Abstract in English:

New psychoactive substances (NPS) have become a global challenge due to their rapid emergence, structural variability, and capacity to evade conventional drug regulations. Developed to mimic the effects of controlled substances, these compounds often exhibit unpredictable pharmacological properties and complex metabolic pathways, complicating forensic detection and toxicological assessment. In this context, metabolomics has emerged as a powerful analytical strategy to investigate the biochemical consequences of NPS exposure, allowing the identification of endogenous metabolic disturbances and affected pathways. When integrated with advanced chemometric methods, metabolomics offers valuable insights into mechanisms of toxicity, supports the discovery of exposure and effect biomarkers, and improves the understanding of interspecies variability in toxic responses. This review summarizes original research articles (n = 19) published between 2015 and 2025, evaluating several NPS classes such as synthetic cathinones, synthetic cannabinoids, tryptamines, synthetic opioids, and other emerging psychoactive compounds, demonstrating the current applications of metabolomics in NPS research. Therefore, this work emphasizes the contribution of metabolomics to toxicological, pharmacological, and analytical investigations of NPS, outlining key findings related to their mechanisms of action and toxicity, as well as perspectives for future research.

Abstract in English:

Although Anacardium humile and Anacardium occidentale fruits are widely consumed in Brazil, quantitative data on their bioactive compound content remain scarce. This study aimed to develop and validate a high-performance liquid chromatography mass spectrometry (HPLC-MS/MS) method for the targeted quantification of 12 metabolites and to assess their antioxidant potential. Twenty-four mature fruit samples were collected from individual trees and purchased from open-air markets in Goiás and the Federal District over three different weeks (during September and October) and were analyzed using a validated method (r > 0.99; relative standard deviation (RSD) < 12.84%; recovery 88-111%). Ascorbic acid was the predominant compound in both species, although notable interspecific differences were observed for catechin, isoquercetin, and gallic acid. Principal component analysis (PCA) confirmed distinct chemical profiles between species. Antioxidant activity varied significantly, with the effective concentration (EC50) values ranging from 65.67 to 381.94 g fruit per g 2,2-diphenyl-1-picrylhydrazyl (DPPH) for A. occidentale and from 85.37 to 227.62 for A. humile. These findings underscore the importance of robust analytical techniques for characterizing the complex phytochemistry of native Brazilian fruits.

Abstract in English:

Atopic dermatitis (AD) is a chronic inflammatory skin condition marked by impaired epidermal barrier function and substantial alterations in lipid homeostasis. While previous metabolomics studies have characterized major lipid classes involved in skin physiology, the contribution of N-acyl lipids and related molecules to AD remains poorly defined. In this study, an integrative reanalysis of the public mass spectrometry interactive virtual environment (MassIVE) dataset is performed combining fold-change statistics, global natural product social molecular networking (GNPS), and fast mass spectrometry search tool (fastMASST). Among the 6,332 mass spectrometry (MS) features detected, 12 were annotated. These compounds were assigned as putative identifications (level 2), based on tandem mass spectrometry (MS/MS) spectral similarity, molecular networking relationships, and in silico fragmentation analysis. Though, their identities were not confirmed with authentic reference standards. The annotated compounds belong to three chemically distinct subclasses: (i) N-acylethanolamines and long-chain amides, (ii) carnitines, and (iii) N-acyl amino acids, dipeptides, and related derivatives. These subclasses exhibited distinct class-specific behavior, characterized by increased levels in AD lesion samples. fastMASST searches further indicated that several of these molecules are widely co-occurring in microbial and personal-care product datasets, providing potential microbiomeand exposome-context for their presence in skin affected by atopic dermatitis. Together, these findings reveal a distinct class-specific signature of N-acyl lipid, carnitines, and amino acids/dipeptides that are associated with the dysregulation in AD, and thereby, demonstrating the power of public data reanalysis to uncover previously overlooked biochemical patterns associated with skin barrier dysfunction.

