Search Results (1,210)

Background/Objectives: Possessing red and white ecotypes, and utilized in traditional Guyanese medicine, Doliocarpus dentatus’ red ecotype is preferred locally for its purported superior therapeutic efficacy. Although therapeutic metabolites were detected in D. dentatus previously, phytohormones remain largely unexplored, until now. Cytokinins, phytohormones responsible for plant cell division, growth and differentiation, are gaining traction for their therapeutic potential in human health. This study screened and quantified endogenous cytokinins and correlated detected cytokinins with selected secondary metabolites. Methods: Liquid chromatography–mass spectrometry was used to acquire phytohormone and metabolite data. Bioinformatics tools were used to assess untargeted metabolomics datasets via statistical and pathway analyses, and chemical groupings of putative metabolites. Results: In total, 20 of the 35 phytohormones were detected and quantified in both ecotypes, with the red ecotype displaying higher free base and glucoside cytokinin concentrations and exhibited 6.2 times the total CK content when compared to the white ecotype. Pathway analysis revealed flavonoid and monoterpenoid biosynthesis in red and white ecotypes, respectively. Positive correlations between specific cytokinins and alkaloids, and between trans-Zeatin and isopentenyladenosine riboside with phenolic compounds were observed. Conclusions: These results suggest that the red ecotype’s elevated cytokinin levels coupled with flavonoid biosynthesis enrichment support its preference in Guyanese traditional medicine. 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

The genus Panax contains traditional herbs that have been widely used in traditional medicine. The active constituents, collectively known as ginsenosides, are well characterized in the most representative species, P. notoginseng. However, the major bioactive chemical constituents of P. stipuleanatus together with P. vietnamensis are relatively less studied. In this study, an untargeted metabolomic analysis was performed in P. notoginseng, P. stipuleanatus, and P. vietnamensis using root and leaf organs. Further metabolomic differences in P. stipuleanatus were compared with those of the two most prevalent species. The analysis results revealed tissue-specific qualitative and quantitative metabolic differences in each species. Several differentially accumulated metabolites were enriched in the biosynthesis of secondary metabolites, including the biosynthesis of ginsenosides I. The ginsenosides Rb1, Rf, Rg1, Rh1, Rh8, and notoginsenosides E, M, and N had a higher abundance level in the roots of both P. notoginseng and P. vietnamensis. In P. stipuleanatus, the accumulation of potentially important ginsenosides is mainly found in the leaf. In particular, the dammarane-type ginsenosides Rb3, Rb1, Mx, and F2 as well as the notoginsenosides A, Fe, Fa, Fd, L, and N were identified to have a higher accumulation in the leaf. The strong positive correlation network of different ginsenosides probably enhanced secondary metabolism in each species. The comparative analysis revealed a significant differential accumulation of metabolites in the leaves of both species. The various compounds of dammarane-type ginsenoside, such as Rb1, Rg1, Rg6, Rh8, Rh10, Rh14, and majoroside F2, had a significantly higher concentration level in the leaves of P. stipuleanatus. In addition, several notoginsenoside compounds such as A, R1, Fe, Fd, and Ft1 showed a higher abundance in the leaf. These results show that the abundance level of major ginsenosides is significant in P. stipuleanatus and provides an important platform to improve the ginsenoside quality of Panax species. Full article

High semen quality is vital for reproductive success in the swine industry; however, seasonal fluctuations often compromise this quality. The molecular mechanism underlying these seasonal effects on semen quality remains largely unclear. This study employed untargeted metabolomic profiling of boar seminal plasma (SP) to identify metabolites and metabolic pathways associated with semen quality during the summer and winter months. Semen samples were collected from mature Duroc boars at a commercial boar stud and classified as Passed or Failed based on motility and morphology. SP from five samples per group was analyzed using ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). In total, 373 metabolites were detected in positive ion mode and 478 in negative ion mode. Several differentially expressed metabolites (DEMs) were identified, including ergothioneine, indole-3-methyl acetate, and avocadyne in the summer, as well as LysoPC, dopamine, and betaine in the winter. These metabolites are associated with key sperm functions, including energy metabolism, antioxidant defense, and capacitation. KEGG pathway analysis indicated enrichment in starch and sucrose metabolism, pyrimidine metabolism, and amino acid metabolism across the seasons. Overall, the results reveal that SP metabolomic profiles vary with the season, thereby influencing semen quality. The identified metabolites may serve as potential biomarkers for assessing semen quality and enhancing reproductive efficiency in swine production. 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

