PubMed

ACS Chem Biol. 2026 Jun 9. doi: 10.1021/acschembio.6c00104. Online ahead of print.ABSTRACTNemamide A and B are hybrid polyketide-nonribosomal peptides that are produced by the PKS-1-NRPS-1 enzymatic assembly line in the canal-associated neurons (CANs) of the nematode Caenorhabditis elegans. These signaling molecules promote survival during and recovery from starvation-induced larval arrest. Here, using genome editing and targeted metabolomics, we probed the roles of the different domains of PKS-1 in the initiation of nemamide biosynthesis. We showed that the first four domains of PKS-1 are not required for the biosynthesis of the triene-containing nemamide A, but are required for the biosynthesis of the tetraene-containing nemamide B. By targeting genes that are highly expressed in the CANs, we identified two additional enzymes that participate in the biosynthetic pathway: the peroxisomal carnitine O-octanoyl transferase CROT-1, which is required for the biosynthesis of nemamide A, and the enoyl-CoA hydratase ECH-7, which is required for the biosynthesis of nemamide B. We heterologously expressed CROT-1 and showed that it prefers hexanoyl-CoA and octanoyl-CoA as substrates, converting them to the corresponding carnitine esters. According to our model, ECH-7 is needed to supply the starter unit for nemamide B biosynthesis, which is loaded onto the first carrier protein of PKS-1 and extended by the first module, thereby installing the double bond that is unique to nemamide B. Meanwhile, CROT-1 is needed to supply the starter unit for nemamide A biosynthesis, which is loaded onto the second carrier protein of PKS-1. Our data suggest that the biosynthetic pathways of nemamide A and B are under the control of two different initiation mechanisms and, thus, that the production of these two secondary metabolites may be independently regulated.PMID:42261222 | DOI:10.1021/acschembio.6c00104

Mini Rev Med Chem. 2026 Jun 8. doi: 10.2174/0113895575436551260522063328. Online ahead of print.ABSTRACTPterocarpus Santalinus: (red sandalwood) is a medicinal species native to the Eastern Ghats of South India, traditionally used in Ayurveda and Siddha for the treatment of inflammatory, gastrointestinal, dermatological, and metabolic disorders. Modern studies support its therapeutic potential against cancer, oxidative stress, infections, ulcers, and neurodegenerative diseases, highlighting its broad pharmacological significance. The diverse pharmacological effects of P. santalinus are attributed to its rich phytochemical profile. The plant harbors a wide array of secondary metabolites, including terpenoids, steroids, sesquiterpenes, flavonoids, benzofurans, coumarins, lignans, pterocarpans, aurones, and chalcones. These bioactive compounds function both individually and synergistically to elicit anti-inflammatory, antioxidant, anticancer, antibacterial, antiviral, woundhealing, and neuroprotective effects. Additionally, its ability to regulate metabolic pathways linked to diabetes and dyslipidemia highlights its promise for addressing non-communicable diseases. Mechanistic studies further reveal that these pharmacological actions are mediated through multiple molecular pathways, notably NF-κB, MAPK, Nrf2-ARE, and TGF-β/Smads, underscoring its multitarget mode of action. Despite its long-standing ethnopharmacological relevance and promising experimental evidence, systematic scientific investigation of P. santalinus remains limited. Future research should focus on bioassay-guided isolation, in vivo validation, safety, and pharmacokinetic evaluation, and the integration of network pharmacology, metabolomics, and sustainable cultivation to enable efficient lead discovery and conservation. In conclusion, a systematic phytochemical and pharmacological investigation of P. santalinus is essential to validate its traditional uses, establish the therapeutic value of its chemical constituents, and support its integration into mainstream pharmaceutical and commercial applications.PMID:42261177 | DOI:10.2174/0113895575436551260522063328

J Sep Sci. 2026 Jun;49(6):e70464. doi: 10.1002/jssc.70464.ABSTRACTViscum coloratum (Kom.) Nakai, a widely distributed hemiparasitic medicinal plant in Asia, exhibits host-influenced metabolic traits that remain inadequately characterized. To further investigate this issue, an untargeted metabolomics approach was employed to comprehensively delineate host-dependent metabolic variation. Ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS), a powerful analytical platform for untargeted metabolomics, was used to examine samples collected from two host species in Hubei Province, China. Differential metabolites were screened through multivariate chemometric analysis and characterized using an integrated annotation strategy to ensure systematic and reliable identification. Sixty-eight differential constituents were annotated and mainly assigned to phenylpropanoids, polyketides, lipids and lipid-like compounds, and organic acids and derivatives. These classes represented the major metabolic groups associated with host-dependent variation among the samples analyzed in this study. Furthermore, an exploratory 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay revealed significant differences in antioxidant capacity between the two groups, suggesting that host plants may influence the pharmacologically relevant properties of V. coloratum. These findings highlight the importance of considering host factors in its quality control, provide a comprehensive framework for differential metabolite identification, and enhance the understanding of the metabolic characteristics of V. coloratum.PMID:42261120 | DOI:10.1002/jssc.70464

