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In recent years, there is a great concern about the potential adverse effects of carbon nanotubes (CNTs) on the aquatic systems due to their increasingly extensive application. In this study, juvenile Cyprinus carpio were exposed to multi-walled CNTs (MWCNTs) at concentrations of 0, 0.25, and 2.5 mg L -1 for 28 days. Then, oxidative stress indicators and metabolite profile of the livers were assessed. Results showed the significant increase of malondialdehyde (MDA) content and decrease of glutathione (GSH) activities in fish treated with 2.5 mg L -1 MWCNTs. LC-MS untargeted metabolomics demonstrated that 406 and 274 metabolites in fish treated with 2.5 mg L -1 MWCNTs were significantly up- and down-regulated, respectively. KEGG functional annotation analysis showed the disturbance of amino acid metabolism, lipid metabolism, and nucleotide metabolism. In addition, ferroptosis signaling pathway was detected. Therefore, iron content analysis and quantitative real-time RT-PCR assay were performed furtherly to validate the contribution of ferroptosis to MWCNTs-induced hepatotoxicity. The iron content increased significantly and the mRNA levels of ferroptosis-related genes including STEAP3, ACSL4, NCOA4, TFR1, NRF2, SLC3A2, SLC7A11, GPX4, and FPN1 were also obviously changed. Taken together, our study suggested that MWCNTs exposure-induced ferroptosis were associated with iron overload and lipid peroxidation via NRF2/SLC7A11/GSH/GPX4 axis. Our findings provide essential information to understand the mechanism of CNTs-induced hepatotoxicity in fish and explore potential biomarkers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC., (© 2024 SETAC.)

Objective: The prevalence of asthma has gradually increased worldwide in recent years, which has made asthma a global public health problem. However, due to its complexity and heterogeneity, there are a few academic debates on the pathogenic mechanism of asthma. The study of the pathogenesis of asthma through metabolomics has become a new research direction. We aim to uncover the metabolic pathway of children with asthma., Methods: Liquid chromatography (LC)-mass spectrometry (MS)-based metabolomic analysis was conducted to compare urine metabolic profiles between asthmatic children ( n  = 30) and healthy controls ( n  = 10)., Results: Orthogonal projections to latent structures-discrimination analysis (OPLS-DA) showed that there were significant differences in metabolism between the asthma group and the control group with three different metabolites screened out, including traumatic acid, dodecanedioic acid, and glucobrassicin, and the levels of traumatic acid and dodecanedioic acid in the urine samples of asthmatic children were lower than those of healthy controls therein. Pathway enrichment analysis of differentially abundant metabolites suggested that α-linolenic acid metabolism was an asthma-related pathway., Conclusions: This study suggests that there are significant metabolic differences in the urine of asthmatic children and healthy controls, and α-linolenic acid metabolic pathways may be involved in the pathogenesis of asthma.

Background: Although malnutrition is common in cancer patients, its molecular mechanisms has not been fully clarified. This study aims to identify significantly differential metabolites, match the corresponding metabolic pathways, and develop a predictive model of malnutrition in patients with gastric cancer., Methods: In this cross-sectional study, we applied non-targeted metabolomics using liquid chromatography-mass spectrometry to explore the serum fingerprinting of malnutrition in patients with gastric cancer. Malnutrition-specific differential metabolites were identified by orthogonal partial least-squares discriminant analysis and t-test and matched with the Human Metabolome Database and the LIPID Metabolites and Pathways Strategy. We matched the corresponding metabolic pathways of malnutrition using pathway analysis at the MetaboAnalyst 5.0. We used random forest analyses to establish the predictive model., Results: We recruited 220 malnourished and 198 non-malnourished patients with gastric cancer. The intensities of 25 annotated significantly differential metabolites were lower in patients with malnutrition than those without, while two others were higher in patients with malnutrition than those without, including newly identified significantly differential metabolites such as indoleacrylic acid and lysophosphatidylcholine(18:3/0:0). We matched eight metabolic pathways associated with malnutrition, including aminoacyl-tRNA biosynthesis, tryptophan metabolism, and glycerophospholipid metabolism. We established a predictive model with an area under the curve of 0.702 (95% CI: 0.651-0.768) based on four annotated significantly differential metabolites, namely indoleacrylic acid, lysophosphatidylcholine(18:3/0:0), L-tryptophan, and lysophosphatidylcholine(20:3/0:0)., Conclusions: We identified 27 specific differential metabolites of malnutrition in malnourished compared to non-malnourished patients with gastric cancer. We also matched eight corresponding metabolic pathways and developed a predictive model. These findings provide supportive data to better understand molecular mechanisms of malnutrition in patients with gastric cancer and new strategies for the prediction, diagnosis, prevention, and treatment for those malnourished., (© 2024. The Author(s).)