Background: The causation of type 2 diabetes remains under debate, but evidence supports both abdominal lipid and ectopic lipid overspill into tissues including muscle as key. How these depots differentially alter cardiometabolic profile and change during body weight and fat loss is not known. Methods: Women with obesity scheduled to undergo bariatric surgery were assessed at baseline (BL, n = 28) and at 6-month follow-up (6m_FU, n = 26) after weight loss. Fasting plasma (Pla), subcutaneous thigh adipose (STA), subcutaneous abdominal adipose, (SAA), and thigh vastus lateralis muscle (VLM) samples were collected at BL through surgery and at 6m_FU using needle biopsy. An untargeted liquid chromatography mass spectrometry metabolomics platform was used. Pla and tissue-specific lipid and polar metabolite profiles were modelled as changes from BL and 6m_FU. Results: There was significant body weight (−24.5 kg) loss at 6m_FU (p < 0.05). BL vs. 6m_FU tissue metabolomics profiles showed the largest difference in lipid profiles in SAA tissue in response to surgery. Conversely, polar metabolites were more susceptible to change in STA and VLM. In Pla samples, both lipid and polar metabolite profiles showed significant differences between timepoints. Jaccard–Tanimoto coefficient t-tests identified a sub-group of gut microbiome and dietary-derived omega-3-fatty-acid-containing lipid species and core energy metabolism and adipose catabolism-associated polar metabolites that are trafficked between sample types in response to bariatric surgery. Conclusions: In this first report on channelling of lipids and polar metabolites to alternative tissues in bariatric-induced weight loss, adaptive shuttling of small molecules was identified, further promoting adipose processing and highlighting the dynamic and coordinated nature of post-surgical metabolic regulation. Full article

Root-knot nematode (Meloidogyne incognita) is a globally destructive plant-parasitic nematode that severely impedes the sustainable production of horticultural crops. Metabolic reprogramming in plant roots represents the host response to M. incognita infection that can also be exploited by the nematode to facilitate its parasitism. In this study, untargeted metabolomics was employed to analyze metabolic changes in cucumber roots following nematode inoculation, with the goal of identifying differentially accumulated metabolites that may influence M. incognita behavior. Metabolomic analysis revealed that M. incognita significantly altered the cucumber root metabolome, triggering an accumulation of lipids and organic acids and enriching biotic stress-related pathways such as alkaloid biosynthesis and linoleic acid metabolism. Among differentially accumulated metabolites, myristic acid and hexadecanal were selected for further study due to their potential roles in nematode inhibition. In vitro assays demonstrated that both metabolites suppressed egg hatching and reduced infectivity of M. incognita, while pot experiments indicated a correlation between their application and reduced root gall formation. Chemotaxis assays further revealed that both metabolites exerted repellent effects on the chemotactic migration of M. incognita J2 and suppressed the transcriptional expression of two motility-and feeding-related neuropeptides, Mi-flp-1 and Mi-flp-18. In conclusion, this study demonstrates the significant potential of differentially accumulated metabolites induced by M. incognita infection for nematode disease control, achieved by interfering with nematode chemotaxis and subsequent infection. This work also provides deeper insights into the metabolomic mechanisms underlying the cucumber-M. incognita interaction. Full article

