Integrated Metabolomics and Metagenomics Unveiled Biomarkers of Antioxidant Potential in Fermented Brewer's Grains.

About one-third of the global food supply is wasted. Brewers' spent grain (BSG), being produced in enormous amounts by the brewery industry, possesses an eminence nutritional profile, yet its recycling is often neglected for multiple reasons. We employed integrated metagenomics and metabolomics techniques to assess the effects of enzyme treatments and Lactobacillus fermentation on the antioxidant capacity of BSG. The biotreated BSG revealed improved antioxidant capability, as evidenced by significantly increased (p < 0.05) radical scavenging activity and flavonoid and polyphenol content. Untargeted metabolomics revealed that Lactobacillus fermentation led to the prominent synthesis (p < 0.05) of 15 novel antioxidant peptides, as well as significantly higher (p < 0.05) enrichment of isoflavonoid and phenylpropanoid biosynthesis pathways. The correlation analysis demonstrated that Lactiplantibacillus plantarum exhibited strong correlation (p < 0.05) with aucubin and carbohydrate-active enzymes, namely, glycoside hydrolases 25, glycosyl transferases 5, and carbohydrate esterases 9. The fermented BSG has potential applications in the food industry as a culture medium, a functional food component for human consumption, and a bioactive feed ingredient for animals.

Progress of Research into Preformed Particle Gels for Profile Control and Water Shutoff Techniques.

Gel treatment is an economical and efficient method of controlling excessive water production. The gelation of in situ gels is prone to being affected by the dilution of formation water, chromatographic during the transportation process, and thus controlling the gelation time and penetration depth is a challenging task. Therefore, a novel gel system termed preformed particle gels (PPGs) has been developed to overcome the drawbacks of in situ gels. PPGs are superabsorbent polymer gels which can swell but not dissolve in brines. Typically, PPGs are a granular gels formed based on the crosslinking of polyacrylamide, characterized by controllable particle size and strength. This work summarizes the application scenarios of PPGs and elucidates their plugging mechanisms. Additionally, several newly developed PPG systems such as high-temperature-resistant PPGs, re-crosslinkable PPGs, and delayed-swelling PPGs are also covered. This research indicates that PPGs can selectively block the formation of fractures or high-permeability channels. The performance of the novel modified PPGs was superior to in situ gels in harsh environments. Lastly, we outlined recommended improvements for the novel PPGs and suggested future research directions.

π-Diamond: A Diamondoid Superstructure Driven by π-Interactions.

Modulating the arrangement of superstructures through noncovalent interactions has a significant impact on macroscopic shape and the expression of unique properties. Constructing π-interaction-driven hierarchical three-dimensional (3D) superstructures poses challenges on account of limited directional control and weak intermolecular interactions. Here we report the construction of a 3D diamondoid superstructure, named π-Diamond, employing a ditopic strained Z-shaped building block comprising a porphyrin unit as bow-limb double-strapped with two m-xylylene units as bowstrings. This superstructure, reminiscent of diamond's tetrahedral carbon composition, is composed of double-walled tetrahedron (DWT) driven solely by π-interactions. Hetero-π-stacking interactions between porphyrin and m-xylylene panels drive the assembly of four building blocks predominantly into a DWT, which undergoes extension to create an adamantane unit and eventually a diamondoid superstructure wherein each porphyrin panel is shared by two neighboring tetrahedra through hetero-π-stacking. π-Diamond exhibits a solid-state fluorescent quantum yield 44 times higher than that of tetraphenylporphyrin along with excellent photocatalytic performance. The precise 3D directionality of π-interactions, achieved through strained multipanel building blocks, revolutionizes the assembly of hierarchical 3D superstructures driven by π-interactions.

Tough and Water-Resistant Bioelastomers with Active-Controllable Degradation Rates.

Biodegradable electronic devices have gained significant traction in modern medical applications. These devices are generally desired to have a long enough working lifetime for stable operation and allow for active control over their degradation rates after usage. However, current biodegradable materials used as encapsulations or substrates for these devices are challenging to meet the two requirements due to the constraints of inadequate water resistance, poor mechanical properties, and passive degradation characteristics. Herein, we develop a novel biodegradable elastomer named POC-SS-Res by introducing disulfide linkage and resveratrol (Res) into poly(1,8-octanediol-co-citrate) (POC). Compared to POC, POC-SS-Res exhibits good water resistance and excellent mechanical properties in PBS, providing effective protection for devices. At the same time, POC-SS-Res offers the unique advantage of an active-controllable degradation rate, and its degradation products express low biotoxicity. Good biocompatibility of POC-SS-Res is also demonstrated. Bioelectronic components encapsulated with POC-SS-Res have an obvious prolongation of working lifetime in PBS compared to that encapsulated with POC, and its degradation rate can be actively controlled by the addition of glutathione (GSH).

Viscosity of Ionic Liquids: Theories and Models.

Ionic liquids (ILs) offer a wide range of promising applications due to their unique and designable properties compared to conventional solvents. Further development and application of ILs require correlating/predicting their pressure-viscosity-temperature behavior. In this review, we firstly introduce methods for calculation of thermodynamic inputs of viscosity models. Next, we introduce theories, theoretical and semi-empirical models coupling various theories with EoSs or activity coefficient models, and empirical and phenomenological models for viscosity of pure ILs and IL-related mixtures. Our modelling description is followed immediately by model application and performance. Then, we propose simple predictive equations for viscosity of IL-related mixtures and systematically compare performances of the above-mentioned theories and models. In concluding remarks, we recommend robust predictive models for viscosity at atmospheric pressure as well as proper and consistent theories and models for P-η-T behavior. The work that still remains to be done to obtain the desired theories and models for viscosity of ILs and IL-related mixtures is also presented. The present review is structured from pure ILs to IL-related mixtures and aims to summarize and quantitatively discuss the recent advances in theoretical and empirical modelling of viscosity of ILs and IL-related mixtures.

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection.

OBJECTIVE: To establish a risk assessment model to predict postoperative National Pressure Injury Advisory Panel stage 2 or higher pressure injury (PI) risk in patients undergoing acute type A aortic dissection surgery. METHODS: This retrospective assessment included consecutive patients undergoing acute type A aortic dissection surgery in the authors' hospital from September 2017 to June 2021. The authors used LASSO (logistic least absolute shrinkage and selection operator) regression analysis to identify the most relevant variables associated with PI by running cyclic coordinate descent with 10-times cross-validation. The variables selected by LASSO regression analysis were subjected to multivariate logistic analysis. A calibration plot, receiver operating characteristic curve, and decision curve analysis were used to validate the model. RESULTS: There were 469 patients in the study, including 94 (27.5%) with postoperative PI. Ten variables were selected from LASSO regression: body mass index, diabetes, Marfan syndrome, stroke, preoperative skin moisture, hemoglobin, albumin, serum creatinine, platelet, and d-dimer. Four risk factors emerged after multivariate logistic regression: Marfan syndrome, preoperative skin moisture, albumin, and serum creatinine. The area under the receiver operating characteristic curve of the model was 0.765. The calibration plot and the decision curve analysis both suggested that the model was suitable for predicting postoperative PI. CONCLUSIONS: This study built an efficient predictive model that could help identify high-risk patients.