Abstract in English:

This study aimed to elucidate lipid changes in zebrafish (Danio rerio) samples, providing insights into alterations related to different diets and exercise. Zebrafish subjects were categorized into four groups based on their diet and exercise. In this regard, high performance liquid chromatography coupled to mass spectrometry (HPLC-MS) and chemometric methods were employed for lipid extracts from zebrafish bodies. Partial least squares discriminant analysis (PLS-DA) with ordered predictors selection for discriminant analysis (OPSDA) successfully classified each sample with 100% accuracy. Volcano plots were utilized alongside multivariate analyses to identify variables that were statistically significant. This integrative approach enhances the robustness of our findings, ensuring that the variables selected for interpretation exhibit significance in both multivariate contexts and individual analyses. The most important lipids for classification of each zebrafish group were putatively annotated, providing insights about lipid metabolism changes in different diet and exercise. Findings reveal distinct lipid metabolic responses between sedentary and exercised groups under high-fat diets, highlighting the role of specific lipid classes in obesity-associated pathways and offering insights into potential metabolic targets for obesity management.

Abstract in English:

The impact of passion fruit seed oil (PFSO) supplementation on the liver proteome of broilers exposed to a cyclic heat stress protocol was the focus of this research. Five experimental diets (0, 0.30, 0.50, 0.70, and 0.90% PFSO) were fed to chickens, which underwent 8 h of daily thermal stress in a climate chamber throughout the trial. At 36 days, hepatic samples were procured from nine animals per group. The proteins were resolved via two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and the spots showing differential expression were identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The main discovery was that dietary supplementation with 0.30 and 0.90% PFSO led to increased levels of heat shock protein (HSPs), which provide essential cellular protection during stress. Simultaneously, a pronounced downregulation of antioxidant proteins was observed, suggesting a recalibration of the cellular defense mechanisms. Beyond stress proteins, significant changes were also noted in proteins governing lipid and carbohydrate metabolism, confirming the influence across multiple metabolic pathways of PFSO. These data indicate that PFSO boosted resistance to heat stress through the modulation of critical metabolic functions, presenting valuable implications for improving poultry welfare and performance in adverse environmental conditions.

Abstract in English:

Untargeted metabolomics data are highly complex and variable. One of the major challenges in processing them is ensuring that biological interpretations reflect the organism metabolic variability rather than undesirable factors arising from random or systematic experimental errors. Here, nine post-acquisition normalization strategies were evaluated on two gas chromatography-mass spectrometry (GC-MS) metabolomics datasets (cellular and serum). GC-MS data are particularly affected by experimental variability since derivatization steps are required. Thus, the use of internal standards (IS) is indicated, although not mandatory. When an IS is not available, post-acquisition normalization methods help correct for variations. Mean, median, and EigenMS normalization proved quite suitable for both datasets, as evidenced by good sample and quality control grouping and within-group relative log abundance (RLA). EigenMS was chosen due to its improved sample grouping. Strategies that use a sample as a reference factor for normalization did not demonstrate the same efficiency, as they introduced biases into the multivariate models. This could be due to a poor choice of reference sample, which compromises the fit of the data matrix. The results observed in this study demonstrate the importance of testing different normalization methods in any metabolomics study to help obtain more robust and reliable matrices for data inspection and interpretation.

Abstract in English:

Cri-du-chat syndrome (CDCS) is a rare genetic disorder caused by a partial deletion of chromosome 5. Common features include intellectual disability, developmental delays, microcephaly, and a characteristic high-pitched cry. Although CDCS has been extensively studied from genetic and developmental perspectives, its metabolic implications remain poorly understood. This study aimed to investigate alterations in metabolic pathways involved in the pathological mechanisms of CDCS through urine metabolomic profiling using nuclear magnetic resonance (NMR) spectroscopy. Sixty-three participants were grouped into children, adolescents, and adults. For the first time, an NMR-based metabolomic signature for CDCS was reported, revealing 33 urinary metabolites and providing new insights into syndrome-related biochemical alterations. Statistical analyses revealed significant metabolic alterations compared to control subjects, particularly involving branched-chain and aromatic amino acids, as well as organic acids associated with energy production. Enrichment analysis further highlighted age-specific pathways impacted by the syndrome. In children, pathways related to phenylalanine, tyrosine, and tryptophan biosynthesis and metabolism, as well as butanoate and glyoxylate metabolism, were affected. Adolescents showed prominent alterations in phenylalanine biosynthesis and metabolism, while adults exhibited disruptions in taurine, hypotaurine, beta-alanine, and histidine metabolism. Altogether, these findings demonstrate pervasive impairments in amino-acid metabolism and energy homeostasis, elucidating key biochemical mechanisms that underlie the physiological manifestations of CDCS and highlighting potential metabolic pathways for future therapeutic exploration.

