Tree peony seed oil alleviates hyperlipidemia and hyperglycemia by modulating gut microbiota and metabolites in high-fat diet mice.

With the changes of people's lifestyle, hyperlipidemia and hyperglycemia which were induced from a diet high in both fat and sugar have become serious health concerns. Tree peony seed oil (PSO) is a novel kind of edible oil that shows great potential in the food industry because of its high constituent of unsaturated fatty acids. Based 16S rRNA and gut untargeted metabolomics, this study elucidated that the mechanism of PSO regulating blood glucose (Glu) and lipids. The impact of PSO on gut microbiota balance and gut metabolites of mice with a high-fat diet (HFD) was evaluated. The findings indicated that PSO decreased HFD mice's body weight and fat accumulation, ameliorating the levels of blood lipid, reduced liver fat vacuole levels. What's more PSO modulated the proportion of gut microbiota in HFD mice and enhanced the abundance of probiotics. Furthermore, untargeted metabolomic analysis revealed that PSO not only impacted the generation of short-chain fatty acids (SCFAs) by gut microorganism and altered metabolic pathway but exerted influence on secondary bile acids (BA), amino acid metabolism, and various other metabolites. These results suggested that PSO has the potential function for mitigating HFD-induced hyperlipidemia and hyperglycemia by regulating gut microbiota and host metabolism.

Quality Evaluation of Asparagus officinalis by Profile of Amino Acids and Mineral Elements in Different Parts Combined with Chemometrics Methods.

Asparagus officinalis has a homologous value in medicine and vegetables. Its immature stem, commonly called asparagus, is a central edible part. Asparagus skin and leaf also contain rich nutrients. However, these parts are often discarded. This study investigated amino acid and mineral elements in immature stem, skinless asparagus, asparagus skin, and leaf. Their quality was further evaluated by chemometrics methods such as principal component analysis and neural network analysis. The results showed amino acid content was high in immature stem and skinless asparagus and low in leaf, whereas the mineral elements were in four parts. Quality evaluation results showed four parts were divided into three grades. Immature stem and skinless asparagus were grouped into cluster 1 with the best quality as high-quality raw materials in food and health-care products. Meanwhile, three AA (Cys, His, Arg) and two mineral elements (Na, Cr) were identified as quality evaluation iconic substances.

Characterization of Agronomic and Seed Oil Features for Different Cultivars of Tree Peony.

Tree peony is a unique oil plant resource in China, and tree peony seed oil is one of the healthy edible oils with a very promising future. However, the main oil tree peony cultivars promoted in China are Paeonia ostii 'Fengdan' and Paeonia rockii. In order to explore new oil tree peony cultivars, 68 tree peony cultivars were investigated and cultivars with oil potential were selected by cluster analysis and grey relational analysis (GRA) in this study. The results demonstrated that the 68 cultivars varied significantly in terms of agronomic characteristics (p < 0.05), with the coefficient of variation in seed yield per plant reaching a high of 75.36%. The oil content of 46 cultivars was higher than 'Fengdan' (20.87 ± 0.26%) and 'Zibanbai' (21.24 ± 1.01%), while the alpha-linolenic acids and total unsaturated fatty acid contents of 26 cultivars were higher than 'Fengdan' (39.79 ± 1.13% and 88.99 ± 0.47%) and 'Zibanbai' (40.51 ± 0.09% and 93.59 ± 0.09%). Finally, three cultivars with better integrated traits were selected by cluster analysis and grey relational analysis (GRA), comprising of 'Changshoule', 'Xianchizhenghui', and 'Yupantuojin'. The contents of alpha-linolenic acids and total unsaturated fatty acids in 'Changshoule' (47.98 ± 0.17% and 93.60 ± 0.08%), 'Xianchizhenghui' (49.44 ± 0.63% and 93.80 ± 0.06%), and 'Yupantuojin' (40.46 ± 0.26% and 93.58 ± 0.06%) were higher than that of 'Fengdan' (39.79 ± 1.13% and 88.99 ± 0.47%). In general, these cultivars can be used as hybrid parental materials for breeding new excellent oil tree peony cultivars.

