Search Results (1,442)

Background/Objectives: The prevalence of obesity continues to rise globally, and with this an increase in the use of herbal weight loss supplements (WLS). At present, there is limited evidence to support the efficacy and safety of WLS, and there have been growing reports of adverse events associated with their use. We aimed to determine those WLS that caused toxicity in vitro and to use ¹H nuclear magnetic spectroscopy (NMR) to examine the metabolomic changes induced by these WLS in human hepatic and intestinal cells. Materials and Methods: This study used in vitro methods and ¹H NMR spectroscopy to analyse the metabolomic changes in vitro of WLS available for purchase in Australia. Ten WLS were selected, nine WLS caused significant toxicity in HepG2 human liver cells, and of these, six met the criteria for ¹H NMR analysis, which was based on a 25–50% reduction in cell viability. Results: All 10 WLS caused a significant reduction in viability of Caco-2 human intestinal cells, with seven selected for metabolic profiling. Orthogonal partial least squares discriminant analysis (O-PLS-DA) of ¹H NMR spectral data was used to characterise the metabolites that differed between the untreated and treated cells and the fold changes of the metabolites were determined. The results showed alterations to key metabolites such as amino acids, glucose, carboxylic acids, and amines in all treatment groups compared to untreated controls across both cell lines. Conclusions: Collectively, these biochemical changes represent disturbances to intracellular proteins, energy metabolism, and membrane lipids suggestive of oxidative stress. This study highlights the need for further investigations into the actions of these WLS in vivo, and, as these products were regulated by the Therapeutic Goods Administration (TGA) at the time of purchase, this study suggests improved pre-market screening to ensure consumer health is protected. Full article

Postmenopausal osteoporosis (PMOP) has become an important public health issue. The diagnosis of PMOP relies on clinical symptoms and radiology. However, most patients with PMOP do not exhibit obvious symptoms in the early stages of this disease. This study aimed to explore the feasibility of surface-enhanced Raman scattering (SERS) technology in the auxiliary screening of PMOP. PMOP rats were induced by ovariectomy (OVX) surgery, with a Sham group and an icariin (ICA) treatment group serving as controls. A monolayer film of Au nanoparticles (NPs) was prepared using the Marangoni effect in an oil/water/oil three-phase system, and was used to detect serum SERS signals in the Sham, OVX, and ICA treatment groups. Then, the spectral diagnostic model for PMOP screening was established utilizing partial least squares (PLS) and support vector machine (SVM) algorithms. Histopathology confirmed the establishment of the PMOP rat model. The assignment of Raman peaks and the analysis of spectral differences revealed the biochemical changes associated with PMOP, including the upregulation of tyrosine levels and the downregulation of arginine, tryptophan, lipids, and collagen. When employing the PLS-SVM algorithm to simultaneously classify and discriminate three groups of samples, the diagnostic sensitivity for PMOP is 93.33%, the specificity is 96.67%, and the accuracy of three-class classification is 91.11%. This study demonstrated the potential of SERS for the auxiliary screening of PMOP. Full article

In this study, a novel pattern recognition method named boosting–partial least squares–discriminant analysis (Boosting-PLS-DA) was developed for the non-destructive and accurate origin identification of food and medicine homologous substances (FMHSs). Taking Gastrodia elata, Aurantii Fructus Immaturus, and Angelica dahurica as examples, spectra of FMHSs from different origins were obtained by portable near-infrared (NIR) spectroscopy without destroying the samples. The identification models were developed with Boosting-PLS-DA, compared with principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA) models. The model performances were evaluated using the validation set and an external validation set obtained one month later. The results showed that the Boosting-PLS-DA method can obtain the best results. For the analysis of Aurantii Fructus Immaturus and Angelica dahurica, 100% accuracies of the validation sets and external validation sets were obtained using Boosting-PLS-DA models. For the analysis of Gastrodia elata, Boosting-PLS-DA models showed significant improvements in external validation set accuracies compared to PLS-DA, reducing the risk of overfitting. Boosting-PLS-DA method combines the high robustness of ensemble learning with the strong discriminative capability of discriminant analysis. The generalizability will be further validated with a sufficiently large external validation set and more types of FMHSs. Full article