Antioxid Redox Signal. 2026 Jun 8:15230864261455465. doi: 10.1177/15230864261455465. Online ahead of print.ABSTRACTOBJECTIVE: Sleeve gastrectomy (SG) improves obesity-associated type 2 diabetes mellitus (T2DM) beyond mere weight loss. We investigated whether SG enhances systemic metabolic homeostasis by suppressing the Ghrelin-growth hormone secretagogue receptor (GHSR) axis, remodeling hypothalamic pro-opiomelanocortin (POMC) neuronal activity, and reprogramming CD4+ T cell immunometabolism.METHODS: Using a diet-induced T2DM mouse model undergoing SG or Sham surgery, we integrated bulk/single-cell RNA sequencing and metabolomics to evaluate systemic neuro-immune-metabolic alterations. Functional assays validated Ghrelin's effects on CD4+ T cell metabolism and differentiation, alongside assessments of hepatic/pancreatic function and hypothalamic neuronal activity.RESULTS: SG globally remodeled peripheral immunity, expanding Tregs while reducing pro-inflammatory Th17 cells. scRNA-seq and metabolomic profiling revealed that CD4+ T cells shifted metabolically from glycolysis toward oxidative phosphorylation, matching increased tricarboxylic acid cycle intermediates. Functionally, Ghrelin-GHSR signaling promoted CD4+ T cell glycolysis, mitochondrial damage, and Th17 skewing; GHSR antagonism successfully reversed these detrimental effects. Systemically, SG reduced hyperglycemia and hepatic lipidosis, restored islet α/β-cell balance, activated anorexigenic POMC neurons, and suppressed AgRP neurons.CONCLUSION: SG alleviates T2DM through coordinated suppression of the Ghrelin-GHSR axis, bridging central appetite regulation with peripheral immunometabolic reprogramming. By shifting CD4+ T cells toward oxidative metabolism and restoring the Treg/Th17 balance, SG drives systemic metabolic recovery, providing critical molecular insights into the neuro-immune mechanisms of metabolic surgery. Antioxid. Redox Signal. 00, 000-000.PMID:42260953 | DOI:10.1177/15230864261455465

Medicine (Baltimore). 2026 Jun 5;105(23):e49161. doi: 10.1097/MD.0000000000049161.ABSTRACTObservational studies have reported associations between circulating blood metabolite features and myocardial infarction (MI), but whether these associations are causal remains uncertain. Mendelian randomization (MR) can strengthen causal inference by using genetic variants as instrumental variables. We therefore conducted a 2-sample MR study, followed by pathway enrichment analysis, to evaluate the potential causal effects of genetically predicted blood metabolite features on MI. Genetic association data for 452 blood metabolite features were obtained from a published metabolomics GWAS including 7824 participants of European ancestry. The metabolite panel comprised annotated small molecules and lipids as well as a limited number of peptide/partially annotated or unknown metabolite signatures defined in the source GWAS. Summary statistics for MI were obtained from FinnGen (n = 369,139) and the IEU Open GWAS project (n = 461,823), and a discovery-replication design was applied. The inverse-variance weighted method was the primary MR analysis, complemented by weighted median, MR-Egger, weighted mode, and simple mode. Sensitivity analyses included Cochran Q test, MR-Egger intercept, funnel plots, and leave-one-out analyses. Significant findings were further evaluated using pathway enrichment analysis. In FinnGen, 12 annotated metabolite features were associated with a lower MI risk, and 8 annotated metabolite features were associated with a higher MI risk after excluding unknown signatures from the descriptive summary. In the IEU Open GWAS dataset, 10 annotated metabolite features were protective, and 7 were risk-associated. Glycine, N-acetylglycine, deoxycholate, propionylcarnitine, and margarate (17:0) showed directionally consistent associations across both MI datasets, supporting the robustness of these findings. This 2-sample MR analysis supports potential causal roles of several circulating metabolite features in MI. These findings expand the evidence base for metabolic mechanisms underlying MI and may help prioritize biomarkers and pathways for future validation.PMID:42260813 | DOI:10.1097/MD.0000000000049161