Microfluidic Biosensor Integrated with Signal Transduction and Enhancement Mechanism for Ultrasensitive Noncompetitive Assay of Multiple Mycotoxins.

To achieve high-throughput ultrasensitive detection of mycotoxins in food, a functional DNA-guided transition-state CRISPR/Cas12a microfluidic biosensor (named FTMB) was successfully constructed. The signal transduction CRISPR/Cas12a strategy in FTMB has utilized DNA sequences with a specific recognition function and activators to form trigger switches. Meanwhile, the transition-state CRISPR/Cas12a system was constructed by adjusting the composition ratio of crRNA and activator to achieve a high response for low concentrations of target mycotoxins. On the other hand, the signal enhancement of FTMB has efficiently integrated the signal output of quantum dots (QDs) with the fluorescence enhancement effect of photonic crystals (PCs). The construction of universal QDs for the CRISPR/Cas12a system and PC films matching the photonic bandgap produced a significant signal enhancement by a factor of 45.6. Overall, FTMB exhibited a wide analytic range (10-5-101 ng·mL-1), low detection of limit (fg·mL-1), short detection period (∼40 min), high specificity, good precision (coefficients of variation <5%), and satisfactory practical sample analysis capacity (the consistency with HPLC at 88.76%-109.99%). It would provide a new and reliable solution for the rapid detection of multiple small molecules in the fields of clinical diagnosis and food safety.

Dictionary learning LASSO for feature selection with application to hepatocellular carcinoma grading using contrast enhanced magnetic resonance imaging.

Introduction: The successful use of machine learning (ML) for medical diagnostic purposes has prompted myriad applications in cancer image analysis. Particularly for hepatocellular carcinoma (HCC) grading, there has been a surge of interest in ML-based selection of the discriminative features from high-dimensional magnetic resonance imaging (MRI) radiomics data. As one of the most commonly used ML-based selection methods, the least absolute shrinkage and selection operator (LASSO) has high discriminative power of the essential feature based on linear representation between input features and output labels. However, most LASSO methods directly explore the original training data rather than effectively exploiting the most informative features of radiomics data for HCC grading. To overcome this limitation, this study marks the first attempt to propose a feature selection method based on LASSO with dictionary learning, where a dictionary is learned from the training features, using the Fisher ratio to maximize the discriminative information in the feature. Methods: This study proposes a LASSO method with dictionary learning to ensure the accuracy and discrimination of feature selection. Specifically, based on the Fisher ratio score, each radiomic feature is classified into two groups: the high-information and the low-information group. Then, a dictionary is learned through an optimal mapping matrix to enhance the high-information part and suppress the low discriminative information for the task of HCC grading. Finally, we select the most discrimination features according to the LASSO coefficients based on the learned dictionary. Results and discussion: The experimental results based on two classifiers (KNN and SVM) showed that the proposed method yielded accuracy gains, compared favorably with another 5 state-of-the-practice feature selection methods.

Rapid quantitative detection of Vibrio parahaemolyticus via high-fidelity target-based microfluidic identification.

With the rapid development of logistics, a growing number of pathogenic microorganisms has the means to spread worldwide using food as a carrier; thus, there is an urgent need to develop effective detection strategies to ensure food safety. By combining novel markers identified by pan-genome analysis and a digital recombinase-aided amplification (RAA) detection method based on a microfluidic chip, a strategy of high-fidelity target-based microfluidic identification (HFTMI) has been developed. Herein, a proof-of-concept study of HFTMI for rapid pathogen detection of V. parahaemolyticus was investigated. Specific primers designed for the gene group_41170 identified in the pan-genome analysis showed high sensitivity and a broad spectrum for the detection of V. parahaemolyticus. Different power systems were investigated to increase the partition rate on specifically designed chamber-based digital chips. The performance of HFTMI was greatly improved compared with qPCR. Collectively, this novel HFTMI system provides more reliable guidance for food safety testing.

Multianticipation for string stable Adaptive Cruise Control and increased motorway capacity without vehicle-to-vehicle communication.