Identification of the individuals having impaired kidney function is essential in preventing the complications of this disease. We measured 1009 metabolites at the baseline study in 10,159 Finnish men of the METSIM cohort and associated the metabolites with an estimated glomerular filtration rate (eGFR). A total of 7090 men participated in the 12-year follow-up study. Non-targeted metabolomics profiling was performed at Metabolon, Inc. (Morrisville, NC, USA) on EDTA plasma samples obtained after overnight fasting. We applied liquid chromatography mass spectrometry (LC-MS/MS) to identify the metabolites (the Metabolon DiscoveryHD4 platform). We performed association analyses between the eGFR and metabolites using linear regression adjusted for confounding factors. We found 108 metabolites significantly associated with a decrease in eGFR, and 28 of them were novel, including 12 amino acids, 8 xenobiotics, 5 lipids, 1 nucleotide, 1 peptide, and 1 partially characterized molecule. The most significant associations were with five amino acids, N-acetylmethionine, N-acetylvaline, gamma-carboxyglutamate, 3-methylglutaryl-carnitine, and pro-line. We identified 28 novel metabolites associated with decreased eGFR in the 12-year follow-up study of the METSIM cohort. These findings provide novel insights into the role of metabolites and metabolic pathways involved in the decline of kidney function.

Ovarian cancer (OC) is the most lethal gynecologic cancer, mainly due to late diagnosis with widespread peritoneal spread at first presentation. We performed metabolomic analyses of ovarian and paired control tissues using capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry to understand its metabolomic dysregulation. Of the 130 quantified metabolites, 96 metabolites of glycometabolism, including glycolysis, tricarboxylic acid cycles, urea cycles, and one-carbon metabolites, showed significant differences between the samples. To evaluate the local and systemic metabolomic differences in OC, we also analyzed low or non-invasively available biofluids, including plasma, urine, and saliva collected from patients with OC and benign gynecological diseases. All biofluids and tissue samples showed consistently elevated concentrations of N 1 ,N 12 -diacetylspermine compared to controls. Four metabolites, polyamines, and betaine, were significantly and consistently elevated in both plasma and tissue samples. These data indicate that plasma metabolic dysregulation, which the most reflected by those of OC tissues. Our metabolomic profiles contribute to our understanding of metabolomic abnormalities in OC and their effects on biofluids., (© 2024. The Author(s).)

A significant hurdle in untargeted lipid/metabolomics research lies in the absence of reliable, cross-validated spectral libraries, leading to a considerable portion of LC-MS features being labeled as unknowns. Despite continuous advancement in annotation tools and libraries, it is important to safeguard, publish and share acquired data through public repositories. Embracing this trend of data sharing not only promotes efficient resource utilization but also paves the way for future repurposing and in-depth analysis; ultimately advancing our comprehension of Covid-19 and other diseases. In this work, we generated an extensive MS-dataset of 39 Covid-19 infected patients versus age- and gender-matched 39 healthy controls. We implemented state of the art acquisition techniques including IDA and SWATH-DIA to ensure a thorough insight in the lipidome and metabolome, ensuring a repurposable dataset., (© 2024. The Author(s).)

Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learning methods has led to high diagnostic and prognostic accuracy for various pathological conditions. This study explored the synergistic potential of dual-platform metabolomics (specifically, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS)) to expand the detection of metabolites and improve the precision of DVT diagnosis. Sixty-one differential metabolites were identified in serum from DVT patients: 22 from GC-MS and 39 from LC-MS. Among these, five key metabolites were highlighted by SHapley Additive exPlanations (SHAP)-guided feature engineering and then used to develop a stacking diagnostic model. Additionally, a user-friendly interface application system was developed to streamline and automate the application of the diagnostic model, enhancing its practicality and accessibility for clinical use. This work showed that the integration of dual-platform metabolomics with a stacking machine learning model enables faster and more accurate diagnosis of DVT in clinical environments.