Abstract in English:

Plant growth-promoting yeasts (PGPYs)-based bioinputs offer a sustainable approach in agriculture, increasing crop productivity and reducing environmental impacts. However, their chemical interactions with plants remain poorly understood. In this paper, metabolites and metabolic pathways were deeply investigated in tomato seedling leaves inoculated with active (L01AT) and inactive (L01IN) Sporidiobolus yeast. Yeast was applied near the roots of the tomato seedlings, and agronomic and metabolomic studies were performed after 40 days. A total of 73 metabolites, including primary and secondary, were annotated using mass spectrometry-based metabolomics. Inoculation of the yeast L01AT promotes more intense changes in the biosynthetic pathways of secondary metabolism compounds, such as phenylpropanoid biosynthesis, such as phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, and anthocyanin biosynthesiss. On the other hand, inoculation of the yeast L01IN promotes changes in the primary metabolic pathways, such as lysine biosynthesis and porphyrin metabolism, which are compounds derived from yeast cell degradation after heating. This integrated agronomic, biological, and chemical analysis provides a comprehensive understanding of the metabolic reprogramming induced by Sporidiobolus inoculation in tomato seedlings. These findings contribute to the design of safer and more efficient bioinput strategies and support the discovery of bioactive compounds for advanced formulation development.

Abstract in English:

2,3-Butanedione is widely used as a flavoring, preservative, and fragrance additive, and increasing evidence suggests that chronic exposure may induce molecular alterations in biological systems. This exploratory study investigated the impact of prolonged 2,3-butanedione exposure on the brain proteomic profile of Wistar rats. Thirty-three animals were assigned to three groups: a vehicle-treated control and two exposed groups receiving 46.6 or 99.1 µg kg-1 day-1 via intragastric administration for 90 days. Following euthanasia under deep anesthesia, brain tissues were analyzed by nano-liquid chromatography-mass spectrometry (nano-LC-MS), and the resulting data were evaluated using chemometric approaches. Data processing in Skyline identified 9,296 proteins, of which 2,500 were retained for multivariate analysis. Clear discrimination among experimental groups was observed, even in the absence of sex stratification, indicating that exposure influenced the global brain proteomic profile. Ontological and pathway analyses revealed 78 affected protein classes, with several dysregulated proteins annotated to biological pathways previously implicated in neurological processes. Importantly, these proteomic alterations represent pathway-level associations and do not constitute evidence of neurological disease or pathology. Overall, the findings demonstrate that chronic exposure to 2,3-butanedione modulates brain proteomic patterns and associated molecular pathways, supporting its use as a hypothesis-generating framework for future mechanistic and functional studies.

Abstract in English:

Dried blood samples on filter paper have been used in newborn screening programs for decades and have recently gained attention as a practical alternative to traditional liquid matrices for untargeted metabolomics. This material provides benefits, such as long-term stability and cost-effective transportation, which are particularly valuable for rare disease studies. While dried blood spots are well-established in clinical and research settings, dried urine spots (DUS) remain largely unexplored for untargeted metabolomics, despite their potential as a noninvasive matrix for biomarker discovery. In this study, it was conducted an exploratory untargeted metabolomics investigation using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to analyze DUS samples from individuals with Pompe disease (PD). Using an integrated data analysis strategy that combined univariate testing with multivariate and machine learning methods, 29 metabolites that differed significantly (p < 0.05) between Pompe disease patients and controls were annotated. Of these, six have been previously reported in liquid urine, confirming that DUS is a reliable sampling method for biomarker detection and discovery. In conclusion, our results demonstrate that untargeted LC-HRMS analysis of DUS offers a reliable alternative for urine studies, highlighting specific metabolic changes in Pompe disease and supporting its application in research on rare disorders.

