancer. This radiomics nomogram could serve as a non-invasive tool to predict HER2 status and guide clinical treatment., (Copyright © 2020 Chinese Journal of Cancer Research. All rights reserved.)