Cardiometabolic heart failure with preserved ejection fraction (HFpEF) is a heterogenous metabolic disease, which in the heart presents as left ventricle diastolic dysfunction, ventricular stiffness, and myocardial structural remodeling. Deleterious changes in cardiac metabolism are central to HFpEF pathophysiology, and proposed treatments for the disease have focused on repairing these defects. In the present study, we used a preclinical mouse model that recapitulates cardiometabolic HFpEF to elucidate the molecular mechanisms driving cardiac dysfunction and tested whether recombinant adropin (Adr.) (a liver- and brain-derived endogenous peptide hormone) could reverse observed defects. We show that long-term treatment with Adr. reversed multiple markers of HFpEF-related cardiac dysfunction (including fibrosis, diastolic dysfunction, and cardiomyocyte hypertrophy). Using untargeted metabolomics, we found that Adr. treatment reduced hexosamine biosynthesis pathway activity, leading to a reduction in the O-GlcNAcylation of the cardiac fatty acid oxidation enzyme long-chain acyl-CoA dehydrogenase (LCAD). Reducing LCAD O-GlcNAcylation increased LCAD activity in vitro and reduced the accumulation of long-chain acylcarnitines in HFpEF mouse hearts in vivo. Our results suggest that Adr. may restore cardiac metabolic function in HFpEF and that targeting this pathway may be a novel therapeutic avenue for this disease.

Integration of morphological, physiological, transcriptomic and metabolomic analysis reveals the toxic effects of triadimefon on the earthworm.

Triclosan exposure perturbs skin lipid metabolism and inflammatory pathways: Insights from network toxicology and multi-omics analyses.

Dietary interventions are essential for managing phenylketonuria (PKU) and may influence metabolic regulation beyond phenylalanine control. We characterized the urinary metabolomic fingerprint of pediatric participants (n=82) recruited into clinical phenotypes: PKU, PKU with response to tetrahydrobiopterin (BH4), and hyperphenylalaninemia (HPA), as well as sex- and age-matched healthy children controls. Untargeted metabolomics (HPLC-Q-TOF-MS/MS) revealed 59 discriminant metabolites across multiple biochemical pathways, including phenylalanine, tryptophan, and caffeine metabolisms, as well as metabolites related to dietary exposure or gut microbial metabolism. Distinct urinary signatures were described across phenotypes. Phenylalanine-related pathways predominated in PKU, accompanied by increased excretion of vitamin derivatives, consistent with protein substitute supplementation. In contrast, reduced levels of non-phenylalanine amino acid derivatives, methylhistidines, creatine, and branched-chain amino acid-related metabolites were observed in PKU, suggesting alterations in muscle metabolism or natural protein intake. Microbiota-derived metabolites were also less represented in PKU, indicating potential effects of dietary restrictions on gut-host metabolic interactions. HPA individuals showed a urinary fingerprint closer to controls, whereas the BH4 subgroup exhibited the greatest metabolic heterogeneity, reflecting variability in dietary and pharmacological treatment responses. These findings reveal metabolic diversity within the pediatric PKU spectrum driven by clinical phenotype and nutritional management. Urinary metabolomics may support more precise monitoring of metabolic health status and guide precision nutrition strategies in PKU and HPA from early life.

Investigation of distinct metabolic profiles in the phloem and xylem of Rehmanniae Radix using untargeted metabolomics coupled with quantification of glycosides.

Xiao Zhen Fang mitigates cutaneous toxicity by inhibiting PANoptosis: Insights from untargeted metabolomics and transcriptomics.

Comparative metabolomic profiling and potential bioactive marker discovery of three Clerodendrum species and their different plant parts.

High-resolution mass spectrometry (HRMS) instruments for untargeted metabolomics typically offer a linear dynamic range spanning approximately 4 orders of magnitude. However, biological samples contain metabolites spanning concentration ranges far exceeding this window, making dilution optimization critical for reliable quantification. Despite its importance, dilution selection in untargeted workflows is rarely standardized and is often determined empirically through manual inspection, leading to operation outside the linear dynamic range, ion suppression, and compromised reproducibility. To address this, we present MetaDilutionR, an open-source R package that standardizes dilution optimization by systematically evaluating electrospray ionization (ESI) linearity using plasma as a model. MetaDilutionR automates dilution assessments, applying user-adjustable slope and R2 thresholds to classify features as linear or nonlinear and executes the complete analysis via a single function call, ensuring algorithmic reproducibility across users and platforms. The package generates comprehensive outputs, including log2-transformed data, a summary of linear features with their optimal dilution ranges, nonlinear features highlighting potential ion suppression or detector saturation, detailed evaluations across dilution scenarios, and visual regression plot reports. Benchmarking against three established metabolomics workflows demonstrated that the R2-slope criterion of MetaDilutionR reduces false-positive linear assignments. Cross-platform applicability of the algorithm on an independent GC-MS data set confirmed consistent classification performance beyond LC-HRMS. By facilitating systematic identification of metabolite-specific optimal dilution conditions, MetaDilutionR enables metabolites to be quantified within their linear dynamic range─a prerequisite for reliable quantification─thereby enhancing reproducibility and consistency of downstream validation, making it readily integrable into existing metabolomics workflows.