Abstract in English:

The coronavirus disease (COVID-19) pandemic highlighted the need for alternative diagnostic strategies based on accessible and non-invasive technologies. This proof-of-concept study evaluates capillary zone electrophoresis with ultraviolet detection as a data-acquisition platform for exploratory profiling of four urinary organic acids (tartrate, malate, lactate, and succinate) in samples collected from individuals tested by reverse transcription polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Electropherogram data were processed using multiple machine learning algorithms to classify COVID-19-positive and -negative samples. The models included partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), decision tree, random forest, bagged trees, and stochastic gradient descent. Overall performance was moderate: PLS-DA showed limited discrimination, SIMCA achieved high sensitivity but low specificity, and tree-based models demonstrated balanced yet modest accuracy. The best results were obtained with the stochastic gradient descent classifier, reaching 70% accuracy and a Matthews correlation coefficient of 0.41. These findings indicate that urinary organic acid profiles provide only weak discriminatory power for COVID-19 classification. Nonetheless, the workflow demonstrates the feasibility of integrating capillary electrophoresis with machine learning modeling for exploratory, non-invasive metabolomics-based screening.

Abstract in English:

As a major biodiversity hotspot, the Atlantic Forest harbors not only an extraordinary richness of species, but also distinct environments, such as inselbergs, where extreme abiotic conditions drive unique ecological and metabolic adaptations. Within the Atlantic Forest biome, the genus Cololobus, native to southeastern Brazil, is endemic to inselbergs. With an evolving taxonomic circumscription, the genus remains understudied from a chemical perspective. Herein, we investigated the chemical profiles of Cololobus species using liquid chromatography coupled to ultraviolet detection and tandem mass spectrometry (LC-UV-MS/MS) followed by metabolite characterization through in silico tools and manual inspection. Comparative analysis of the metabolic profile revealed interspecific variation, with a high prevalence of phenolic compounds, specifically flavonoids and hydroxycinnamic acid derivatives, and sesquiterpene lactones. These metabolites are widely recognized for their ecological functions, including chemical defense against natural enemies and ultraviolet radiation protection, traits likely critical for survival in inselberg habitats. Our results suggest that species from harsher inselbergs are characterized by greater chemical diversity, likely reflecting adaptation to environmental conditions. Taken together, these findings provide insights into metabolic and ecological variation in plants occurring in extreme habitats of the Atlantic Forest.

Abstract in English:

Propolis exhibits marked chemical diversity driven by botanical sources and environmental conditions, which challenges its classification based solely on geographic origin or color. In this study, 54 propolis samples collected from different microregions of Vale do Jequitinhonha (Minas Gerais, Brazil) were analyzed using an untargeted metabolomics approach by liquid chromatography-mass spectrometry, combined with visible spectroscopy measurements and correlation-based statistical analyses. Multivariate analysis revealed pronounced chemical variability across the dataset, with partial differentiation observed for samples from the Diamantina microregion, while other microregions showed substantial overlap. Visible spectroscopy allowed objective classification of the extracts into green (19 samples), red (5 samples), and other (30 samples), with green samples showing absorption bands mainly around 670 nm and red samples around 495 nm. A total of 77 molecular features were tentatively annotated, predominantly corresponding to phenolic acids, flavonoids, dihydrochalcones, and related phenolic subclasses. Compounds commonly reported as markers of Brazilian green and red propolis, such as artepillin C, caffeoylquinic acid derivatives, liquiritigenin, vestitol, and formononetin, were detected, including samples outside their classical regions of occurrence. Correlation-based integration of metabolomics and spectroscopic data indicated that propolis color arises from the combined contributions of multiple phenolic compounds rather than from a single pigment molecule.