Background/Objectives: Gout, a complex metabolic disorder of increasing global incidence, remains incompletely understood in its pathogenesis. Current diagnostic approaches exhibit significant limitations, including insufficient specificity and the requirement for invasive joint aspiration, highlighting the need for non-invasive, sensitive biomarkers for early detection. Methods: Urine metabolites were extracted from 28 healthy controls, 13 asymptomatic hyperuricemia (HUA) patients, and 29 acute gouty arthritis (AGA) patients. The extracted metabolites were analyzed by UHPLC-MS/MS for untargeted metabolomics. Differential metabolites were screened by partial least squares discriminant analysis (PLS-DA) and volcano plot analysis. Pathway analysis determined the core disorder pathway of gout progression. Results: A total of 278 differential metabolites associated with gout progression were identified. The most pronounced metabolic alterations were observed between the AGA and control groups, indicative of substantial metabolic reprogramming during disease transition. Metabolic pathway analysis revealed four significantly dysregulated pathways: histidine metabolism, nicotinate and nicotinamide metabolism, phenylalanine metabolism, and tyrosine metabolism. Receiver operating characteristic (ROC) curve analysis revealed that three urine markers with high diagnostic efficacy—oxoamide, 3-methylindole, and palmitic acid—exhibited progressive alterations across the disease continuum. Conclusions: This metabolomics study identified core regulatory metabolites and newly discovered metabolic pathways underlying gout pathogenesis, along with novel urinary biomarkers capable of predicting HUA-to-AGA progression. The aberrant levels of key metabolites in the disordered pathway implicate neuroimmune dysregulation, energy metabolism disruption, and oxidative stress in gout pathogenesis. These findings provide new foundations and strategies for the daily monitoring and prevention of gout. Full article

Commercial fruit juices are categorized into juice not from concentrate (JNFC) and juice from concentrate (JFC). Tomato juice is one of the most popular vegetable juices, and its aroma is an important factor in evaluating its quality. However, differences in the aroma characteristics of JNFC and JFC tomato juices have not been clearly identified. This study aimed to investigate the volatile organic compounds (VOCs) involved in distinguishing between JNFC and JFC using commercially available tomato juices. Furthermore, the effect of concentration on the VOC composition was evaluated using different procedures. Twenty-three commercial tomato juices were prepared for analysis of VOCs using headspace solid phase microextraction-gas chromatography mass spectrometry (HS-SPME-GC-MS). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to discriminate the samples into JNFC and JFC groups. JNFC contained 43 VOCs, which was more than twice that contained in JFC, and the quantitative variation was larger in JNFC than in JFC. In particular, the JNFC group contained significantly more alcohol and phenol compounds. On the other hand, the JFC group contained more formyl pyrrole and Strecker aldehydes. Additional GC-MS/olfactometry (GC-MS/O) and odor active value analyses indicated that (Z)-3-hexenol and 3-methylbutanal were the best VOCs to distinguish between the JNFC and JFC groups. Furthermore, different concentration procedures, including heating concentration (HC), decompression concentration (DC), and freeze drying (FD), were performed, and the corresponding VOCs were compared. HC and DC reduced the levels of most of the compounds to the levels seen in commercial JFC. These results indicate that the concentration procedure is an important processing stage, in addition to the break process, that determines the quality of tomato juice. Full article

The dynamic metabolic landscape underlying goose meat quality deterioration during refrigerated storage remains incompletely elucidated. Here, ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS)-based widely targeted metabolomics was employed to characterize metabolic profiling in refrigerated goose meat. Orthogonal partial least squares discriminant analysis (OPLS-DA) revealed 211 differential metabolites, while random forest regression (RFR) identified 30 candidate biomarkers. Seven metabolites, including xanthine, oxidized glutathione, and inosine 5′-monophosphate, exhibited significant correlations with total volatile basic nitrogen (TVB-N). By integrating potential biomarkers, metabolic pathways involving purines, amino acids, and sugars were identified as underlying mechanisms of goose meat spoilage. Notably, through comprehensive analysis of time-dependent correlations between physicochemical properties and metabolic profiles, a temporal threshold for quality deterioration in refrigerated goose meat was identified as day 5. These findings deepen our understanding of metabolite variations in refrigerated goose meat and provide a basis for optimizing storage protocols. The identified biomarkers may enable rapid detection kits and smart packaging systems for poultry industry applications. Full article

