Search Results (2,496)

Forest ginseng (FG) is a rare medicinal and culinary plant in China, and its drying quality is heavily dependent on the drying method. This study investigated the effects of traditional hot air drying (HAD) and the self-developed negative-pressure circulating airflow-assisted desiccator drying (PCAD) method on the quality of FG using metabolomics and enzyme activity. The results revealed that the enzyme activities of dried FG were reduced considerably. PCAD preserved higher enzyme activity than HAD. Metabolomics data demonstrate that HAD promotes the formation of primary metabolites (amino acids, lipids, nucleotides, etc.), whereas PCAD promotes the formation of secondary metabolites (terpenoids, phenolic acids, etc.). A change-transformation network was built by combining the metabolites listed above and their biosynthetic pathways, and it was discovered that these biosynthetic pathways were primarily associated with the mevalonate (MVA) pathway, lipid metabolism, phenylpropane biosynthesis, and nucleotide metabolism. It is also believed that these findings are related to the chemical stimulation induced by thermal degradation and the ongoing catalysis of enzyme responses to drought stress. The facts presented above will give a scientific basis for the selection of FG drying processes, as well as helpful references for increasing the nutritional quality of processed FG. Full article

Background/Objectives: The breast cancer susceptibility gene 1 (BRCA1) is a tumor suppressor gene whose mutations are associated with increased susceptibility to develop breast or ovarian cancer. BRCA1 mainly exerts its protective effects through DNA double-strand break repair. Although not itself a transcriptional factor, BRCA1, through its multiple protein interaction domains, exerts transcriptional coregulation. In addition, BRCA1 expression alters cellular metabolism including inhibition of de novo fatty acid synthesis, changes in cellular bioenergetics, and activation of antioxidant defenses. Some of these actions may contribute to its global oncosuppressive effects. However, the breadth of metabolic pathways reprogrammed by BRCA1 is not fully elucidated. Methods: Breast cancer cells expressing BRCA1 were investigated by multiplatform metabolomics, metabolism-related transcriptomics, and joint metabolomics/transcriptomics data processing techniques, namely two-way orthogonal partial least squares and pathway analysis. Results: Joint analyses revealed the most important metabolites, genes, and pathways of metabolic reprogramming in BRCA1-expressing breast cancer cells. The breadth of metabolic reprogramming included fatty acid synthesis, bioenergetics, HIF-1 signaling pathway, antioxidation, nucleic acid synthesis, and other pathways. Among them, rewiring of glycerophospholipid (including phosphatidylcholine, -serine and -inositol) metabolism and increased arginine metabolism have not been reported yet. Conclusions: Rewired glycerophospholipid and arginine metabolism were identified as components of BRCA1-induced metabolic reprogramming in breast cancer cells. The study helps to identify metabolites that are candidate biomarkers of the BRCA1 genotype and metabolic pathways that can be exploited in targeted therapies. Full article

Sulfur fumigation (SF), acid dipping (HCl treatment, HAT), and their combination (SF+HAT) are common methods for long-term preservation and color protection of litchi. However, their effects on the metabolic profile of the litchi pericarp have not been investigated. SF resulted in a yellowish-green pericarp by up-regulating lightness (L*), b*, C*, and h° but down-regulating total anthocyanin content (TAC) and a*, while HAT resulted in a reddish coloration by up-regulating a*, b*, and C* but down-regulating L*, h°, and TAC. SF+HAT recovered reddish color with similar L*, C* to SF but a*, b*, h°, and TAC between SF and HAT. Differential accumulated metabolites (DAMs) detected in HAT (vs. control) were more than those in SF (vs. control), but similar to those in SF+HAT (vs. control). SF specifically down-regulated the content of cyanidin-3-O-rutinoside, sinapinaldehyde, salicylic acid, and tyrosol, but up-regulated 6 flavonoids (luteolin, kaempferol-3-O-(6″-malonyl)galactoside, hesperetin-7-O-glucoside, etc.). Five pathways (biosynthesis of phenylpropanoids, flavonoid biosynthesis, biosynthesis of secondary metabolites, glutathione metabolism, and cysteine and methionine metabolism) were commonly enriched among the three treatments, which significantly up-regulated sulfur-containing metabolites (mainly glutathione, methionine, and homocystine) and down-regulated substrates for browning (mainly procyanidin B2, C1, and coniferyl alcohol). These results provide metabolic evidence for the effect of three treatments on coloration and storability of litchi. Full article