Abstract in English:

Isabelcristinia aromatica is a new monotypic species of a new genus recently described, and belongs to the Linderniaceae family. In order to investigate the phytochemical composition of I. aromatica, high-performance liquid chromatography with diode array detector and electrospray ionization mass spectrometric detection (HPLC-DAD-ESI-MS2) analyses were conducted on crude methanolic extract and methanolic fraction obtained by partition from the dried leaves of the plant species. The putative annotation was carried out using UCSD Global Natural Products Social Molecular Networking (GNPS) and revealed the clustering of various classes of metabolites, including flavonoid glycoconjugates, phenylethanoids, and iridoid glycosides. The results showed the diversity of secondary metabolites in the species, and molecular networking could be considered a useful method for speeding the annotation of secondary metabolites in plant extracts.

Abstract in English:

Understanding the biochemical mechanisms underlying drought tolerance in citrus is essential for developing rootstocks adapted to water-deficit conditions. This study applied proton high resolution magic-angle spinning nuclear magnetic resonance (1H HR-MAS NMR) combined with chemometrics to characterize the metabolism of leaves from conventional non-transgenic (NT) and transgenic (T35S) Swingle citrumelo plants overexpressing the P5CSF129A gene, responsible for proline overproduction. This approach enabled the identification of metabolic alterations throughout stress progression. Transgenic plants exhibited constitutive proline accumulation, accompanied by coordinated modulation of choline, fatty acids, glucose, and sucrose. These adjustments reflect the involvement of nitrogen, carbon, and lipid pathways, conferring osmotic and redox stabilities and supporting the maintenance of metabolic homeostasis under severe water deficit. The combination of 1H HR MAS NMR and chemometrics proved to be a robust, non-destructive chemical tool for elucidating metabolic profiles in genetically modified plants, contributing to the understanding of molecular mechanisms underlying drought tolerance in citrus and supporting the development of rootstocks better adapted to climate change. These findings support the use of 1H HR MAS NMR metabolomics for elucidating drought-response mechanisms and for advancing omics-driven breeding strategies in citrus.

Abstract in English:

This study explores the application of paper spray ionization-mass spectrometry (PSI-MS/MS) in evaluating the metabolomic profiles of lettuce varieties cultivated under soil-based and hydroponic conditions. Compared to electrospray ionization tandem mass spectrometry (ESI-MS/MS), the PSI-MS/MS technique demonstrated improved sensitivity and robust ion signal intensity, allowing effective discrimination between the chemical constituents of the lettuce samples. Significant metabolic differences were identified between the cultivation methods, particularly in the negative ionization mode. PSI-MS/MS provided detailed insights into the chemical composition due to its high sensitivity and minimal sample preparation requirements. The study further analyzed three lettuce varieties (loose leaf, iceberg, and oak leaf) using PSI-MS/MS, revealing distinct ion profiles and variation in ion abundances. Chemometric techniques, including parallel factor analysis (PARAFAC) and partial least squares for discriminant analysis (PLS-DA) with variable selection were utilized to differentiate between lettuce varieties and cultivation methods. This approach highlighted the impact of growing conditions on the metabolic composition of lettuce, identifying key ions such as choline, mannose, and malic acid as significant markers. Overall, the integration of PSI-MS/MS with chemometric tools provides a comprehensive approach for metabolomic profiling, offering valuable insights into the effects of cultivation methods on the nutritional and chemical properties of lettuce. This study underscores the potential of PSI-MS/MS in agricultural and food science research, contributing to the optimization of cultivation practices and the enhancement of crop quality, while also adhering to the principles of green analytical chemistry.

