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Abstract: While reusing treated wastewater (TWW) for irrigation provides a sustainable solution to water scarcity, it can potentially introduce contaminants that may threaten crop safety and quality. Consequently, further research is needed to understand the effects of TWW on the metabolomic and elemental profiles of irrigated crops. This study investigated how using TWW affect metabolism and element uptake in tomatoes grown in soil (lysimeters) and soilless (hydroponics) systems. Soil-grown tomatoes were irrigated with potable water, treated wastewater, and treated wastewater spiked with 14 CECs (0.1 mg/L), which included bisphenols, non-steroidal anti-inflammatory drugs, estrogens, and caffeine. Hydroponically grown tomatoes were grown in a nutrient solution, with or without CECs. Tomatoes were assessed by analysing sugars, organic acids, polyphenols, carotenoids, amino acids, fatty acids, and elements. Classification machine learning models were applied, and the best-performing model, a decision tree classifier, achieved 88% accuracy in distinguishing treatments under stratified five-fold cross-validation. The SHAP method identified key metabolites (ascorbic, palmitic, margaric, oleic, linoleic, behenic acids) and elements (Cd, Co, Cs, Cu, P, Na) that drive treatment differentiation. This study demonstrates how explainable machine learning can decode complex metabolic interactions, providing insights into the effects of using treated wastewater in agriculture.
Keywords: contaminants of emerging concern, metabolites, explainable machine learning
Published in DiRROS: 04.09.2026; Views: 60; Downloads: 47
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Abstract: Background. Exposure to per- and polyfluoroalkyl substances (PFAS) and phthalates is widespread during adolescence, a critical developmental period for metabolic regulation. Aim. To assess associations of serum PFAS and urinary phthalate/DINCH metabolites-individually and as mixtures-with a unified panel of metabolic biomarkers representing adipose-brain-liver cross-talk and oxidative stress in European teenagers. Methodology. Serum PFAS and urinary phthalate/DINCH metabolites were measured in 1033 European teenagers (12–17 years) from the Human Biomonitoring Initiative for Europe (HBM4EU) Aligned Studies. Metabolic biomarkers representing adipose (HDL, LDL, cholesterol, and triglycerides)-brain (leptin, adiponectin, and kisspeptin)–liver (glucose, insulin) cross-talk and oxidative stress (8-hydroxy-2′-deoxyguanosine, 8OHdG) were measured. The Body Mass Index z-score (zBMI) was calculated. Single pollutant models, multivariate MANOVA, quantile g-computation, and BKMR models were fit, including interaction terms with sex. Results. Single pollutant models showed positive associations of PFAS and phthalate/DINCH metabolites with 8OHdG. PFAS were associated with higher leptin, HDL, LDL, and cholesterol, while some phthalate/DINCH metabolites were associated with lower kisspeptin, HDL, triglycerides, cholesterol, zBMI, and higher adiponectin. We observed weak but statistically significant associations between PFAS and phthalate/DINCH metabolites with the entire set of metabolic biomarkers in the MANOVA. The PFAS mixture was associated with higher kisspeptin, LDL, HDL, cholesterol, and 8OHdG. The phthalate/DINCH mixture was associated with lower HDL. Conclusions. Exposure to these contaminants may be related to dyslipidemia in teenagers. PFAS and phthalate/DINCH metabolites may exert opposite associations on metabolism, with the exception of increasing oxidative stress. Given the cross‑sectional design and potential residual confounding, longitudinal studies are warranted.