BMC Psychiatry. 2026 Jun 8. doi: 10.1186/s12888-026-08178-8. Online ahead of print.ABSTRACTAutism Spectrum Disorder (ASD) arises from complex and not yet completely understood interactions between genetic and environmental factors. Alongside known hallmarks of neurobiological and structural changes in ASD brain, alterations in gut microbiota are frequently observed in ASD and may contribute to its pathophysiology. Identifying reliable biomarkers through multivariate analysis and machine learning offers promising avenues for improving ASD diagnosis and understanding comorbid gastrointestinal symptoms. In this study, a machine learning model was trained to identify ASD and healthy controls based on the theoretical production of metabolites for each gut bacterial species and each individual, combining the data collected from two global databases (GMRepo v2 and Agora2). Random Forest Classification models reach a mean accuracy of 85%, and a subsequent literature analysis of the 5% most significant metabolites showed a 40% correspondence with previously published in vivo studies. Some of the most relevant compounds detected by the theoretical model are amino acid and amino-acidic derivatives, volatile organic compounds, and short-chain fatty acids. Results are coherent with empirical evidence, supporting microbiota's role in ASD pathophysiology by contributing to neurotransmitters' biosynthesis and degradation, intestinal epithelial barrier integrity, immunological modulation. Future work will focus on stratified sampling, empirical validation, and developing personalized metabolic signatures for early diagnosis and precision medicine.PMID:42260510 | DOI:10.1186/s12888-026-08178-8

Respir Res. 2026 Jun 9. doi: 10.1186/s12931-026-03731-1. Online ahead of print.ABSTRACTBACKGROUND: Acute respiratory failure remains a major challenge in critical care, and early identification of patients at risk of clinical deterioration is essential. Metabolomics provides a systems-level characterization of disease severity but its clinical implementation is limited by the need for high-resolution Nuclear Magnetic Resonance (NMR) infrastructure. Benchtop NMR offers a compact and potentially scalable alternative. This study aimed to identify serum metabolic signatures associated with respiratory severity and evaluate agreement between benchtop and high-resolution NMR platforms.METHODS: Serum samples from COVID-19 patients with acute respiratory failure were classified by respiratory severity (mild, moderate, severe, and very severe). Metabolomic profiling was performed using 500 MHz high-resolution and 80 MHz benchtop NMR systems. Multivariate analyses were used to identify severity-associated metabolic signatures, assess cross-platform agreement, and evaluate associations with clinical variables.RESULTS: Both platforms identified consistent metabolic alterations across severity groups. Supervised models achieved accurate discrimination between hospitalized and non-hospitalized patients and between moderate and very severe cases. Twenty-one metabolites, including glutamine, citrate, lactate, phenylalanine, myo-inositol, glycerol, and trimethylamine N-oxide, contributed to group separation. Altered pathways included carbohydrate metabolism, amino acid turnover, lipid metabolism, and tricarboxylic acid cycle intermediates, consistent with hypoxia and immune activation. Several metabolites correlated with inflammatory markers, immune cell counts, and oxygenation parameters. Importantly, benchtop NMR reproduced the key metabolic patterns observed with high-resolution NMR.CONCLUSIONS: Serum NMR metabolomics identifies metabolic signatures associated with respiratory severity. The agreement between high-resolution and benchtop NMR supports the feasibility of benchtop systems for clinically accessible patient stratification in acute respiratory disease, with potential applicability beyond COVID-19.PMID:42260468 | DOI:10.1186/s12931-026-03731-1

BMC Cancer. 2026 Jun 8. doi: 10.1186/s12885-026-16232-7. Online ahead of print.ABSTRACTA comprehensive understanding of the underlying molecular mechanisms of prostate cancer is essential for the development of precise diagnostic biomarkers. In this study, we applied the unsupervised multi-omics factor analysis framework (MOFA) to integrate DNA methylation, gene expression, and metabolic profiles derived from the same individuals, aiming to characterize the biological landscape of normal, malignant, and aggressive prostate tissue. Our analysis identified distinct molecular pathways associated with aggressive disease, specifically those involved in zinc metabolism, cell cycle regulation, smooth muscle architecture, immune activation, and tissue morphology. Key metabolites within the TCA cycle, amino acid metabolism, and lipid pathways were central to these signatures. Furthermore, we observed a consistent co-enrichment of SP1 and CTCFL binding regions among factor-associated CpGs, suggesting a model of global epigenetic reprogramming. These findings indicate a novel interplay between Polycomb deregulation, CTCFL-mediated chromatin remodeling, and SP1-driven transcriptional activation in shaping the prostate cancer epigenome. Apart from immune activation, the identified molecular signatures were validated in the TCGA cohort and demonstrated significant predictive value for disease recurrence. Overall, these results underscore the power of multi-omics integration in providing a holistic understanding of prostate cancer biology and its potential for clinical translation into prognostic biomarkers.PMID:42260416 | DOI:10.1186/s12885-026-16232-7