Abstract in English:

The Amazon hosts countless plant species, many still unknown to science. Among catalogued species, hundreds are edible, yet most are rarely consumed or locally restricted. Known in Brazil as PANCs (“Plantas Alimentícias Não Convencionais”), these unconventional food plants, these species can enhance food security, especially for vulnerable populations. Beyond nutrition, studies reveal their nutraceutical potential due to specialized metabolites such as polyphenols, terpenes, and alkaloids, which enable applications in supplements, cosmetics, and herbal formulations. In this context, Theobroma mariae (Mart.) K. Schum., or “cacau-jacaré”, is a little-known fruit-bearing plant with promising applicability. This study annotated its volatile and non-volatile compounds in pulp and seeds using headspace solid-phase microextraction gas chromatography coupled with mass spectrometry (HS-SPME/GC-MS) and ultra-high-performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-HRMS/MS), respectively. A total of 72 volatile and 32 non-volatile compounds were annotated. Fatty acids predominated in the pulp volatilome, whereas theacrine was the main volatile compound in the seeds. Phenolic compounds dominated the non-volatile fraction, notably flavonoid-C-glycosides, O-glycosides, and O-glucuronides. The findings highlight T. mariae as a valuable yet underutilized Amazonian fruit, whose chemical profile resembles that of common cacao and offers potential for novel applications in food, nutraceutical, and cosmetic formulations.

Abstract in English:

Glycosides are widely distributed plant metabolites with remarkable structural diversity and broad biological activities. However, comprehensive strategies for their systematic recognition, extraction, and annotation from complex plant matrices remain scarce, especially for chemically underexplored Amazonian species such as Strychnos jobertiana. In this study, we present an integrated analytical strategy combining leaf spray chemical profiling and feature-based molecular networking (FBMN) analysis to guide extract preparation and enable glycoside annotation from S. jobertiana leaves. Rapid chemical profiling by leaf spray mass spectrometry (LS-MS) enabled the early recognition of glycoside-related ions, including alkaloid and flavonoid derivatives, guiding the preparation of an aqueous extract processed by solid-phase extraction (SPE) before liquid chromatography-mass spectrometry (LC-MS) analysis. The resulting data were explored using FBMN supported by spectral search analysis and manual interpretation of tandem mass spectra. In parallel, the isolation of desoxycordifoline (1), harman-3-carboxylic acid (2), kaempferol 3-O-(2”,6”-di-O-rhamnopyranosyl) glucopyranoside (3), and kaempferol-3-O-neohesperidoside (4) provided structural support for the annotation of molecular clusters. Two major glycoside clusters were characterized, one dominated by flavonoid glycosides, and another composed primarily of monoterpene-derived glycosides. Overall, 21 compounds were annotated, including derivatives related to compounds 1-4, such as secoxyloganin (8), kaempferol-3-O-glucoside (5), kaempferol-3-O-rutinoside (6), and kaempferol-3-O-rungioside (7), and diagnostic fragment ions associated with glycoside compounds were highlighted. This integrated workflow demonstrates the value of LS-MS profiling as a decision-making tool for extract preparation and highlights feature-based molecular networking (FBMN) as a powerful approach for glycoside annotation, contributing to the chemical knowledge of Amazonian plant species.

Abstract in English:

Ocotea odorifera (“canela-sassafras”) has a rich history in the traditional medicine of Brazil for treating inflammatory conditions such as edema, arthritis, and fever. Ethnobotanical records indicate that leaves are commonly prepared by decoction to relieve inflammatory conditions. This research applied metabolomics strategies to investigate how seasonal variation influences the chemical composition and anti-inflammatory activity of O. odorifera leaf essential oils (EOs). Leaves were collected monthly over one year, and EOs were extracted via hydrodistillation. Gas chromatography-mass spectrometry (GC-MS) was applied for EOs chemical composition identification. The EOs were assessed using an ex vivo anti-inflammatory assay, measuring prostaglandin E2 (PGE2) levels in lipopolysaccharide-stimulated human whole blood. Ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) was employed to determine PGE2 inhibition levels. Untargeted metabolomics demonstrated that EOs harvested in autumn and spring exhibited fluctuations in the chemical composition, which favoured greater PGE2 inhibition levels, with pronounced seasonal shifts among the minor compounds. Orthogonal partial least squares discriminant analysis (PLS-DA) revealed terpinen-4-ol as statistically different and positively correlated with the increase in the anti-inflammatory activity. Safrole, a major compound, demonstrated no relevant seasonal variation. These findings highlight and confirm how seasonal chemical dynamics modulate the specialized metabolism and the anti-inflammatory activity profile of O. odorifera EOs.

