Citrus depressa peel extract acts as a prebiotic to reduce lipid accumulation and modulate gut microbiota in obese mice.

Citrus peels contain abundant polyphenols, particularly flavonoids, and have been shown to exert lipid accumulation decreasing ability. In this study, Citrus depressa peel applied to oven drying and extracted with ethanol extract as CDEE to analyze its flavonoids compositions and investigated its effects on a high-fat diet (HFD)-induced obese mice model. CDEE contained several flavonoids such as hesperidin, sinesentin, nobiletin, tangeretin, 5-demethylnobiletin, and 5-demethyltangeretin. The mice fed an HFD, and administration of 2% CDEE to could decrease weight gain, abdominal fat weight, inguinal fat weight, and the adipocyte size, and CDEE also reduced serum total cholesterol (TCHO), triacylglycerol (TG) compared with mice fed only on HFD. CDEE hindered lipid accumulation through a decreased fatty acid synthase (FAS) protein expression via upregulation of the protein expression of AMP-activated protein kinase α (AMPKα). Moreover, CDEE modulated gut microbiota that altered by HFD through an increased abundance of Lactobacillus reuteri compared with the HFD group. The results demonstrated that CDEE helps decrease lipid accumulation through the AMPK pathway, which also indicates a prebiotic-like effect on gut microbiota.

Essential oil from Citrus depressa peel exhibits antimicrobial, antioxidant and cancer chemopreventive effects.

BACKGROUND: Many diseases may be caused by pathogens and oxidative stress resulting from carcinogens. Earlier studies have highlighted the antimicrobial and antioxidant effects of plant essential oils (EO). It is crucial to effectively utilize agricultural waste to achieve a sustainable agricultural economy and protect the environment. The present study aimed to evaluate the potential benefits of EO extracted from the discarded peels of Citrus depressa Hayata (CD) and Citrus microcarpa Bunge (CM), synonyms of Citrus deliciosa Ten and Citrus japonica Thunb, respectively. RESULTS: Gas chromatography-mass spectrometry analysis revealed that the main compounds in CD-EO were (R)-(+)-limonene (38.97%), γ-terpinene (24.39%) and linalool (6.22%), whereas, in CM-EO, the main compounds were (R)-(+)-limonene (48.00%), ß-pinene (13.60%) and γ-terpinene (12.07%). CD-EO exhibited inhibitory effects on the growth of common microorganisms, including Candida albicans, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. However, CM-EO showed only inhibitory effects on E. coli. Furthermore, CD-EO exhibited superior antioxidant potential, as demonstrated by its ability to eliminate 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azinobis-3-ethylbenzthiazoline-6-sulfonate free radicals. Furthermore, CD-EO at a concentration of 100 µg mL-1 significantly inhibited 12-O-tetradecanoylphorbol-13-acetate-induced cancer transformation in mouse epidermal JB6 P+ cells (P < 0.05), possibly by up-regulating protein expression of nuclear factor erythroid 2-related factor 2 and its downstream antioxidant enzymes, such as NAD(P)H:quinone oxidoreductase 1, heme oxygenase-1 and UGT1A. CONCLUSION: These findings suggest that CD-EO exhibits inhibitory effects on pathogenic microorganisms, possesses antioxidant properties and has cancer chemopreventive potential. © 2024 Society of Chemical Industry.

Tangeretin and 4'-demethyltangeretin prevent damage to mouse hepatocytes from oxidative stress by activating the Nrf2-related antioxidant pathway via an epigenetic mechanism.

Polymethoxyflavones (PMFs) in citrus fruits have a variety of biological activities, including antioxidant, anti-inflammatory, anticancer, and anti-atherosclerotic effects. The liver is the major detoxifying organ of the human body; however, factors such as acetaminophen (APAP) overdose may increase oxidative stress in liver cells and lead to severe liver failure. In this study we examined the effects of tangeretin (TAN), a common citrus PMF, and its metabolite 4'-demethyltangeretin (4'-OH-TAN) on activation of the Nrf2 antioxidant system in mouse AML-12 hepatocytes through regulation by epigenetic mechanisms. The ability of TAN and 4'-OH-TAN to inhibit APAP-induced hepatotoxicity was also evaluated. The results showed that TAN and 4'-OH-TAN significantly increased the mRNA and protein levels of Nrf2 and Nrf2-mediated antioxidant and detoxifying enzymes (UGT1A, HO-1, and NQO1) in AML-12 cells. TAN and 4'-OH-TAN also suppressed protein expression of histone deacetylases (HDACs) and DNA methyltransferases (DMNTs) and reduced DNA methylation of the nrf2 promoter. Furthermore, TAN and 4'-OH-TAN prevented APAP-induced injury and inhibited APAP-induced ROS generation in AML-12 cells. Based on these results, we conclude that TAN and 4'-OH-TAN may increase the antioxidant capacity of liver cells by regulating epigenetic alteration to activate the Nrf2-related antioxidant system, thereby preventing liver cells from being damaged by APAP-induced oxidative stress.