Clin Proteomics. 2026 Jun 8. doi: 10.1186/s12014-026-09614-3. Online ahead of print.ABSTRACTBACKGROUND: Tuberculosis (TB) remains a global health threat, affecting over a million children under the age of 15 annually. Many children with TB do not receive treatment due to challenges in diagnosis.METHODS: We performed a multi-omics analysis for pediatric TB by integrating plasma proteomics and metabolomics data from children with presumptive TB across four high-burden countries. Pathway enrichment analysis was conducted using multiGSEA to identify relevant immune and metabolic pathways. We also applied mixOmics and multiview approaches for diagnostic biomarker discovery and compared the performance of multi-omics signatures with those derived from single-omics datasets.RESULTS: Enrichment analysis revealed several immune and metabolic pathways, including PTEN and RUNX2 regulation pathways, as well as arginine and proline metabolism, that were uniquely identified through data integration. While the multi-omics model showed marginal improvement over single-omics models, proteomics alone generally outperformed metabolomics and demonstrated greater potential for accurately classifying Confirmed TB versus Unlikely TB in children.CONCLUSION: These findings demonstrate the advantage of combining complementary molecular layers to gain a deeper understanding of disease mechanisms and highlight the potential of proteomics for improving pediatric TB diagnosis.PMID:42260364 | DOI:10.1186/s12014-026-09614-3

BMC Microbiol. 2026 Jun 8. doi: 10.1186/s12866-026-05279-y. Online ahead of print.ABSTRACTBACKGROUND: The ABC-type oligopeptide transporter (Opp system), composed of five subunits (OppA-F), plays an essential role in microbial fitness and survival by mediating the uptake of short peptides. Paradoxically, although the probiotic strain Escherichia coli Nissle 1917 (EcN) harbors multiple Opp systems, it exhibits a defect in the import of oligopeptides comprising three or more amino acids, a limitation that may compromise its ability to colonize the intestinal tract. This functional paradox underscores the need for further investigation into the substrate specificity and physiological roles of Opp systems in EcN.RESULTS: Genomic analysis identified four putative Opp systems in EcN, which exhibited low mutual homology (< 41% amino acid identity across all OppA-OppF components), indicating potential functional divergence. Deletion or overexpression of one of the operons, oppABCDF-1 (ECOLIN_07295-07315) did not alter EcN growth under standard or oligopeptide-supplemented conditions. Untargeted metabolomics further demonstrated that this operon was dispensable for oligopeptide uptake. Notably, metabolic profiling revealed significantly impaired uptake of three metabolites in the oppABCDF-1 deletion mutant, along with a modest reduction in the export of putrescine, austinoneol, and leucinic acid. These findings suggest that this Opp system may function as a bidirectional transporter with differential import and export activities.CONCLUSION: These findings indicate that the oppABCDF-1 operon encoded by ECOLIN_07295-07315 in EcN is dispensable for oligopeptide assimilation, but may contribute to the transport of specific metabolites, offering new insights into the functional diversification of bacterial Opp systems.PMID:42260344 | DOI:10.1186/s12866-026-05279-y

BMC Plant Biol. 2026 Jun 8. doi: 10.1186/s12870-026-09101-9. Online ahead of print.ABSTRACTThe Variable-frequency (VF) fan regulation is a promising technique for flue-curing of tobacco (Nicotiana tabacum L.), and exploring its mechanism is of great significance for improving the curing quality. The middle leaves of "Yunyan 87" were used as experimental materials for exploring the changes of metabolic components by untargeted metabolomics and monitoring dynamic changes of key physiological indicators during flue-curing, VF curing (dynamic frequency: 35-40-45-40 Hz) and constant-frequency curing (50 Hz, CK). VF treatment resulted in a more uniform yellowing process, reduced leaf browning, and improved color retention compared with the control. Leaves under VF treatment showed enhanced superoxide dismutase (SOD), peroxidase (POD), and polyphenol oxidase (PPO) activities, accompanied by lower malondialdehyde (MDA) accumulation. At 48 h, Pathway enrichment analysis revealed the glyoxylate and dicarboxylate metabolism pathway was most affected, with significantly enriched metabolites including isocitrate, citric acid, and glyoxylate. At 120 and 168 h, the most significant metabolic pathways affected by variable frequency fan were flavonoid and flavanol biosynthesis, accompanied significantly enrichment of kaempferol, quercetin, and quercetin. Notably, total aroma substances were reduced under VF (Neophytadiene - 42%, benzaldehyde - 28%). This study provided a metabolomics-based framework for improving intensive curing processes.PMID:42260339 | DOI:10.1186/s12870-026-09101-9

