The aim of this study of patients with chronic kidney disease (CKD) is to assess the safety of daily consumption of walnuts on the physiological levels of phosphorous, potassium, parathyroid hormone (PTH), and fibroblast growth factor 23 (FGF23), and to assess the short-term benefits of this intervention on risk factors associated with cardiovascular events. This led us to perform a prospective, randomized, cross-over, pilot clinical trial examined 13 patients with chronic kidney disease (CKD). Subjects were randomly assigned to a diet of 30 g of walnuts per day or the control diet. After 30 days, each group was given a 30-day washout period, and then switched to the alternate diet for 30 days. Urinary and serum levels of phosphorous and potassium, multiple vascular risk factors, and urinary inositol phosphates (InsPs) were measured at baseline and at the end of the intervention period. Our results showed that the walnut dietary supplement led to reduced blood pressure, LDL cholesterol, and serum albumin, but had no effect on the physiological levels of phosphorous, potassium, PTH, and FGF23. This is the first report to show that daily consumption of walnuts by patients with CKD does not alter their physiological levels of phosphorous, potassium, PTH, and FGF23. Consequently, this dietary supplement may prevent cardiovascular events in patients with CKD.

Objective: To assess the effects of chronic walnut consumption on body weight and adiposity in elderly individuals. Methods: The Walnuts And Healthy Aging study is a dual-center (Barcelona, Spain and Loma Linda University [LLU]), 2-year randomized parallel trial. This report concerns only the LLU cohort. Healthy elders (mean age 69 y, 67% women) were randomly assigned to walnut (n = 183) or control diets (n = 173). Subjects in the walnut group received packaged walnuts (28–56 g/d), equivalent to ≈15% of daily energy requirements, to incorporate into their habitual diet, while those in the control group abstained from walnuts. Adiposity was measured periodically, and data were adjusted for in-trial changes in self-reported physical activity. Results: After 2 years, body weight significantly decreased (P = 0.031), while body fat significantly increased (P = 0.0001). However, no significant differences were observed between the control and walnut groups regarding body weight (−0.6 kg and −0.4 kg, respectively, P = 0.67) or body fat (+0.9% and +1.3%, respectively, P = 0.53). Lean body mass, waist circumference and waist-to-hip ratio remained essentially unchanged. Sensitivity analyses were consistent with the findings of primary analysis. Conclusion: Our findings indicate that walnuts can be incorporated into the daily diet of healthy elders without concern for adverse effects on body weight or body composition.

The purpose of this work was to achieve non-destructive detection of the internal defects of in-shell walnuts using X-ray radiography technology based on improved Faster R-CNN network model. First, the FPN structure was added to the feature extraction layer to extract richer image information. Then ROI Align was used to instead of ROI Pooling for eliminating the localization bias problem caused by quantization operation. Finally, the Softer-NMS module was introduced to the final regression layer with the predicted bounding box for improving the localization accuracy of the candidate boxes. The results indicated that the internal defects in intact walnuts with shells could be identified effectively using the proposed improved network model in this study. Specifically, the discrimination accuracy of the in-shell sound, shriveled and empty-shell walnuts were 96.14%, 91.72% and 94.80% respectively, and the highest overall accuracy can reach 94.22 %. Contrasted with original Faster R-CNN network model, the mAP and F1-value of the improved Faster R-CNN model increased by 5.86% and 5.65%, respectively. Consequently, the proposed method can be applied for the in-shell walnuts with shriveled and empty-shell defects.