Diabetes mellites (DM) is a chronic disease with increasing prevalence worldwide and multiple health implications. Among them, sarcopenia is a metabolic disorder characterized by loss of muscle mass and function. The two age-related diseases, DM and sarcopenia, share underlying pathophysiological pathways. This narrative literature review aims to provide an overview of the existing evidence on metabolomic studies evaluating DM associated with sarcopenia. Advancements in targeted and untargeted metabolomics techniques could provide better insight into the pathogenesis of sarcopenia in DM and describe their entangled and fluctuating interrelationship. Recent evidence showed that sarcopenia in DM induced significant changes in protein, lipid, carbohydrate, and in energy metabolisms in humans, animal models of DM, and cell cultures. Newer metabolites were reported, known metabolites were also found significantly modified, while few amino acids and lipids displayed a dual behavior. In addition, several therapeutic approaches proved to be promising interventions for slowing the progression of sarcopenia in DM, including physical activity, newer antihyperglycemic classes, D-pinitol, and genetic USP21 ablation, although none of them were yet validated for clinical use. Conversely, ceramides had a negative impact. Further research is needed to confirm the utility of these findings and to provide potential metabolomic biomarkers that might be relevant for the pathogenesis and treatment of sarcopenia in DM. Full article

Black tea is widely consumed worldwide, and its characteristic taste and color result from fermentation, where polyphenols are enzymatically oxidized to generate major pigments, including theaflavins (TFs), thearubigins (TRs), and theabrownins (TBs). This study investigated the effects of increased oxygen treatment during fermentation on the flavor attributes and chemical properties of Congou black tea. Fresh tea leaves (variety “Fuyun 6”) were subjected to four oxygen treatments: 0 h (CK), 1 h (TY-1h), 2 h (TY-2h), and 3 h (TY-3h), with oxygen supplied at 8.0 L/min. Sensory evaluation revealed that oxygen-treated samples exhibited tighter and deeper-colored leaves, a redder liquor, fuller taste, and a sweeter fragrance compared with CK. Chromatic analysis showed significant increases in redness (a*) and luminance (L*), alongside reduced yellowness (b*), indicating enhanced liquor color. Chemical analyses demonstrated elevated levels of TFs, TRs, and TBs in oxygen treatments, with TRs showing the most pronounced increase. Non-targeted metabolomics identified 2318 non-volatile and 761 volatile metabolites, highlighting upregulated flavonoids, phenolic acids, and lipids, and downregulated catechins and tannins, which collectively contributed to improved taste and aroma. Optimal results were achieved with 2–3 h of oxygen treatment, balancing pigment formation and sensory quality. These findings can provide a scientific basis for optimizing oxygen conditions in black tea fermentation to improve product quality. Full article

Alopecia, a prevalent dermatological disorder affecting over half of the global population, is strongly associated with psychological distress. Extracts from Periplaneta americana (L. PA), a medicinal insect resource, exhibit pharmacological activities (e.g., antioxidant, anti-inflammatory, microcirculation improvement) that align with core therapeutic targets for alopecia. This study aimed to systematically investigate the efficacy and mechanisms of PA extracts in promoting hair regeneration. A strategy combining network pharmacology prediction and in vivo experiments was adopted. The efficacy of a Periplaneta americana extract was validated by evaluating hair regrowth status and skin pathological staining in C57BL/6J mice. Transcriptomics, metabolomics, RT-qPCR, and 16s rRNA techniques were integrated to dissect the underlying mechanisms of its hair-growth-promoting effects. PA-011 significantly promoted hair regeneration in depilated mice via multiple mechanisms: enhanced skin superoxide dismutase activity and upregulated vascular endothelial growth factor expression; modulated FOXO/PI3K/AKT signaling pathway and restored skin microbiota homeostasis; and accelerated transition of hair follicles from the telogen to anagen phase. PA-011 exerts hair-promoting effects through synergistic modulation of FOXO/PI3K/AKT signaling and the skin microbiome. As a novel therapeutic candidate, it warrants further systematic investigation for clinical translation. Full article