The interactions of proteins, membranes, nucleic acid, and metabolites shape a cell's phenotype. These interactions are stochastic, and each cell develops differently, making it difficult to synchronize cell populations. Consequently, studying biological processes at the single- or few-cell level is often necessary to avoid signal dilution below the detection limit or averaging over many cells. We have developed a method to study metabolites and proteins from a small number of or even a single adherent eukaryotic cell. Initially, cells are lysed by short electroporation and aspirated with a microcapillary under a fluorescent microscope. The lysate is placed on a carrier slide for further analysis using liquid-chromatography mass spectrometry (LC-MS) and/or reverse-phase protein (RPPA) approach. This method allows for a correlative measurement of (i) cellular structures and metabolites and (ii) cellular structures and proteins on the single-cell level. The correlative measurement of cellular structure by light-microscopy, metabolites by LC-MS, and targeted protein detection by RPPA was possible on the few-cell level. We discuss the method, potential applications, limitations, and future improvements.

A comprehensive understanding of the exact influence of type 2 diabetes mellitus (T2DM) on the metabolic status of non-small cell lung cancer (NSCLC) is still lacking. This study explores metabolic alterations in tumor tissues among patients with coexisting NSCLC and T2DM in comparison with NSCLC patients. A combined approach of clinical analysis and metabolomics was employed, including 20 NSCLC patients and 20 NSCLC+T2DM patients. Targeted metabolomics analysis was performed on tumor tissues using the liquid chromatography-mass spectrometry (LC-MS) approach. A clear segregation was observed between NSCLC+T2DM and matched NSCLC tissue samples in Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA). Furthermore, the levels of 7 metabolites are found to be significantly different between diabetes/nondiabetes tumor tissue samples. The related pathways included arginine biosynthesis, glutathione metabolism, arginine and proline metabolism, purine metabolism, biotin metabolism, and histidine metabolism. 3-Phenyllactic acid, carnitine-C5, carnitine-C12, and serotonin showed a positive linear correlation with fasting blood glucose levels in NSCLC patients. Uridine, pipecolic acid, cytosine, and fasting blood glucose levels were found to have a negative correlation. Our results suggest that NSCLC patients with concurrent T2DM exhibit distinct metabolic shifts in tumor tissues compared to those of solely NSCLC patients.

Breast cancer (BC) is among the most commonly diagnosed cancers. Besides mammography, breast ultrasonography and the routinely monitored protein markers, the variations of small molecular metabolites in blood may be of great diagnostic value. This study aimed to quantify specific metabolite markers with potential application in BC detection. The study enrolled 50 participants, 25 BC patients and 25 healthy controls (CTRL). Dried blood spots (DBS) were utilized as biological media and were quantified via a simplified liquid chromatography tandem mass spectrometry (LC-MS/MS) method, used in expanded newborn screening. The targeted metabolomic analysis included 12 amino acids and 32 acylcarnitines. Statistical analysis revealed a significant variation of metabolic profiles between BC patients and CTRL. Among the 44 metabolites, 18 acylcarnitines and 10 amino acids remained significant after Bonferroni correction, showing increase or decrease and enabled classification of BC patients and CTRL. The well-established LC-MS/MS protocol could provide results within few minutes. Therefore, the combination of an easy-to-handle material-DBS and LC-MS/MS protocol could facilitate BC screening/diagnosis and in the next step applied to other cancer patients, as well.

Purpose: Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach., Methods: Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles., Results: Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points., Conclusion: The application of plasma metabolomics, utilizing CE-MS and LC-MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Aims: Gallstone disease affects ≥40 million people in the USA and accounts for health costs of ≥$4 billion a year. Risk factors such as obesity and metabolic syndrome are well established. However, data are limited on relevant metabolomic alterations that could offer mechanistic and predictive insights into gallstone disease. This study prospectively identifies and externally validates circulating prediagnostic metabolites associated with incident gallstone disease., Methods: Female participants in Nurses' Health Study (NHS) and Nurses' Health Study II (NHS II) who were free of known gallstones (N=9960) were prospectively followed up after baseline metabolomic profiling with liquid chromatography-tandem mass spectrometry. Multivariable logistic regression and enrichment analysis were used to identify metabolites and metabolite groups associated with incident gallstone disease at P FDR <0.05. Findings were validated in 1866 female participants in the Women's Health Initiative and a comparative analysis was performed with 2178 male participants in the Health Professionals Follow-up Study., Results: After multivariate adjustment for lifestyle and putative risk factors, we identified and externally validated 17 metabolites associated with incident gallstone disease in women-nine triacylglycerols (TAGs) and diacylglycerols (DAGs) were positively associated, while eight plasmalogens and cholesterol ester (CE) were negatively associated. Enrichment analysis in male and female cohorts revealed positive class associations with DAGs, TAGs (≤56 carbon atoms and ≤3 double bonds) and de novo TAG biosynthesis pathways, as well as inverse associations with CEs., Conclusions: This study highlights several metabolites (TAGs, DAGs, plasmalogens and CE) that could be implicated in the aetiopathogenesis of gallstone disease and serve as clinically relevant markers., Competing Interests: Competing interests: ATC served as a consultant for Pfizer Inc. and Boehringer Ingelheim and received grants from Pfizer Inc, Zoe Ltd and Freenome., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The chemical compounds found in propolis vary according to plant sources, species, and geographical regions. To date, Indonesian propolis has not yet become standardized in terms of its chemical constituents. Thus, this study aimed to identify the presence of marker compounds and determine whether different classes of Indonesian propolis exist. In this study, yields, total polyphenol content (TPC), total flavonoid content (TFC), and antioxidants were measured. Identification of chemical compounds was carried out with Fourier-transform infrared (FTIR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Metaboanalyst 6.0 was employed in conducting principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) using the results of the FTIR and LC-MS/MS. The propolis with the highest TFC, TPC, and antioxidant activity was Geniotrigona thoracica from North Sumatra. The results of propolis compound mapping based on region with discriminant analysis revealed that types of propolis from Java have similar characteristics. Then, based on species, the types of propolis from Tetragonula laeviceps and Heterotrigona itama have special characteristics; the samples from these species can be grouped according to similar characteristics. In conclusion, 10 potential marker compounds were identified in Indonesian propolis, enabling regional and species-specific varieties of Indonesian propolis to be classified based on chemical composition mapping.