Background/Objectives: The aim of this study was to explore the effects of diets with different protein levels on the metabolite composition and metabolic pathways of the longest dorsal muscle of Tibetan pigs, in order to provide a metabolic basis for optimizing the nutritional regulation strategy of Tibetan pigs. Methods: A total of 32 healthy 180-day-old depopulated male Tibetan pigs were randomly divided into four groups and fed diets with protein levels of 10%, 12%, 14%, and 16%, respectively, with a feeding cycle of 8 weeks. The longest dorsal muscle samples were collected, and their metabolic profiles were systematically analyzed by LC-MS non-targeted metabolomics. Results: The TIC plots of the quality control samples were highly overlapped, indicating a stable instrumental detection process and good consistency of sample processing. Principal component analysis and orthogonal partial least squares discriminant analysis revealed significant metabolic differences between groups with different protein levels. A total of multiple differential metabolites was obtained based on VIP value and p-value screening, and Venn diagram analysis revealed a total of 11 metabolites among the three comparative groups, suggesting that they may have key roles in the protein regulation process. Volcano plots further clarified the number and trend of significantly up- and down-regulated metabolites in each group. KEGG pathway enrichment analysis showed that, with the elevation of protein level, the metabolic pathway response showed a tendency of expanding from basal energy metabolism to the complex network of amino acid synthesis, steroidogenesis, endocrine signaling, and detoxification pathways, especially in the high-protein-treated group. Conclusions: The study showed that different protein intake levels could significantly regulate the metabolites and key metabolic pathways in the longest muscle of Tibetan pigs, which provided theoretical support for the scientific formulation of a protein supply program to optimize the quality and growth performance of Tibetan pork. Full article

Elemental contents are effective fingerprints for Pu-erh tea’s geographical traceability, which is crucial for consumer protection and sustainable development. Region and processing methods are key factors influencing the tea’s elemental fingerprint. This study analyzed 28 elements in Pu-erh tea samples from three Yunnan production regions subjected to different processing stages in the year of 2023. The results show that significant regional differences were observed for 25 of the 28 elements. As, Li, Cu, Zn, and Cd contents vary significantly during processing. The contents of 27 elements (excluding Pb) are significantly influenced by the interaction between region and processing stage. Orthogonal partial least squares discriminant analysis (OPLS-DA) achieved good validation (Q² = 0.946) and identified 18 key factors, while the original and cross-validation correct classification rates were 100% and 98.6%, respectively. Crucially, the robustness of the model was confirmed with 100% accuracy through an independent validation set from tea samples in the harvest year of 2024. This study confirms that the elemental contents of Pu-erh tea are mainly influenced by region rather than processing stage, and elemental analysis can trace the geographical origin of Pu-erh effectively, even when mixed with a differently processed tea. Full article

High-pressure carbon dioxide (HPCD) has been widely used in the extraction of high-quality bioactive compounds. The flavor profiles of cold brew coffee (CBC) prepared by HPCD, traditional cold brew (TCB), and ice drip (ID) were comprehensively evaluated by chromatographic approaches, and their variations were investigated by multivariate statistical methods. ID produced the lightest coffee color while HPCD produced the darkest. No significant difference was found in pH among the three coffee processes. The concentrations of chlorogenic acids and caffeine were the highest in ID but the lowest in HPCD. Seventeen of the forty-eight volatiles were identified as key aroma compounds, contributing nutty, cocoa, caramel, baked, and other coffee flavors to all CBCs. Among them, linalool (OAV = 100.50) was found only in ID and provided ID with unique floral and fruity notes; 2-methyl-5-propylpyrazine (OAV = 17.70) was found only in TCB and gave a roasted aroma. With significantly lower levels of medicine-like and plastic off-flavors, HPCD had a refined aroma experience featuring nutty, cocoa, and caramel notes, though their contents were not the highest. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 36 aromas that could differentiate three cold brew methods, with TCB and HPCD being the most similar. Aroma sensory tests showed that no significant difference was perceived between TCB and HPCD. These findings provide a profound understanding of CBC flavor produced by cold brew methods from the aspect of composition, indicating that HPCD has great potential to realize TCB-like flavor characteristics in a shorter time. Full article