Background: Type 2 diabetes (T2D) is a global health epidemic with rising prevalence within Asian populations, particularly amongst individuals with high visceral adiposity and ectopic organ fat, the so-called Thin-Outside, Fat-Inside phenotype. Metabolomic and microbiome shifts may herald T2D onset, presenting potential biomarkers and mechanistic insight into metabolic dysregulation. However, multi-omics datasets across ethnicities remain limited. Methods: We performed cross-sectional multi-omics analyses on 171 adults (99 Asian Chinese, 72 European Caucasian) from the New Zealand-based TOFI_Asia cohort at 4-years follow-up. Paired plasma and faecal samples were analysed using untargeted metabolomic profiling (polar/lipid fractions) and shotgun metagenomic sequencing, respectively. Sparse multi-block partial least squares regression and discriminant analysis (DIABLO) unveiled signatures associated with ethnicity, glycaemic status, and sex. Results: Ethnicity-based DIABLO modelling achieved a balanced error rate of 0.22, correctly classifying 76.54% of test samples. Polar metabolites had the highest discriminatory power (AUC = 0.96), with trigonelline enriched in European Caucasians and carnitine in Asian Chinese. Lipid profiles highlighted ethnicity-specific signatures: Asian Chinese showed enrichment of polyunsaturated triglycerides (TG.16:0_18:2_22:6, TG.18:1_18:2_22:6) and ether-linked phospholipids, while European Caucasians exhibited higher levels of saturated species (TG.16:0_16:0_14:1, TG.15:0_15:0_17:1). The bacteria Bifidobacterium pseudocatenulatum, Erysipelatoclostridium ramosum, and Enterocloster bolteae characterised Asian Chinese participants, while Oscillibacter sp. and Clostridium innocuum characterised European Caucasians. Cross-omic correlations highlighted negative correlations of Phocaeicola vulgatus with amino acids (r = −0.84 to −0.76), while E. ramosum and C. innocuum positively correlated with long-chain triglycerides (r = 0.55–0.62). Conclusions: Ethnicity drove robust multi-omic differentiation, revealing distinctive metabolic and microbial profiles potentially underlying the differential T2D risk between Asian Chinese and European Caucasians. Full article

The impact of seasonality on the aroma quality of tea has been documented in various tea types, but not specifically in oolong tea. This study is the first to explore the complex relationships between seasonality, volatile compounds, and aroma quality in oolong tea. Using Headspace Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC-MS)-based untargeted metabolomics, we analyzed 266 samples of Tieguanyin oolong tea. The data identified linalool, linalool oxides (trans-linalool oxide (furanoid) and trans-linalool oxide (pyranoid)), and their metabolites (diendiol I; hotrienol) as key seasonal discriminants. Four out of the top ten key differential compounds for distinguishing aroma scores were metabolites from fatty acid degradation, namely trans-3-hexenyl butyrate, trans-2-hexenyl hexanoate, hexyl hexanoate, and hexyl 2-methyl butyrate. Approximately one-fifth of the seasonal discriminant volatile compounds were significant in influencing aroma quality. Overall, the impact of seasonality on the aroma quality of finished Tieguanyin oolong tea is marginal. These findings enhance our understanding of the interplay between seasonal variations, volatile composition, and aroma quality in oolong tea. 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

Rhubarb, a medicinal herb in Gansu Province, China, undergoes significant quality changes during sun-drying. This study investigated color changes, drying kinetics, anthraquinone (AQ) content, metabolic profiles, and enzyme activity during the process. Results showed that drying induced enzymatic browning, with the browning index (BI) progressively increasing over extended drying periods (4–16 h) and with greater slice thickness (2–8 mm). Catalase (CAT) activity first decreased and then increased, while polyphenol oxidase (PPO) activity decreased throughout drying. Slice thickness significantly affected AQ content, with the highest in 2 mm slices and the lowest in 4 mm slices. The drying process followed a logarithmic model (R² = 0.99418, RMSE = 0.02310, and χ² = 0.0005). Metabolomics analysis identified 631 differential metabolites, with 8 key metabolites linked to flavonoid biosynthesis, phenylalanine biosynthesis, and tyrosine metabolism. Fifteen enzymes were involved in metabolite synthesis and decomposition, though some enzyme activity trends contradicted metabolite changes. This study provides insight into rhubarb drying mechanisms and a basis for optimizing the drying process. Full article

Sanghuangporus spp. are medicinal fungi with significant therapeutic value, but their taxonomic ambiguity and frequent market adulteration have hindered their standardized utilization. In this study, untargeted metabolomics based on UPLC-Q-TOF-MS was employed to systematically analyze the metabolic profiles of three Sanghuangporus species: Sanghuangporus. sanghuang (SS), Sanghuangporus. vaninii (SV), and Sanghuangporus. baumii (SB). A total of 788 metabolites were identified and classified into 16 categories, among which 97 were common differential metabolites, including bioactive compounds such as flavonoids, polysaccharides, and terpenoids. Multivariate statistical analyses (PCA and OPLS-DA) revealed distinct metabolic patterns among the species. KEGG pathway enrichment analysis showed that the differential metabolites were mainly involved in flavonoid and isoflavonoid biosynthesis. Notably, SV and SB exhibited significantly higher levels of several key bioactive compounds, including Apigenin and D-glucuronolactone, compared to SS. These findings highlight substantial interspecies differences in metabolic composition and pharmacological potential, providing a scientific basis for species authentication, quality control, and medicinal development of Sanghuangporus. Full article