Abstract in English:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder for which acetylcholinesterase inhibitors (AChIs) are commonly prescribed to mitigate cognitive decline. In this study, untargeted metabolomics and lipidomics based on liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) were applied to investigate metabolic alterations in plasma samples from AD patients before and during AChI treatment. Differential feature selection and pathway enrichment analyses revealed significant modulation of lipidic and energetic metabolism. Alterations in glycerophospholipid and glycosphingolipid metabolism, accompanied by a progressive reduction in phospholipids, suggest an increased demand for substrates associated with acetylcholine synthesis. Enrichment of carnitine transport and fat-soluble vitamin (E and D) metabolism after AChI treatment points to bioenergetic dysfunction and enhanced oxidative and inflammatory stress in AD. Changes in arginine and proline metabolism, carbohydrate metabolism, and butyrate metabolism further reflect key biochemical disturbances in AD, including glucose hypometabolism and nitrosative stress. These findings provide insights into the systemic metabolic effects of AChI therapy and highlight the potential of LC-HRMS-based metabolomics and lipidomics for biomarker discovery and therapeutic monitoring in AD.

Abstract in English:

Toxoplasmosis, caused by the obligate intracellular protozoan Toxoplasma gondii, represents a relevant zoonotic disease affecting both human and animal health. Free-ranging neotropical primates (FRNP) are particularly susceptible to severe clinical outcomes; however, systemic metabolic alterations associated with infection in these species remain poorly characterized. This study aimed to investigate serum metabolic perturbations in FRNP naturally infected with T. gondii using an untargeted liquid chromatography-mass spectrometry (LC-MS) approach integrated with multivariate and machine learning (ML) analyses. Serum samples from infected and non infected FRNP were analyzed by liquid chromatography-high-resolution mass spectrometry (LC-HRMS), yielding 1025 metabolic features following rigorous data preprocessing and quality control procedures. Both unsupervised and supervised ML models were employed to explore group discrimination. Several metabolic features (m/z 809.2713, 660.5429, 718.3614, 537.5458, 707.2745, 318.2951) were significantly altered in infected animals. Receiver Operating Characteristic (ROC) analysis indicated moderate discriminatory performance (area under the curve (AUC) = 0.78; sensitivity = 0.88). Collectively, these findings indicate that T. gondii infection in FRNP is associated with measurable systemic metabolic perturbations. The identified features should be interpreted as preliminary metabolic signatures, warranting further targeted validation and larger-scale studies to clarify their biological and potential translational relevance.

Abstract in English:

The Amaryllidaceae family is widely recognized for its remarkable alkaloid diversity, comprising secondary metabolites with significant pharmacological potential. Advances in liquid chromatography-mass spectrometry (LC-MS) combined with molecular networking strategies have enabled comprehensive structural characterization and visualization of complex metabolite datasets. Considering the limited efficacy and toxicity associated with current therapies for leishmaniasis, a neglected tropical disease of global relevance, Amaryllidaceae species represent a promising source of novel antileishmanial compounds. This study investigated the alkaloid diversity of methanolic extracts obtained from bulbs of 52 wild and hybrid Amaryllidaceae species collected in Latin American countries and evaluated their activity against Leishmania amazonensis. Extracts were analyzed by LC-MS and processed using MZmine, followed by feature-based molecular networkin (FBMN). This workflow enabled the annotation of 28 alkaloids organized into structurally related clusters, in addition to more than 15 compounds detected as unique nodes based on spectral similarity. Biological assays against promastigote forms, together with cytotoxicity evaluation in NIH/3T3 cells, identified Ismene amancaes as the most active extract (half-maximal inhibitory concentration (IC50) = 1.29 µg mL–1), compared with amphotericin B (IC50 = 0.04 µg mL–1). These findings highlight the chemical diversity and pharmacological relevance of Amaryllidaceae species.