Cell Death Differ. 2026 Jun 8. doi: 10.1038/s41418-026-01763-0. Online ahead of print.ABSTRACTThe mechanisms that mediate endocrine therapy resistance remain incompletely understood. We identified promyelocytic leukemia protein isoform 1 (PML1) as a central node of this resistance. We established a PML1 gene signature that strongly correlates with PI3K, MAPK, and endocrine resistance signatures across multiple patient cohorts, predicting poor clinical outcomes. Mechanistically, PML1 promotes a self-reinforcing survival circuit by inducing the expression of CCL5 and HBEGF, which activate PI3K and MAPK signaling in an autocrine/paracrine manner. Reciprocally, ERK activation stabilizes PML1 protein, whereas activated mTOR increases PML1 protein synthesis, thereby establishing a positive feedback loop that sustains cancer cell survival under therapeutic pressure. Paradoxically, selective ER degraders (SERDs) and modulators (SERMs) induce PML1 protein accumulation. Fulvestrant, a SERD, while inducing ER protein degradation, rapidly activates PI3K and MAPK pathways, driving PML1 protein accumulation. Consistently, we observed an inverse relationship between ER and PML protein levels. In therapy-sensitive wild-type ER cells with low basal PML1 levels and PI3K/MAPK activity, fulvestrant's ER-suppressive effects overcome drug-induced elevated PML1 and PI3K/MAPK activity, thereby maintaining therapeutic efficacy. In contrast, in therapy-resistant ER Y537S mutant cells or cells with PML gene amplification, fulvestrant-mediated amplification of constitutively hyperactive PML1-PI3K/MAPK feedback loops dominates over cytotoxic effects, resulting in enhanced cell survival. Notably, reducing PML1 levels through knockdown or arsenic trioxide (ATO), an FDA-approved PML1 degrader, disrupts this resistance circuit and restores endocrine sensitivity. Treatment of ATO resensitizes ER Y537S-bearing resistant tumors to endocrine therapy in xenograft models. These findings establish PML1 as a central hub of resistance, linking ER signaling to the activation of the PI3K/MAPK survival pathway.PMID:42260104 | DOI:10.1038/s41418-026-01763-0

Arch Toxicol. 2026 Jun 8. doi: 10.1007/s00204-026-04466-0. Online ahead of print.ABSTRACTPolyhexamethylene guanidine phosphate (PHMG-p), a cationic disinfectant previously used in humidifiers, has been linked to severe pulmonary diseases in Korea. This study aimed to elucidate the molecular mechanisms underlying PHMG-p-induced lung toxicity using an integrated multi-omics approach. BALB/c mice were intratracheally instilled with PHMG-p (0, 0.03, 0.1 mg/kg, twice weekly for 4 weeks). Histopathology revealed dose-dependent pulmonary lesions, including inflammatory infiltration, alveolar wall hyperplasia, and fibrosis. Transcriptomic profiling identified 213 and 1,506 differentially expressed genes (DEGs) in the low- and high-dose groups, respectively, with enriched pathways related to immune activation, cytokine signaling, and cellular stress responses. Proteomic analysis detected 148 and 1,168 differentially expressed proteins (DEPs), many of which overlapped with DEGs and were associated with chemokine signaling, protein refolding, and ion transport dysregulation. Metabolomic profiling of serum samples identified dose-responsive alterations in amino acid and energy metabolism, with notable increases in glutamate, leucine, serine, and related metabolites. Integrated omics analysis revealed consistent up-regulation of CDKN1A, HSP90AA1, HSPA1A, HSPA8, and HSPH1, and down-regulation of FPR1, suggesting their roles as potential biomarkers of PHMG-p-induced pulmonary injury. Pathway convergence indicated activation of inflammatory and fibrotic remodeling processes, as well as metabolic reprogramming involving glutamate and branched-chain amino acid pathways. These findings provide mechanistic insight into PHMG-p-induced lung toxicity and highlight multi-omics signatures that may serve as biomarkers for monitoring or predicting pulmonary damage caused by cationic polymer biocides.PMID:42259956 | DOI:10.1007/s00204-026-04466-0