Breast cancer (BC) is a neoplasm characterized by high heterogeneity and is influenced by intrinsic molecular subtypes and clinical stage, aspects that remain underexplored in the Colombian population. This study aimed to characterize metabolic alterations associated with subtypes and disease progression in a group of newly diagnosed, treatment-naive Colombian women using an untargeted metabolomics approach. To improve metabolite coverage, samples were analyzed using LC-QTOF-MS and GC-QTOF-MS, along with amino acid profiling. The Luminal B subtype exhibited elevated levels of long-chain acylcarnitines and higher free fatty acid concentrations than the other subtypes. It also presented elevated levels of carbohydrates and essential glycolytic intermediates, suggesting that this subtype may adopt a hybrid metabolic phenotype characterized by increased glycolytic flux as well as enhanced fatty acid catabolism. Tumor, Node, and Metastasis (TNM) staging analysis revealed progressive metabolic reprogramming of BC. In advanced stages, a sustained increase in phosphatidylcholines and a decrease in lysophosphatidylcholines were observed, reflecting lipid alterations associated with key roles in tumor progression. In early stages (I-II), plasma metabolites with high discriminatory power were identified, such as glutamic acid, ribose, and glycerol, which are associated with dysfunctions in energy and carbohydrate metabolism. These results highlight metabolomics as a promising tool for the early diagnosis, clinical follow-up, and molecular characterization of BC. Full article

Tanacetum parthenium (Asteraceae) has been traditionally used worldwide for medicinal purposes, and some of its therapeutic uses have been attributed to the pharmacological effects of its secondary metabolites. The root culture of this species might represent a sustainable source of several pharmacologically active compounds. The biomass of a root T. parthenium culture was extracted with methanol and fractionated using column chromatography. Three selected fractions (4TP, 5TP, and 8TP) were analyzed via spectrophotometric, chromatographic, and mass spectrometry techniques and in vitro pharmacological assays. The greatest values for total phenolic and phenolic acid contents and antibacterial activity against Escherichia coli were determined for 4TP. The highest values for total flavonoid and sesquiterpene lactone contents, antioxidant potential, and α-amylase inhibitory effect were determined for 8TP. The antibacterial effect against Staphylococcus aureus was not significantly different among the three fractions. The root culture of T. parthenium is a potential source of several metabolites, such as phenolic acids, fatty acids, coumarins, sesquiterpenoids, and triterpenoids, which are capable of exerting α-amylase inhibition and antioxidant, antibacterial, and cytotoxic effects. Among eight phenolic compounds detected and quantified in the fractions, chlorogenic acid was the most abundant. Full article

Obesity is currently one of the major medical problems affecting humans and companion animals, including cats; however, a detailed understanding of the metabolic processes altered in feline obesity remains limited. This study aimed to investigate obesity-related changes in the serum metabolome of three groups of cats, metabolically healthy normal-weight (MHN) cats, metabolically healthy overweight (MHO) cats, and metabolically unhealthy overweight (MUO) cats. Metabolome changes were assessed using LC-MS (untargeted), LC-MS (targeted), and FIA-MS (targeted) methods. Untargeted analysis detected 141 significant annotated features, while targeted approach identified 48 metabolites significantly associated with obesity. Both untargeted and targeted analyses showed lower kynurenine levels in the MUO group compared to the MHN group. Targeted LC-MS analysis identified 11 significant metabolites, whereas the FIA-MS approach detected 37. Four metabolites—glycine, citrulline, and two phosphatidylcholines—were found at lower levels in the MHO group compared to the MHN group. Arginine and proline metabolism, along with methionine metabolism, were significantly altered pathways, while thyroid hormone synthesis was independently altered with the highest enrichment ratio. The obtained results suggest that cats with a healthy phenotype exhibit an intermediate-metabolic-risk profile and provide new insights into the metabolic mechanisms and pathways underlying feline obesity. Full article