Background/Objective: Pharmacological interventions often exert systemic effects beyond their primary targets, underscoring the need for a comprehensive evaluation of their metabolic impact. Etodolac is a nonsteroidal anti-inflammatory drug (NSAID) that alleviates pain, fever, and inflammation by inhibiting cyclooxygenase-2 (COX-2), thereby reducing prostaglandin synthesis. While its pharmacological effects are well known, the broader metabolic impact and potential mechanisms underlying improved clinical outcomes remain underexplored. Untargeted metabolomics, which profiles the metabolome without prior selection, is an emerging tool in clinical pharmacology for elucidating drug-induced metabolic changes. In this study, untargeted metabolomics was applied to investigate metabolic changes following a single oral dose of etodolac in healthy male volunteers. By analyzing serial blood samples over time, we identified endogenous metabolites whose concentrations were positively or inversely associated with the drug’s plasma levels. This approach provides a window into both therapeutic pathways and potential off-target effects, offering a promising strategy for early-stage drug evaluation and multi-target discovery using minimal human exposure. Methods: Thirty healthy participants received a 400 mg dose of Etodolac. Plasma samples were collected at five time points: pre-dose, before Cmax, at Cmax, after Cmax, and 36 h post-dose (n = 150). Samples underwent LC/MS-based untargeted metabolomics profiling and pharmacokinetic analysis. A total of 997 metabolites were significantly dysregulated between the pre-dose and Cmax time points, with 875 upregulated and 122 downregulated. Among these, 80 human endogenous metabolites were identified as being influenced by Etodolac. Results: A total of 17 metabolites exhibited time-dependent changes closely aligned with Etodolac’s pharmacokinetic profile, while 27 displayed inverse trends. Conclusions: Etodolac influences various metabolic pathways, including arachidonic acid metabolism, sphingolipid metabolism, and the biosynthesis of unsaturated fatty acids. These selective metabolic alterations complement its COX-2 inhibition and may contribute to its anti-inflammatory effects. This study provides new insights into Etodolac’s metabolic impact under healthy conditions and may inform future therapeutic strategies targeting inflammation. Full article

Drought stress severely limits the productivity of sweet potato (Ipomoea batatas L.), yet the stage-specific molecular mechanisms of its adaptation remain poorly understood. Therefore, we integrated transcriptomics and extensive targeted metabolomics analysis to investigate the drought responses of the sweet potato cultivar ‘Luoyu 11’ during the branching and tuber formation stage (DS1) and the storage root expansion stage (DS2) under controlled drought conditions (45 ± 5% field capacity). Transcriptome analysis identified 8292 and 13,509 differentially expressed genes in DS1 and DS2, respectively, compared with the well-watered control (75 ± 5% field capacity). KEGG enrichment analysis revealed the activation of plant hormone signaling, carbon metabolism, and flavonoid biosynthesis pathways, and more pronounced transcriptional changes were observed during the DS2 stage. Metabolomic analysis identified 415 differentially accumulated metabolites across the two growth periods, with flavonoids being the most abundant (accounting for 30.3% in DS1 and 23.7% in DS2), followed by amino acids and organic acids, which highlighted their roles in osmotic regulation and oxidative stress alleviation. Integrated omics analysis revealed stage-specific regulation of flavonoid biosynthesis under drought stress. Genes such as CYP75B1 and IF7MAT were consistently downregulated, whereas flavonol synthase and glycosyltransferases exhibited differential expression patterns, which correlated with the selective accumulation of trifolin and luteoloside. Our findings provide novel insights into the molecular basis of drought tolerance in sweet potato and offer actionable targets for breeding and precision water management in drought-prone regions. Full article