Commun Chem. 2026 Jun 8. doi: 10.1038/s42004-026-02087-3. Online ahead of print.ABSTRACTSAM-dependent methyltransferases are enzymes that catalyze the transfer of a methyl group from a cofactor to a substrate through an ordered or random sequential bi-bi mechanism. However, the structural dynamics governing binding cooperativity between the cofactor and substrate remain understudied. In this study, we demonstrate that SbSOMT, a plant O-methyltransferase, exhibits bilateral positive cooperativity between the cofactor and substrate, except the unproductive SbSOMT-SAM-pterostilbene complex. Furthermore, SbSOMT displayed substrate-binding kinetics that shift in response to the nature of bound-cofactor. Sinefungin-bound SbSOMT exhibited positive cooperativity primarily attributed to an increased substrate association rate constant (kon), whereas SAH-bound SbSOMT displayed positive cooperativity driven primarily by a decreased dissociation rate constant (koff). Structural analysis implies that these cooperativity switch and divergent binding kinetics stem from the interactions between the cofactor and substrate at the methyl binding site. Integrating structural insights reveals that a dynamic W279 π-stacking network governs this cooperativity. Upon binding of the first ligand, H196, W279, and H282 rearrange to form a π-stacking network, in which W279 serves as the essential central plane that also stacks with the substrate. Accordingly, W279A mutagenesis substantially impaired the substrate affinity, cooperativity and enzymatic activity.PMID:42259925 | DOI:10.1038/s42004-026-02087-3

J Clin Lipidol. 2026 May 22:S1933-2874(26)00363-6. doi: 10.1016/j.jacl.2026.05.225. Online ahead of print.ABSTRACTBACKGROUND: An elevated level of lipoprotein(a) (Lp[a]) is a genetically-determined cardiovascular risk factor. A size polymorphism in its apolipoprotein(a) (apo[a]) component, expressed as kringle (K) 4 repeat numbers, is a major contributor to variability in levels. While chronic kidney disease (CKD) increases Lp(a) levels, less is known about its effect on Lp(a) molecular properties.OBJECTIVE: To assess and compare Lp(a) lipidomic properties in patients with CKD and controls.METHODS: We assessed and compared Lp(a)-lipidomic properties in 54 nondiabetic, nondialysis patients with CKD and 39 controls. CKD was defined by an estimated glomerular filtration rate of <60 mL/min/1.73 m2.RESULTS: The mean age of the cohort was 63 years, 48% were women, and 77% were of European descent. Lp(a)-bound oxidized phospholipids (Lp[a]-OxPL) concentrations were higher in patients with CKD vs controls (median [IQR] 2.7 [0.5; 7.4] vs 1.2 [0.5; 3.4] U/L, P = .031), in particular for the medium (23-27 K repeats) apo(a) size range (P = .002). Among Lp(a)-OxPL subspecies, 1-palmitoyl-2-(5'-oxo-valeroyl)-sn-glycero-3-phosphocholine relative abundance was significantly higher in patients with CKD compared to controls (21% vs 16%, P = .0004). Of the 437 individual lipid species in Lp(a), 146 species primarily representing diacylglycerols (P = .009), acylcarnitines (P = .003), and triacylglycerols (P = .005) showed significantly higher abundance in patients with CKD vs controls. This pattern remained unchanged after adjusting for differences in Lp(a) levels, indicating an impact of the CKD condition on Lp(a) lipidomic properties.CONCLUSION: Among individuals without diabetes, kidney impairment was characterized by higher Lp(a)-OxPL concentrations and proinflammatory Lp(a)-lipidomic properties. Mechanisms underlying these changes and relevance to cardiovascular risk warrant further investigations.PMID:42259745 | DOI:10.1016/j.jacl.2026.05.225

Nutr Metab Cardiovasc Dis. 2026 May 26:104810. doi: 10.1016/j.numecd.2026.104810. Online ahead of print.ABSTRACTBACKGROUND AND AIMS: Metabolomic signatures representing a "healthy" and "unhealthy" dietary pattern have previously been constructed using data from a randomised controlled crossover feeding study (DQFS). The utility of these metabolomic signatures in other populations has not been evaluated. Here, we mapped changes in diet-derived plasma metabolites in a sample of rural adults screened as at elevated-cardiovascular disease (CVD) risk receiving medical nutrition therapy (MNT), against the DQFS dietary metabolite signature.METHODS AND RESULTS: A sub-sample of MNT participants (n = 11) received personalised MNT from a dietitian over 6-months. Plasma metabolites for DQFS and HRH were analysed using ultra-high performance liquid chromatography-tandem mass spectrometry. Restricted maximum likelihood mixed-effect models were used to evaluate change in metabolites and dietary intake across the MNT intervention. Principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) plots were used to compare metabolite profiles between both studies. Five metabolites significantly changed between baseline and either the 3- or 6-month, with two metabolites [Ethylmalonate and Glycosyl-N-stearoyl-sphingosine (d18:1/18:0)] significantly reduced at both 3- and 6-months. Diet quality significantly increased across the intervention (p < 0.001). PCA and PLS-DA plots identified that post MNT intervention 3- and 6-month metabolic signatures aligned more closely with the "healthy" dietary pattern signature.CONCLUSION: Findings demonstrated that the metabolomic signature identified in the controlled DQFS feeding study can be used to map changes in diet quality in response to an MNT intervention in people at an elevated CVD risk. Future studies in larger, independent cohorts are warranted.PMID:42259719 | DOI:10.1016/j.numecd.2026.104810

