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The organic acids and microbial community structure of fermented grains in the dominant stacking fermentation rounds for sauce-flavor Baijiu production (i.e., the 2nd and 3rd rounds corresponding to the 3rd and 4th rounds of base liquor) were analyzed using high-performance liquid chromatography (HPLC) and high-throughput sequencing, and the interaction between them was investigated. The results revealed that lactic acid, acetic acid, and succinic acid were the primary organic acids present in fermented grains at mean values of 32.70, 4.87 and 1.93 mg/g, respectively. In total, 8 dominant bacterial genera and 7 dominant fungal genera (average relative abundance > 1%) were identified across the two fermentation rounds. The dominant bacterial genera were Virgibacillus, Kroppenstedtia and Bacillus. The dominant fungal genera were Monascus, Thermomyces and Thermoascus. Principal coordinate analysis (PCoA) revealed that there was a significant difference in the structure of bacteria community between the second and third rounds of stacking fermentation, while the difference in the structure of fungal community was not significant. Co-occurrence network analysis showed that the bacterial-fungal (55.60%), bacterial-bacterial (50.57%), and fungal-fungal (91.67%) networks were mainly positively correlated, and there were more unknown interactions between bacterial communities. Mantel test analysis showed a significantly positive correlation between acidity and bacterial community structure (P < 0.01), and succinic acid was highly correlated with both bacterial and fungal community succession (P < 0.01). Spearman’s correlation analysis revealed that the bacterial community had a more significant correlation with organic acids than the fungal community, while the fungal community showed a negative correlation with most organic acids. Nine organic acids citric acid were positively correlated with Oceanobacillus, Bacillus, and Sphingobacterium but negatively correlated with Thermoactinomyces. The results of this study can provide a theoretical basis for the production of high-quality sauce-flavor Baijiu.

Identification of the core functional microorganisms in food fermentations is necessary to understand the ecological and functional processes for making those foods. Wheat qu, which provides liquefaction and saccharifying power, and affects the flavor quality, is a key ingredient in ancient alcoholic huangjiu fermentation, while core microbiota of them still remains indistinct. In this study, metagenomics, metabolomics, microbial isolation and co-fermentation were used to investigate huangjiu. Although Aspergillus is usually regarded as core microorganism in wheat qu to initiate huangjiu fermentations, our metagenomic analysis showed that bacteria Saccharopolyspora are predominant in wheat qu and responsible for breakdown of starch and cellulose. Metabolic network and correlation analysis showed that Saccharopolyspora rectivirgula, Saccharopolyspora erythraea, and Saccharopolyspora hirsuta made the greatest contributions to huangjius metabolites, consisting of alcohols (phenylethanol, isoamylol and isobutanol), esters, amino acids (Pro, Arg, Glu and Ala) and organic acids (lactate, tartrate, acetate and citrate). S. hirsuta J2 isolated from wheat qu had the highest amylase, glucoamylase and protease activities. Co-fermentations of S. hirsuta J2 with S. cerevisiae HJ resulted in a higher fermentation rate and alcohol content, and huangjiu flavors were more similar to that of traditional huangjiu compared to co-fermentations of Aspergillus or Lactiplantibacillus with S. cerevisiae HJ. Genome of S. hirsuta J2 contained genes encoding biogenic amine degradation enzymes. By S. hirsuta J2 inoculation, biogenic amine content was reduced by 45%, 43% and 62% in huangjiu, sausage and soy sauce, respectively. These findings show the utility of Saccharopolyspora as a key functional organism in fermented food products.

To optimize the performance of the soft actuator, numerical simulation and regression analysis of the multi-structure parameter are presented based on the numerical calculation method. Firstly, numerical simulation and regression analysis were performed on the parameters of different driving channel shapes, including equilateral triangle, square, regular pentagon, regular hexagon, and circle, to determine the driving performance under different channel cross-sections. Secondly, numerical simulation and regression analysis were conducted on the parameters of fiber winding diameter and winding angle of the soft actuator, and qualitative analysis was performed on the failure states of the numerical calculations. Lastly, numerical simulation and regression analysis were carried out on the parameters of wall thickness and driving channel length of the soft actuator to determine the influence of these parameters on the driving performance. Through the numerical simulation and regression analysis, this study provides a necessary theoretical foundation for the optimization design of soft actuator, effectively improving the development efficiency and dynamic performance of soft actuators.