(1) Background: This study used the cold-tolerant cultivar “Daye No. 3” (DY) and the cold-sensitive cultivar “Longdong” (LD) as plant materials to study the metabolic changes in plant hormones in alfalfa (Medicago sativa L.) under cold stress. (2) Methods: The targeted quantitative detection of phytohormones in alfalfa was carried out by liquid chromatography–tandem mass spectrometry (LC-MS/MS) technology. Principal component analysis (PCA), orthogonal signal correction, and partial least squares discriminant analysis (OPLS-DA) were used to investigate sample classification and screen differential metabolites. (3) Results: The results showed that 17 differential metabolites were detected. Seven metabolites showed common changes in the two cultivars after low-temperature stress induction. The levels of tryptamine, N-jasmonoylisoleucine, trans-zeatin riboside, isopentenyladenine riboside, cis-zeatin riboside, and gibberellin A7 were decreased, while N6-isopentenyladenine levels increased. In addition, compared with the LD variety, DY had more metabolite changes in response to low-temperature stress. Abscisic acid and trans-zeatin were elevated, whereas IAA-alanine, dihydrozeatin riboside, and indole-3-carboxaldehyde showed reduced concentrations. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that differential plant hormones were more active in plant hormone signal transduction, zeatin biosynthesis, and tryptophan metabolism pathways. In addition, a total of 12 metabolites in these three pathways showed common changes under cold stress. (4) This study identified significant metabolomic differences between two alfalfa genotypes under stress. It highlighted key pathways and provided new insights into the metabolic changes of alfalfa under cold-stress conditions. Full article

Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa, has become an intermittent yet economically significant disease of wheat in the Upper Midwest during the last decade. Because chemical and cultural controls remain ineffective, breeders rely on developing resistant varieties, yet visual ratings in inoculated nurseries are labor-intensive, subjective, and time-consuming. To accelerate this process, we combined unmanned-aerial-vehicle hyperspectral imaging (UAV-HSI) with a carefully tuned chemometric workflow that delivers rapid, objective estimates of disease severity. Principal component analysis cleanly separated BLS, leaf rust, and Fusarium head blight, with the first component explaining 97.76% of the spectral variance, demonstrating in-field pathogen discrimination. Pre-processing of the hyperspectral cubes, followed by robust Partial Least Squares (RPLS) regression, improved model reliability by managing outliers and heteroscedastic noise. Four variable-selection strategies—Variable Importance in Projection (VIP), Interval PLS (iPLS), Recursive Weighted PLS (rPLS), and Genetic Algorithm (GA)—were evaluated; rPLS provided the best balance between parsimony and accuracy, trimming the predictor set from 244 to 29 bands. Informative wavelengths clustered in the near-infrared and red-edge regions, which are linked to chlorophyll loss and canopy water stress. The best model, RPLS with optimal preprocessing and variable selection based on the rPLS method, showed high predictive accuracy, achieving a cross-validated R² of 0.823 and cross-validated RMSE of 7.452, demonstrating its effectiveness for detecting and quantifying BLS. We also explored the spectral overlap with Sentinel-2 bands, showing how UAV-derived maps can nest within satellite mosaics to link plot-level scouting to landscape-scale surveillance. Together, these results lay a practical foundation for breeders to speed the selection of resistant lines and for agronomists to monitor BLS dynamics across multiple spatial scales. Full article