J Immunother Cancer. 2026 Jun 8;14(6):e015116. doi: 10.1136/jitc-2026-015116.ABSTRACTBACKGROUND: Cholangiocarcinoma (CCA), a malignancy arising from biliary epithelial cells, features a tumor microenvironment (TME) characterized by metabolic dysregulation and immunosuppression. Although diverse metabolic aberrations have been observed, the dominant metabolic driver remains unclear. Therefore, the study aims to elucidate the molecular connections between metabolic reprogramming and immune evasion, and to provide the basis for developing TME-targeted therapies.METHODS: First, untargeted metabolomics was performed to identify key metabolite classes involved in CCA progression. We subsequently used next-generation sequencing combined with database analysis to identify the key genes involved in tumor fatty acid metabolism. Metabolomics, proteomics and metabolic phenotyping experiments were subsequently performed to investigate this metabolic process. Tumor malignancy was evaluated using a range of in vitro and in vivo models. Single-cell RNA sequencing, Olink proteomics, flow cytometry and multiplex immunohistochemistry were performed to analyze the changes in the TME. Finally, we used humanized NOG mice to evaluate the efficacy of the combination therapy.RESULTS: Integrated multi-omics analysis revealed that long-chain unsaturated fatty acids (LCUFAs) were enriched in CCA tissues and closely associated with tumor progression. Ubiquitin-specific peptidase 1 (USP1) was upregulated in CCA tissues, driving dynamic lipid metabolic reprogramming and was associated with poor prognosis. Mechanistically, USP1 orchestrated LCUFAs accumulation through coordinating the enhancement of lipophagy and lipogenesis, establishing a systems-level metabolic regulatory network. Tumor-secreted LCUFAs were preferentially internalized by tumor-associated macrophages (TAMs) through FABP5, thereby suppressing cytotoxic T cells activity. Additionally, TAMs upregulated USP1 in CCA cells, forming a positive feedback loop that perpetuates the metabolic-immune crosstalk.CONCLUSION: In summary, based on multi-omics analysis, this study establishes a systemic mechanism that links tumor lipid metabolism, immune suppression, and therapeutic response in CCA. Targeting the USP1-mediated metabolic-immune axis not only significantly suppresses tumor progression but also enhances the efficacy of immunotherapy. These findings construct a conceptual framework that integrates metabolic reprogramming, immune evasion, and treatment sensitivity, thereby establishing USP1 as a precision therapeutic target with broad biological and clinical importance for patients with CCA.PMID:42259603 | DOI:10.1136/jitc-2026-015116

J Nutr. 2026 Jun 7:101652. doi: 10.1016/j.tjnut.2026.101652. Online ahead of print.ABSTRACTBACKGROUND: Western-style dietary patterns are associated with colitis and colon cancer. Existing data indicate intake of apiaceous vegetables (API; e.g., celery, parsnip) may prevent inflammation-associated diseases.OBJECTIVE: We investigated in mice the effect of API supplementation to the Total Western Diet (TWD) against dextran sulfate sodium (DSS)-induced colitis.METHODS: Male C57BL/6J mice (8-week-old; 15/group) were fed TWD supplemented with 21% or 42% fresh API (w/w) and given 2% DSS to induce colitis. Diet intake, body weight, and disease activity index (DAI) were monitored. Serum was collected for cytokine/chemokine analysis and colonic tissues for histology and Western blot. Fecal samples were analyzed by 16S rRNA gene sequencing and targeted/untargeted metabolomics. Phenotypic data were analyzed by ANOVA with Tukey's test. Microbiome data were Centered-Log Ratio (CLR) transformed and analyzed using linear mixed models with adjusted pairwise comparisons.RESULTS: API supplementation attenuated colitis phenotypes including weight loss (44% recovery; P < 0.001), colon shortening (57% recovery; P < 0.01), disease activity (59% lower; P < 0.001), cytokine/chemokine release (35-73% reductions; P < 0.05), and mucosal F4/80+ cells infiltration (80% reduction; P < 0.001). API also improved gut microbiota diversity and composition, increasing alpha diversity metrics (4.4%-13.8%; P <0.05), suppressing pathogenic bacteria (Paraclostridium, Enterococcus, Eubacterium; estimated CLR difference: -1.8 to -6.7; P < 0.001), and enriching beneficial bacteria (Lachnospiraceae and Blautia; estimated CLR difference: +1.6 to +3.0; P < 0.05). Furthermore, metabolomics indicated TWD consumption increased arachidonic acid and aliphatic aldehydes (by 109%-510%; P < 0.001), and decreased short-chain and unsaturated fatty acids (by 30%-91%; P < 0.001). API supplementation also mitigated TWD-derived functional metabolites (including bile acids; P < 0.05).CONCLUSIONS: These data indicate that API intake is beneficial for risk reduction of diseases associated with Western diets. However, further investigations are warranted to determine the mechanism behind these beneficial effects.PMID:42259440 | DOI:10.1016/j.tjnut.2026.101652