Research on an intelligent diagnosis method of mechanical faults for small sample data sets.

The difficulty of feature extraction and the small sample size are two challenges in the field of mechanical fault diagnosis for a long time. Here we propose an intelligent mechanical fault diagnosis method for scenario with small sample datasets. This method can not only diagnose bearing faults but also gear faults, and has strong generalization performance. We use convolutional neural network to realize automatic feature extraction. Through sliding window scanning, one sample set is expanded to three sub-sample sets with different scales to meet the needs of deep learning training. Three convolutional networks are used to extract the features of the subsets respectively to ensure that their useful features are fully extracted. After feature extraction, the feature is reconstructed through feature splicing. Because of the unique advantages of SVM in dealing with small sample sets, we use SVM to classify the reconstructed features. We use the bearing data set collected by Case Western Reserve University in the United States, the bearing fault data set collected by Xi'an Jiaotong University in China, and the gearbox fault data collected by the University of Connecticut in the United States to conduct experiments. The experimental results show that the accuracy of training, validation and testing of the proposed method on the three data sets all reach 100%. This proves that our method can not only tackle the two challenges, but also has high fault diagnosis accuracy and strong generalization performance. It is hoped that our proposed method can contribute to the development of mechanical fault diagnosis.

Effects of green manure planting mode on the quality of Korla fragrant pears (Pyrus sinkiangensis Yu).

In this study, a three-year experiment on the fragrant pear orchard was conducted to investigate the effects of different varieties of green manure on the Korla fragrant pear fruit quality, with a view to finding a suitable green manure planting mode for Korla fragrant pear orchard. Green manures were planted in spaces among rows of pear trees, and then smashed and pressed into the soil as fertilisers by the agricultural machinery equipment in their full bloom period. In the experiment, four planting modes of green manure had been set for comparison: SA: Leguminosae green manures alfalfa (Medicago sativa L.), SP: Poaceae green manures oats (Avena sativa L.), ST: Cruciferae green manures oilseed rape (Brassica napus L.), and S: orchard authigenic green manures (Chenopodium album L., Mulgedium tataricum (L) DC., and Phragmites australis (Cav.) Trin. ex Steud.). Apart from that, eleven fruit quality indicators were analyzed to evaluating the effects of different green manure planting mode on the quality of fragrant pear. According to analysis of variance (ANOVA) results, there were significant differences among four planting modes in terms of nine fruit quality indicators (P<0.05). In addition, the correlation analysis (CA) results revealed that there were different degrees of correlations among quality indicators. On this basis, repeated information among indicators was eliminated by principal component analysis (PCA), thus simplifying and recombining the three principal components. All in all, these three principal components reflect appearance traits, internal nutritive value and taste of fruits, respectively. Specifically, SA significantly improved the internal quality and nutritive value of fruits, SP improved the physical traits of fruits, and ST significantly improved the taste of fruits. Based on the PCA results, a comprehensive evaluation model of fruit quality was constructed. The are comprehensive fruit quality scores:SA>SP>ST>S.

The knowledge domain and emerging trends in apple detection based on NIRS: A scientometric analysis with CiteSpace (1989-2021).

In this paper, 317 literature in the Web of Science (WoS) related to research on apple by near-infrared spectroscopy (NIRS) were drawn on the knowledge map of the number of literature, the co-occurrence network of authors and institutions, the co-occurrence and clustering of keywords based on CiteSpace. And a related analysis was carried out. Combined with the results of visual analysis and related literature, the research hotspots were sorted out and discussed. This paper provides a certain reference for relevant researchers to study in this field and provides a new method for macroscopically grasping the current status of apple quality detection research, which helps new researchers to quickly integrate into this field and obtain more valuable scientific information.