Keywords: human biomonitoring, DINCH metabolites, HBM4EU, metabolic regulation, perfluoroalkyl substances, polyfluoroalkyl substances
Published in DiRROS: 16.06.2026; Views: 292; Downloads: 367
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Abstract: Autism spectrum disorder (ASD) has been associated with alterations in the gut microbiota and its metabolites, particularly short-chain fatty acids (SCFAs) and microbiota-derived tryptophan catabolites, which may influence neurodevelopment through immune and epigenetic mechanisms. We investigated whether stool SCFAs and tryptophan-pathway metabolites differ between children with ASD and typically developing controls, and whether these metabolites associate with ASD severity and systemic biochemical signatures. In this cross-sectional study, we analyzed stool samples from 229 children (160 with ASD, 69 controls) with complete SCFA and tryptophan-metabolite data, while urine metabolomics data were available for a subset and were used for exploratory stool–urine integration analyses. Children with ASD and controls were similar in age, but the ASD group had a higher proportion of males. Absolute concentrations of individual SCFAs, total SCFAs, and derived indices were broadly comparable between groups; nominal differences in propionate/acetate ratio and caproate did not remain significant after false discovery rate correction. Similarly, stool tryptophan-pathway metabolites reported as ng/a.u. based on the NanoDrop-derived proxy (tryptophan, kynurenine, indole-3-acetic, indole-3-lactic, indole-3-propionic, indole-3-aldehyde, N-acetyl-tryptophan, serotonin, melatonin, tryptamine) and functional ratios (kynurenine/tryptophan, indole-derived/tryptophan, serotonin/tryptophan) showed no robust ASD–control differences; N-acetyl-tryptophan was nominally higher in ASD but did not survive multiple-testing correction. In the ASD subgroup with available Childhood Autism Rating Scale (CARS) data (n = 34), SCFA and tryptophan indices showed only weak, non-significant correlations with global ASD severity. In contrast, correlation analyses revealed two coherent metabolic modules, i.e., an SCFA block with very strong internal correlations among individual SCFAs and total SCFAs and a tryptophan block with strong correlations between metabolites and their normalized ratios, while cross-module correlations were modest. These results indicate that stool SCFA and microbiota-derived tryptophan profiles do not robustly distinguish ASD from controls in this cohort, but they form stable metabolic modules compatible with microbiome–epigenome frameworks.
Keywords: autism spectrum disorder, gut microbiota, short-chain fatty acids, tryptophan metabolism, indole metabolites, kynurenine pathway, epigenetics, microbiome–epigenome interaction, metabolomics, pediatrics
Published in DiRROS: 05.05.2026; Views: 373; Downloads: 281
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Keywords: biological control, antagonistic fungi, antagonistic bacteria, secondary metabolites, non-chemical control, gry moul
Published in DiRROS: 13.01.2026; Views: 561; Downloads: 318
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Abstract: Idiopathic nephrotic syndrome (INS) is the most prevalent glomerular illness in children. Even while immunologic processes are well-established, oxidative stress is becoming more widely acknowledged as a significant factor in the etiopathogenesis of illness. Assessing its activity and treatment response may be made easier with the use of trustworthy, non-invasive indicators to track redox balance. We report on the oxidative stress levels of a 10.7-year-old boy with INS with five clinical time points in one year. The FRAS5 analyzer was used to calculate the oxidative stress index (OSI), plasma antioxidant capacity (PAT) and derivatives of reactive oxygen metabolites (d-ROMs) as biomarkers. A 4-tier oxidative state classification scheme based on d-ROM and PAT thresholds was used to interpret the values. The patient had low antioxidant defense, moderate oxidative and increased OSI at relapses, a positive transition to reduced oxidative burden and enhanced defense during remission. The order of events showed a dynamic redox response associated with glucocorticoid (GC) medication and disease activity. The potential value of d-ROM, PAT, and OSI as dynamic biomarkers for tracking disease activity, response to treatment and residual oxidative burden in pediatric INS is supported by this case. To confirm their function in more comprehensive clinical decision-making, more research is required.
Keywords: idiopathic nephrotic syndrome, children, derivatives of reactive oxygen metabolites, plasma antioxidant capacity, oxidative stress index
Published in DiRROS: 06.01.2026; Views: 673; Downloads: 533
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