Clin Chim Acta. 2026 Jun 7:121162. doi: 10.1016/j.cca.2026.121162. Online ahead of print.ABSTRACTBACKGROUND: It is urgent to find novel non-invasive biomarkers that can accurately diagnose alcohol-associated liver disease (ALD). The objective of this study was to explore dysregulated metabolites in the serum of ALD patients by metabolomics, and establish a reliable diagnostic model by machine learning algorithms.METHODS: A total of 1800 participants, including ALD, metabolic dysfunction-associated steatotic liver disease (MASLD), chronic hepatitis B (CHB), alcohol use disorder (AUD) and normal control (NC) individuals were recruited from four medical centers. Steroid hormone and bile acid metabolism was identified to be dysregulated in ALD in the discovery cohort by untargeted metabolomic analysis, and further confirmed in the training cohort by absolute quantitative metabolomic analysis. A machine learning model named "Bashald" was built based on the training cohort, and further validated in three independent validation cohorts.RESULTS: Our Bashald model exhibited great diagnostic performance with an AUC of 0.942 (95% CI, 0.880-1.000) in an internal test subset. In the validation cohorts, Bashald maintained good predictive performances, with the AUCs of ≥0.821 for diagnosing ALD. In addition, Bashald demonstrated superior performance for the detection of early-stage ALD patients, with the AUCs of 0.870 and 0.792 for the training cohort and validation cohort 2, respectively, which had greatly surpassed traditional clinical indicators.CONCLUSIONS: Our research uncovered the specific metabolic profile of ALD and identified a distinct set of biomarkers that facilitate early detection, thereby promoting the application of precision diagnosis for ALD.PMID:42259427 | DOI:10.1016/j.cca.2026.121162

Chemosphere. 2026 Jun 8;407:144975. doi: 10.1016/j.chemosphere.2026.144975. Online ahead of print.ABSTRACTPerovskite nanomaterials are increasingly used in energy storage, catalysis, and sensing, but their effects on human health and the environment remain poorly understood, especially for newer types. This study presents the first direct comparison of two emerging perovskites, nickel-titanate (NiTiO3) and calcium-manganite (CaMnO3) tested simultaneously in human epithelial cells (A549) and Escherichia coli bacteria, providing a dual-host perspective on their biological impact. The materials differed notably in shape and size: NiTiO3 formed smooth, spherical-like particles (∼367 nm), while CaMnO3 had irregular, sharp-edged structures (∼588 nm). Neither caused destruction of red blood cells up to 400 μg/mL, although CaMnO3 induced visible deformation. In human cells, CaMnO3 was more toxic, causing oxidative stress, DNA damage, and activation of inflammatory and cell-death pathways. In bacteria, both nanomaterial increased cell membrane permeability, oxidative stress, with CaMnO3 showing stronger bactericidal effects. Metabolomic analysis of bacterial and human cells via NMR revealed NiTiO3 disrupted amino acid and energy metabolism primarily. Surprisingly, CaMnO3 caused broader but moderate metabolic changes., whereas NiTiO3 caused greater metabolic disruption despite being less lethal, suggesting that cell death and metabolic harm are not always correlated. Notably, both nanomaterials significantly enhanced horizontal gene transfer between bacteria, especially via outer membrane vesicles, raising concerns about accelerating antibiotic resistance spread. Overall, small differences in composition and shape led to vastly different biological outcomes. This study establishes a cross-species testing framework for nanomaterial safety and underscores the importance of biosafety considerations in developing next-generation perovskites. Environmental implication: This study highlights important environmental concerns associated with the growing use of perovskite nanomaterials. Once released into air, water, or soil, NiTiO3 and CaMnO3 may interact with human cells and beneficial microbial communities. CaMnO3 showed higher toxicity in human cells and bacteria, while both nanomaterials significantly increased horizontal gene transfer, which may accelerate the spread of antibiotic resistance in the environment. Such changes can affect ecosystem balance and public health. These findings emphasize the need for responsible production, controlled disposal, and rigorous environmental risk assessment before the large-scale application of perovskite nanomaterials.PMID:42259126 | DOI:10.1016/j.chemosphere.2026.144975