Adaptive Cruise Control (ACC) systems have been expected to solve many problems of motorway traffic. Now that they are widespread, it is observed that the majority of existing systems are string unstable. Therefore, small perturbations in the speed profile of a vehicle are amplified for the vehicles following upstream, with negative impacts on traffic flow, fuel consumption, and safety. Increased headway settings provide more stable flow but at the same time it deteriorates the capacity. Substantial research has been carried out in the past decade on utilizing connectivity to overcome this trade-off. However, such connectivity solutions have to overcome several obstacles before deployment and there is the concrete risk that motorway traffic flow will considerably deteriorate in the meanwhile. As an alternative solution, the paper explores multianticipation without inter-vehicle communication, taking advantage of the recent advancements in the field of RADAR sensing. An analytical study is carried out, based on the most widely used model and parameter settings used to simulate currently available commercial ACC systems, comparing the transfer functions and step responses for the nominal and the multianticipative formulations. Then, a microsimulation framework is employed to validate our claim on different speed profiles. Analytical results demonstrate that multianticipation enhances stability without impacting traffic flow. On the contrary, the simulation study indicates that the multianticipative-ACC can produce higher road capacity even in the presence of external disturbances and for a wide range of calibrated parameters. Finally, optimality conditions for the tuning of the headway policy are derived from a Pareto optimization.

Postharvest quality maintenance of wax apple and guava fruits by use of a fermented broth of an ε-poly-l-lysine-producing Streptomyces strain.

ε-Poly-l-lysine (ε-PL) is a natural antimicrobial polymer with significant inhibitory activity against a broad spectrum of microorganisms, and nowadays used widely as a preservative in the food industry. In the present study, ε-PL broth was obtained from Streptomyces ahygroscopicus GIM8 fermentation in a nutrient-limited liquid medium. The in vitro antifungal activity of the broth against fruit pathogens Penicillium expansum and Colletotrichum gloeosporioides was investigated, and its usage for postharvest storage of two highly perishable fruits wax apple and guava was evaluated. Results showed that ε-PL concentration in the broth reached 0.61 g/L, and the nutrition level of the broth was low. The antifungal activity of ε-PL broth was comparable to that of the aqueous solution of ε-PL under the same concentration. Immersion with the diluted broth (200 mg/L ε-PL) markedly delayed the decline in the quality of postharvest wax apple and guava fruits during storage, and the decay incidences were also greatly decreased as compared to their respective controls (distilled water immersion). A further investigation demonstrated that the ε-PL broth immersion induced an increase in the activity of defense-related enzymes peroxidase and polyphenol oxidase in the two fruits during storage. The present study proved that the fermentation broth of ε-PL could be used as a promising alternative to high purity ε-PL and synthetic fungicides for preserving fruits at postharvest stage.

Identification of the Potential Biological Preservative Tetramycin A-Producing Strain and Enhancing Its Production.

The aim of this study was to develop a potential microbial preservative to prevent the growth of fungi in food. The isolate ZC-G-5 showed strong antifungal activity against food spoilage fungi and Streptomyces albulus was identified on the basis of morphologic, culture, and 16S rDNA sequence analyses. The active metabolite was elucidated as tetramycin A (TMA) through spectroscopic techniques, including HR-ESI-MS, 1D-NMR, and 2D-NMR. An antifungal activity assay revealed that the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) of TMA were 1.50-2.50 and 3.00-5.00 µg/ml, respectively. In situ antifungal activity analyses demonstrated that 90.0 µg/ml of TMA could inhibit the growth of fungi for over 14 days. In order to enhance TMA production, the high-yield mutant strain YB101 was screened, based on the isolate ZC-G-5, using a high-throughput screening method. The best metabolic precursor was selected during fermentation, when the concentration of glycerol was 8% (v/v) in Gauze's broth medium to cultivate the mutant strain YB101; the concentration of TMA could be increased to 960.0 µg/ml, compared with the original isolate ZC-G-5, where the concentration of the TMA was only 225.0 µg/ml. Our study may contribute to the application of S. albulus and its active metabolite as a potential bio-preservative in the food industry.