Antrodia cinnamomea, a renowned rare medicinal fungus in China, is rich in active components, exhibiting pharmacological effects, such as liver protection, hypoglycemic activity, and anti-tumor properties. Aiming to address the lack of horizontal comparative studies on volatile components of A. cinnamomea under different culture methods and the limitations of traditional detection methods, this study investigated the mycelia of A. cinnamomea cultured by solid-state culture (SAC), liquid culture (LAC), and dish culture (DAC). The flavor profiles were comprehensively evaluated using a combination of electronic tongue (E-tongue), electronic nose (E-nose), gas chromatography–ion mobility spectrometry (GC-IMS), and multivariate statistical methods. Results from E-tongue and E-nose showed distinct flavor profiles among the three culture methods. A total of 75 volatile compounds were detected by GC-IMS, among which esters, alcohols, and ketones were the main components, accounting for 62.7%. Partial least squares discriminant analysis (PLS-DA) identified 41 characteristic volatile compounds, and cluster heatmaps and orthogonal partial least squares discriminant analysis (OPLS-DA) further validated the metabolic preferences among culture methods. These findings provide a scientific basis for improving A. cinnamomea product quality through targeted flavor enhancement, support the development of standardized functional foods, and establish a flavor fingerprint for authenticity assessment, advancing the high-value utilization of this medicinal fungus. Full article

Rice wine is a beverage rich in flavor, but the flavor difference caused by rice raw materials has received little attention. To determine the key aroma compounds in rice wine, four types of samples were analyzed by gas chromatography–mass spectrometry (GC–MS), gas chromatography–olfactometry (GC-O), and sensory evaluation. Thirty-eight aroma compounds were detected in the experiment, thirteen of which were identified and quantified using the internal standard method. Additionally, multivariate statistical analyses such as partial least squares discriminant analysis (PLS-DA) effectively revealed three major differential aroma components in rice wine (VIP value ≥ 1). Furthermore, by correlation analysis, it was found that starch and fat in the raw material properties of glutinous rice were significantly and positively correlated with the main differential volatile aroma components in rice wine (p < 0.05). Combined with principal component analysis (PCA), the selection of glutinous rice varieties associated with starch and lipid characteristics during the rice wine brewing process is conducive to improving the overall quality of rice wine. Full article

Deoxynivalenol (DON) is a common mycotoxin that causes immunosuppression in pigs. Its effects on cellular metabolism remain unclear. In this study, we investigate DON-induced metabolic alterations in porcine alveolar macrophage cell line 3D4/21 using non-targeted metabolomics. MTT assays showed DON reduced cell viability in a concentration- and time-dependent manner. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) revealed distinct metabolic profiles between control and DON-treated groups. Metabolomic analysis identified 127 differential metabolites (VIP > 1, p < 0.05), primarily in purine metabolism, glutathione metabolism, and arginine–proline metabolism. Integration with transcriptomic data confirmed that these pathways play key roles in DON-induced immunotoxicity. Specifically, changes in purine metabolism suggested disrupted nucleotide synthesis and energy balance, while glutathione depletion indicated weakened antioxidant defense. These findings provided a systems biology perspective on DON’s metabolic reprogramming of immune cells and identified potential therapeutic targets to reduce mycotoxin-related immunosuppression in swine. Full article

Bamboo shoot boiled liquid (BSBL), a processing byproduct containing soluble proteins, peptides, amino acids, carbohydrates, and phenolics, is typically discarded, causing resource waste and environmental issues. This study analyzed metabolic changes in BSBL during Pediococcus pentosaceus B49 fermentation. The result of partial least squares discriminant analysis (PLS-DA) revealed significant metabolite profile differences across fermentation times (0 h, 24 h, 48 h, 72 h, 96 h). The most substantial alterations occurred within the first 24 h, followed by stabilization. Compared to unfermented BSBL, fermented samples exhibited significantly elevated signal intensities for 5,7-dimethoxyflavone, cinnamic acid, 3,4-dihydro-2H-1-benzopyran-2-one, 6,8-dimethyl-4-hydroxycoumarin, and 2-hydroxycinnamic acid (p < 0.05), showing upward trends over time. Conversely, (+)-gallocatechin intensity decreased gradually. Bitter peptides, such as alanylisoleucine, isoleucylisoleucine, leucylvaline, and phenylalanylisoleucine, in BSBL exhibited a significant reduction following fermentation with P. pentosaceus B49 (p < 0.05). KEGG enrichment indicated tyrosine metabolism (ko00350) and arginine/proline metabolism (ko00330) as the most impacted pathways. These findings elucidate metabolic regulation in BSBL fermentation, supporting development of functional fermented bamboo products. Full article