Gas chromatography-mass spectrometry (GC-MS) and electronic tongue were used to quantitatively determine the volatile compounds and taste indices of 21 Jiang-flavor baijiu samples of different grades. These samples were differentiated by chemometrics, and key differential compounds among grades were identified. Finally, a discriminant model was established by machine learning. The results showed that there were differences in the contents of volatile compounds in Jiang-flavor baijiu of three grades, indicating the feasibility of further discriminant analysis. The total content of flavor compounds in second-grade baijiu (4 908 mg/L) was significantly lower than that in premium-grade (6 583 mg/L) and first-grade baijiu (8 254 mg/L), while the proportion of several esters responsible for floral and fruity aromas in total esters showed a decreasing trend as the grade decreased. Partial least squares-discriminant analysis (PLS-DA) identified 16 key differential compounds represented by ethyl palmitate and acetic acid. The results of electronic tongue showed that the taste indexes of premium-grade baijiu were more consistent, with lower bitterness and astringency aftertaste. The taste indexes of second-grade baijiu showed significant intersample differences. Principal component analysis (PCA) showed clear discrimination of Jiang-flavor baijiu of different grades according to their taste indexes. The above results provide a basis for the establishment of Jiang-flavor baijiu quality system. Four discriminant models were established based on 25 differential compounds and taste indexes identified. The accuracy of all models was higher than 90%, and the support vector machine (SVM) model performed best, with an accuracy of 100%.

Childhood and adolescent overweight and obesity rates have been increasing year by year, becoming extremely common and posing serious health risks, making it a global epidemic. Childhood obesity should not be ignored, and in-depth prevention and treatment should be implemented to reduce the risk of chronic diseases in adulthood and promote long-term health and physical development in children. Dietary therapy is beneficial for children to maintain a healthy weight, achieve nutritional balance, and prevent obesity. Additionally, specific nutritional requirements such as the ketogenic diet can be used in combination with dietary therapy to target the treatment of obese children. The traffic light diet plan can enhance children’s awareness of healthy eating and promote adherence to a balanced diet. However, childhood obesity is influenced by various factors. This article will analyze the causes of childhood obesity and incorporate the dietary concepts of ancient Chinese scholars. It will compare the different dietary treatment methods for childhood obesity in traditional Chinese medicine and Western medicine, such as the Warm Gallbladder Decoction, and explore other complementary interventions such as medication. By comparing the similarities and differences between traditional Chinese medicine and Western medicine, we can avoid their respective shortcomings and develop their advantages, combining them to provide feasible short-term and long-term treatment methods for obese children and adolescents. Furthermore, it can provide future research prospects for the development of dietary treatments specifically tailored to pediatric obesity patients.

Introduction: Selenium is an essential micronutrient the human body requires, which is closely linked to health. Rice, a primary staple food globally, is a major source of human selenium intake. To develop selenium-enriched rice varieties, it is imperative to understand the mechanisms behind selenium's absorption and transport within rice, alongside identifying the key genes involved in selenium uptake, transport, and transformation within the plant. Methods: This study conducted transcriptome sequencing on four types of rice materials (two with low-selenium and two with high-selenium contents) across roots, stems, leaves, and panicles to analyze the gene expression differences. Results and discussion: Differential gene expression was observed in the various tissues, identifying 5,815, 6,169, 7,609, and 10,223 distinct genes in roots, stems, leaves, and panicles, respectively. To delve into these differentially expressed genes and identify the hub genes linked to selenium contents, weighted gene co-expression network analysis (WGCNA) was performed. Ultimately, 10, 8, 7, and 6 hub genes in the roots, stems, leaves, and panicles, respectively, were identified. The identification of these hub genes substantially aids in advancing our understanding of the molecular mechanisms involved in selenium absorption and transport during the growth of rice. [ABSTRACT FROM AUTHOR]

The objective of this paper was to analyze the difference of composition between hybrid sorghum and conventional sorghum in southwest China, and to establish the method of variety identification. The basic physical and chemical components of 29 sorghum samples were determined, and the metabolite composition of 29 sorghum samples was determined by ultra high performance liquid chromatography coupled with Q Exactive HF-X mass spectrometry. The marker component screening and construction of variety identification model were carried out using stoichiometry, which included principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), cluster analysis and receiver operating characteristic (ROC) curve analysis. The model was based on the basic physicochemical composition and all metabolites. The results showed that the contents of amylopectin and tannin of the conventional varieties form southwest China were higher than that of hybrid varieties, while the contents of amylose and 1000-grain weight were lower. By analyzing the physicochemical properties, it was possible to identify certain samples. The OPLS-DA model was constructed with all 1048 compounds variables, and 46 of the differential metabolites that had a significant impact on the model identification were screened out. A novel OPLS-DA identification model was developed for sorghum varieties, achieving a 100% accuracy in identification. The conventional varieties from southwest China exhibited a relatively high concentration of phenolic compounds. Furthermore, after conducting receiver operating characteristic (ROC) curve analysis and assessing the relative standard deviation (RSD) of quality control sample (QC), 20 feature components that exhibited both high diagnostic accuracy and good reproducibility were identified. Among them, syringetin 3-glucoside and 6"-o-acetyldaidzein had higher expression abundance in conventional sorghum varieties, while D-glucarate, putsutrine, N-acetylputsutrine and L-glutamine had higher content in hybrid sorghum varieties. This study unveiled the disparity in metabolites between hybrid sorghum and conventional sorghum. The study successfully developed a scientifically rigorous and precise untargeted metabolomics approach using UHPLC-Q Exactive HF-X-MS. This method can be effectively utilized for the identification of sorghum varieties, offering a novel strategy for sorghum variety identification. [ABSTRACT FROM AUTHOR]