Maternal infections can have profound effects on embryonic heart development, yet the precise pathways through which these impacts manifest are still largely unexplored. This research explores the influence of maternal exposure to lipopolysaccharide (LPS) and polyinosinic-polycytidylic acid [Poly(I:C)] on metabolic profiles and mitochondrial function of offspring. At embryonic day 16.5, pregnant female C57BL/6J mice received either LPS or Poly(I:C) treatment. Human induced pluripotent stem cells were differentiated into cardiomyocytes (hiPSC-CMs) to evaluate the effects of various interventions on cardiomyocyte differentiation. mRNA sequencing and untargeted metabolomics were performed to analyze metabolic alterations. The findings from mRNA sequencing indicated that both LPS and Poly(I:C) caused metabolic pathway disturbances in the offspring's heart, with differentially expressed genes enriched in lipid, energy, and amino acid metabolism. Additionally, untargeted metabolomics showed a notable elevation in polyunsaturated fatty acids following LPS or Poly(I:C) treatment. Moreover, both LPS and Poly(I:C) treatment significantly impaired mitochondrial function, increased reactive oxygen species, and heightened lipid peroxidation within offspring mouse hearts. Mitochondrial dysfunction was mitigated through the application of antioxidant agents, such as N-acetylcysteine and ferrostatin-1. During hiPSC-CM differentiation, Poly(I:C) treatment led to similar mitochondrial dysfunction, while LPS treatment had minimal effects on ATP levels and lipid peroxidation. These findings indicate that maternal infection impairs metabolic signaling and mitochondrial function in the developing heart, with oxidative stress and lipid peroxidation playing key roles in these effects.

Urinary Microbiome and Metabolome Differentiate Overactive Bladder From the Physiological State, and Reflect Recent Antibiotic Use and Treatment Response.

As climate change drives more frequent drought-heat extremes, selecting drought-tolerant trees is crucial for future forest resilience. However, the role of tree-microbial associations remains largely unclear. We investigated how geographic origin, species identity, and intrinsic water use efficiency (iWUE) shape the rhizosphere microbiome and root-rhizosphere metabolome of Quercus robur L. and Q. petraea (Matt.) Liebl. In a 6-yr common garden experiment, we analyzed trees from two distinct geographic origins (upper Rhine basin and north German lowland) using 16S/ITS metabarcoding and untargeted metabolomics. We found a consistent legacy effect of seed origin on the prokaryotic rhizosphere microbiome and metabolome, whereas tree species had no significant impact. The bacterial family Pseudonocardiaceae was enriched for trees from the drier origin (NGL), while Blastocatellaceae and Micromonosporaceae were associated with iWUE. Higher iWUE also correlated with lower prokaryotic diversity. Ellagic acid, a polyphenol associated with drought tolerance, was enriched in the drier origin. The rhizosphere fungal community, however, was largely unaffected by origin or species. Our findings suggest that ecotypic adaptation linked to origin can outweigh species-level traits in shaping the oak rhizosphere. These findings emphasize that provenance-driven adaptation influences plant-microbe interactions and underscore the need for provenance-aware selection to strengthen forest drought resilience.

Chlorogenic acid attenuates rheumatoid arthritis by modulating immunity via the gut microbiota-derived metabolite indolelactic acid.

Grape seed proanthocyanidin extract suppresses bladder cancer by dual blockade of IMPDH1/2-mediated purine and pyrimidine nucleotide biosynthesis.

Ammonia accumulation triggers hepatic metabolic dysregulation and oxidative damage in grass carp (Ctenopharyngodon idellus) exposed to carbonate alkalinity: A metabolomic insight.

Biotransformation-derived metabolites from Astragalus membranaceus and Cordyceps militaris alleviate hyperuricemia via multi-target regulation.

With great social and economic importance, black wattle bark (Acacia mearnsii De Wild.) stands out due to its high content of condensed tannins. Although it is a known and exploited source of proanthocyanidins, little is known about the other compounds that may be present in this raw material and that may further contribute to its bioactive properties. Given this context, this work focused on applying untargeted metabolomics to investigate the metabolic diversity of black wattle bark using different extraction solvents. Furthermore, it aimed to investigate the proanthocyanidin profile of the raw material cultivated in southern Brazil. It was observed that the use of different solvents influenced the extraction and composition of metabolites, with the main differences observed between aqueous and organic solvents. Thus, 50% and 70% acetone, as well as 70% methanol, achieved the highest relative abundances in terms of metabolites. Eighty different compounds were annotated, including organic acids and phenolic compounds, among others, many of which were detected for the first time in black wattle bark. These results demonstrate the richness of the extracts in terms of their metabolic composition, exhibiting chemical complexity far beyond the condensed tannins. Regarding proanthocyanidins, the presence of oligomers up to pentamers was observed. The monomers observed were varied, with (epi)catechin and (epi)gallocatechin acting as polymer chain initiators, while (epi)robinetifinol and fisetinidol are the extender units. The metabolic diversity verified in black wattle bark justifies the potential use of its extracts as natural additives to be explored by the food and feed industries.

Chronic chlorpyrifos exposure induced depression and anxiety by gut microbiota alterations combined with metabolic disorders of ammonia and quinolinate.

A mathematical approach is introduced to achieve pseudoenhanced peak efficiency in liquid chromatography-high resolution mass spectrometry (LC-HRMS1), utilizing second-derivative transformations with respect to time and Gaussian smoothing cycles. The pipeline involved interpolating all MS scans, recorded as profile scans, onto a common m/z axis, allowing for second-derivative transformations for each m/z increment with respect to time across the entire data set. Validation using a public study (comprising 1100 compounds analyzed on a Thermo Q Exactive) demonstrates substantial improvements in feature detection and resolution, with qualitative and quantitative benefits. The transformation enables increased peak efficiency by up to 2 orders of magnitude in multicycle implementations without requiring physical hardware enhancements. The approach provides enhanced separation of complex mixtures, reduced background contributions, and increased reliability in untargeted metabolomics and related analyses.

Inhibition of endothelial ALOX12 mitigates cerebral ischemia-reperfusion injury by suppressing 12-HETE.

Microbial interaction and metabolic profile of low-salinity doubanjiang fermentation with Staphylococcus carnosus and Zygosaccharomyces rouxii.