Background: Charcot–Marie–Tooth (CMT) is a group of inherited diseases impairing the peripheral nervous system. CMT originates from genetic variants that affect proteins fundamental for the myelination of peripheral nerves and survival. Moreover, environmental and humoral factors can impact disease development and evolution. Currently, no therapy is available. Metabolomics is an emerging field of biomedical research that enables the development of novel biomarkers for neurodegenerative diseases by targeting metabolic pathways or metabolites. This study aimed to evaluate the metabolomics profile of CMT disease by comparing patients with healthy individuals. Methods: A total of 22 CMT patients (CMT) were included in this study and were demographically matched with 26 healthy individuals (C). Serum samples were analyzed through Nuclear Magnetic Resonance spectroscopy, and multivariate and univariate statistical analyses were subsequently applied. Results: A supervised model showed a clear separation (R²X = 0.3; R²Y = 0.7; Q² = 0.4; p-value = 0.0004) between the two classes of subjects, and nine metabolites were found to be significantly different (2-hydroxybutyrate, 3-hydroxybutyrate, 3-methyl-2-oxovalerate, choline, citrate, glutamate, isoleucine, lysine, and methyl succinate). The combined ROC curve showed an AUC of 0.94 (CI: 0.9–1). Additional altered metabolic pathways were also identified within the disease context. Conclusion: This study represents a promising starting point, demonstrating the efficacy of metabolomics in evaluating CMT patients and identifying novel potential disease biomarkers. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Mitochondria, pivotal organelles in cellular metabolism and energy production, have emerged as critical players in the pathogenesis of cancer. This review outlines the progress in mitochondrial profiling through mass spectrometry-based metabolomics and its applications in cancer research. We provide unprecedented insights into the mitochondrial metabolic rewiring that fuels tumorigenesis, metastasis, and therapeutic resistance. The purpose of this review is to provide a comprehensive guide for the implementation of mitochondrial metabolomics, integrating advanced methodologies—including isolation, detection, and data integration—with insights into cancer-specific metabolic rewiring. We first summarize current methodologies for mitochondrial sample collection and pretreatment. Furthermore, we then discuss the recent advancements in mass spectrometry-based methodologies that facilitate the detailed profiling of mitochondrial metabolites, unveiling significant metabolic reprogramming associated with tumorigenesis. We emphasize how recent technological advancements have addressed longstanding challenges in the field and explore the role of mitochondrial metabolism-driven cancer development and progression for novel drug discovery and translational research applications in cancer. Collectively, this review delineates emerging opportunities for therapeutic discovery and aims to establish a foundation for future investigations into the therapeutic modulation of mitochondrial pathways in cancer, thereby paving the way for innovative diagnostic and therapeutic approaches targeting mitochondrial pathways. Full article

(1) Background: Epidemiological studies link ozone (O₃) exposure to diabetes risk, but mechanisms and early biomarkers remain unclear. (2) Methods: Female mice exposed to 0.5/1.0 ppm O₃ were assessed for glucose tolerance and HOMA (homeostasis model assessment) index. Genes related to impaired glucose tolerance and insulin resistance were screened through the Comparative Toxicogenomics Database (CTD), and verified using quantitative real-time PCR. In addition, liver histopathological observations and the determination of basic biochemical indicators were conducted, and targeted metabolomics analysis was performed on the liver to verify glycogen levels and gene expression. In vitro validation was conducted with HepG2 and Min6 cell lines. (3) Results: Fasting blood glucose and insulin resistance were elevated following O₃ exposure. Given that the liver plays a critical role in glucose metabolism, we further investigated hepatocyte apoptosis and alterations in glycogen metabolism, including reduced glycogen levels and genetic dysregulation. Metabolomics analysis revealed abnormalities in fructose metabolism and glycogen synthesis in the livers of the O₃-exposed group. In vitro studies demonstrated that oxidative stress enhances both liver cell apoptosis and insulin resistance in pancreatic islet β cells. (4) Conclusions: O₃ triggers prediabetes symptoms via hepatic metabolic dysfunction and hepatocyte apoptosis. The identified metabolites and genes offer potential as early biomarkers and therapeutic targets. Full article

Background/Objectives: Blunt cardiac injury (BCI) is a severe medical condition that may arise as a result of various traumas, including motor vehicle accidents and falls. The main objective of this study was to explore the role and underlying mechanisms of the TRPV4 gene in BCI. Elucidating the function of TRPV4 in BCI may reveal potential novel therapeutic targets for the treatment of this condition. Methods: Rats in each group, including the SD control group (SDCON), the SD blunt-trauma group (SDBT), the TRPV4 gene-knockout control group (KOCON), and the TRPV4 gene-knockout blunt-trauma group (KOBT), were all freely dropped from a fixed height with a weight of 200 g and struck in the left chest with a certain energy, causing BCI. After the experiment, the levels of serum IL-6 and IL-1β were detected to evaluate the inflammatory response. The myocardial tissue structure was observed by HE staining. In addition, cardiac transcriptome analysis was conducted to identify differentially expressed genes, and metabolomics studies were carried out using UHPLC-Q-TOF/MS technology to analyze metabolites. The results of transcriptomics and metabolomics were verified by qRT-PCR and Western blot analysis. Results: Compared with the SDCON group, the levels of serum IL-6 and IL-1β in the SDBT group were significantly increased (p < 0.001), while the levels of serum IL-6 and IL-1β in the KOBT group were significantly decreased (p < 0.001), indicating that the deletion of the TRPV4 gene alleviated the inflammation induced by BCI. HE staining showed that myocardial tissue injury was severe in the SDBT group, while myocardial tissue structure abnormalities were mild in the KOBT group. Transcriptome analysis revealed that there were 1045 upregulated genes and 643 downregulated genes in the KOBT group. These genes were enriched in pathways related to inflammation, apoptosis, and tissue repair, such as p53, apoptosis, AMPK, PPAR, and other signaling pathways. Metabolomics studies have found that TRPV4 regulates nucleotide metabolism, amino-acid metabolism, biotin metabolism, arginine and proline metabolism, pentose phosphate pathway, fructose and mannose metabolism, etc., in myocardial tissue. The combined analysis of metabolic and transcriptional data reveals that tryptophan metabolism and the protein digestion and absorption pathway may be the key mechanisms. The qRT-PCR results corroborated the expression of key genes identified in the transcriptome sequencing, while Western blot analysis validated the protein expression levels of pivotal regulators within the p53 and AMPK signaling pathways. Conclusions: Overall, the deletion of the TRPV4 gene effectively alleviates cardiac injury by reducing inflammation and tissue damage. These findings suggest that TRPV4 may become a new therapeutic target for BCI, providing new insights for future therapeutic strategies. Full article

