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Background and objectives Intradialytic hypotension has high clinical significance. However, predicting it using conventional statistical models may be difficult because several factors have interactive and complex effects on the risk. Herein, we applied a deep learning model (recurrent neural network) to predict the risk of intradialytic hypotension using a timestamp-bearing dataset. Design, setting, participants, & measurements We obtained 261,647 hemodialysis sessions with 1,600,531 independent timestamps (i.e., time-varying vital signs) and randomly divided them into training (70%), validation (5%), calibration (5%), and testing (20%) sets. Intradialytic hypotension was defined when nadir systolic BP was Results The recurrent neural network model for predicting intradialytic hypotension 1 achieved an area under the receiver operating characteristic curve of 0.94 (95% confidence intervals, 0.94 to 0.94), which was higher than those obtained using the other models (P Conclusions Our deep learning model can be used to predict the real-time risk of intradialytic hypotension.

Cheese contains various beneficial nutrients, including calcium and whey protein, as well as large amounts of saturated fatty acids. Thus, intake of cheese increases the production of low‐density lipoprotein‐cholesterol (LDL‐C), a well‐defined risk factor for cardiovascular disease. Therefore, identification of natural products that inhibit LDL‐C production following cheese intake and verification of the efficacy of such products in animal models are essential. Here, we evaluated the effects of Allium hookeri, a well‐known traditional herbal remedy, on metabolism and thermogenesis in mice consuming a cheese‐containing diet. Intake of A. hookeri extracts significantly blocked increases in body weight and fat mass caused by intake of Gouda cheese in mice. Additionally, increases in blood triglyceride levels following intake of Gouda cheese were alleviated by A. hookeri. Moreover, intake of Gouda cheese enhanced thermogenesis efficiency. Thus, A. hookeri may have applications as an important additive for reducing the risk of metabolic disease resulting from cheese consumption.

Bifidobacterium longum KACC 91563 secretes family 5 extracellular solute-binding protein via extracellular vesicle. In our previous work, it was demonstrated that the protein effectively alleviated food allergy symptoms via mast cell specific apoptosis, and it has revealed a therapeutic potential of this protein in allergy treatment. In the present study, we cloned the gene encoding extracellular solute-binding protein of the strain into the histidine-tagged pET-28a(+) vector and transformed the resulting plasmid into the Escherichia coli strain BL21 (DE3). The histidine-tagged extracellular solute-binding protein expressed in the transformed cells was purified using Ni-NTA affinity column. To enhance the efficiency of the protein purification, three parameters were optimized; the host bacterial strain, the culturing and induction temperature, and the purification protocol. After the process, two liters of transformed culture produced 7.15 mg of the recombinant proteins. This is the first study describing the production of extracellular solute-binding protein of probiotic bacteria. Establishment of large-scale production strategy for the protein will further contribute to the development of functional foods and potential alternative treatments for allergies.