Legumes are vital sources of protein, dietary fibre and nutrients, making them crucial for global food security and sustainable agriculture. However, their widespread acceptance and consumption are often limited by undesirable sensory characteristics, such as “a beany flavour”, bitterness or variable textures. Addressing these challenges requires a comprehensive understanding of the complex molecular mechanisms governing appearance, aroma, taste, flavour, texture and palatability in legumes, aiming to enhance their sensory appeal. This review highlights the transformative power of multi-omics approaches in dissecting these intricate biological pathways and facilitating the targeted enhancement of legume sensory qualities. By integrating data from genomics, transcriptomics, proteomics and metabolomics, the genetic and biochemical networks that directly dictate sensory perception can be comprehensively unveiled. The insights gained from these integrated multi-omics studies are proving instrumental in developing strategies for sensory enhancement. They enable the identification of key biomarkers for desirable traits, facilitating more efficient marker-assisted selection (MAS) and genomic selection (GS) in breeding programs. Furthermore, a molecular understanding of sensory pathways opens avenues for precise gene editing (e.g., using CRISPR-Cas9) to modify specific genes, reduce off-flavour compounds or optimise texture. Beyond genetic improvements, multi-omics data also inform the optimisation of post-harvest handling and processing methods (e.g., germination and fermentation) to enhance desirable sensory profiles and mitigate undesirable ones. This holistic approach, spanning from the genetic blueprint to the final sensory experience, will accelerate the development of new legume cultivars and products with enhanced palatability, thereby fostering increased consumption and ultimately contributing to healthier diets and more resilient food systems worldwide. Full article

The Pelargonium genus, encompassing over 280 species, remains markedly underexplored despite extensive traditional use for respiratory, gastrointestinal, and dermatological disorders. This review of aqueous, alcoholic, and hydroalcoholic extracts reveals critical research gaps: only 10 species have undergone chemical characterization, while 17 have been evaluated for biological activities. Phytochemical analysis identified 252 unique molecules across all studies, with flavonoids emerging as the predominant class (n = 108). Glycosylated derivatives demonstrated superior bioactivity profiles compared to non-glycosylated analogs. Phenolic acids (n = 43) and coumarins (n = 31) represented additional major classes. Experimental studies primarily documented antioxidant, antibacterial, and anti-inflammatory effects, with emerging evidence for antidiabetic, anticancer, and hepatoprotective activities. However, methodological heterogeneity across studies limits comparative analysis and comprehensive understanding. In silico target prediction analysis was performed on 197 high-confidence molecular structures. Glycosylated flavonols, anthocyanidins, flavones, and coumarins showed strong predicted interactions with key inflammatory targets (ALOX15, ALOX5, PTGER4, and NOS2) and metabolic regulators (GSK3A and PI4KB), providing mechanistic support for observed therapeutic effects and suggesting potential applications in chronic inflammatory and metabolic diseases. These findings underscore the substantial therapeutic potential of underexplored Pelargonium species and advocate for systematic research employing untargeted metabolomics, standardized bioassays, and compound-specific mechanistic validation to fully unlock the pharmacological potential of this diverse genus. Full article