Background: Coronary atherosclerosis (CAS) is a prevalent and chronic life-threatening disease. However, the detection of CAS at an early stage is difficult because of the lack of effective noninvasive diagnostic methods. The present study aimed to characterize the plasma metabolome of early-stage CAS patients to discover metabolomic biomarkers, develop a novel metabolite-based model for accurate noninvasive diagnosis of early-stage CAS, and explore the underlying metabolic mechanisms involved., Methods: A total of 100 patients with early-stage CAS and 120 age- and sex-matched control subjects were recruited from the Chinese Han population and further randomly divided into training (n = 120) and test sets (n = 100). The metabolomic profiles of the plasma samples were analyzed by an integrated untargeted liquid chromatography-mass spectrometry approach, including two separation modes and two ionization modes. Univariate and multivariate statistical analyses were employed to identify potential biomarkers and construct an early-stage CAS diagnostic model., Results: The integrated analytical method established herein improved metabolite coverage compared with single chromatographic separation and MS ionization mode. A total of 80 metabolites were identified as potential biomarkers of early-stage CAS, and these metabolites were mainly involved in glycerophospholipid, fatty acid, sphingolipid, and amino acid metabolism. An effective diagnostic model for early-stage CAS was established, incorporating 11 metabolites and achieving areas under the receiver operating characteristic curve (AUCs) of 0.984 and 0.908 in the training and test sets, respectively., Conclusions: Our study not only successfully developed an effective noninvasive diagnostic model for identifying early-stage CAS but also provided novel insights into the pathogenesis of CAS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study aims to explore the link between retinal vein occlusion (RVO), a blinding ocular condition, and alterations in gut microbiota composition, to offer insights into the pathogenesis of RVO. Fecal samples from 25 RVO patients and 11 non-RVO individuals were analyzed using 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC-MS). Significant differences in the abundance of gut microbial species were noted between RVO and non-RVO groups. At the phylum level, the RVO group showed an elevation in the ratio of Firmicutes to Bacteroidetes. At the genus level, the RVO group showed higher abundance in Escherichia&#95;Shigella ( P < 0.05) and less abundance in Parabacteroides ( P < 0.01) than the non-RVO group. Functional predictions indicated reduced folate synthesis, biotin metabolism, and oxidative phosphorylation, with an increase in butyric acid metabolism in the RVO group. LC-MS analysis showed significant differences in purine metabolism, ABC transporters, and naphthalene degradation pathways, especially purine metabolism. Pearson correlation analysis revealed significant associations between bacterial genera and fecal metabolites. Enrichment analysis highlighted connections between specific metabolites and bacterial genera. The findings showed that the dysregulation of gut microbiota was observed in RVO patients, suggesting the gut microbiota as a potential therapeutic target. Modulating the gut microbiota could be a novel strategy for managing RVO and improving patient outcomes. Furthermore, the study findings suggest the involvement of gut microbial dysbiosis in RVO development, underscoring the significance of understanding its pathogenesis for effective treatment development., Importance: Retinal vein occlusion (RVO) is a blinding ocular condition, and understanding its pathogenesis is crucial for developing effective treatments. This study demonstrates significant differences in gut microbiota composition between RVO patients and non-RVO individuals, implicating the involvement of gut microbial dysbiosis in RVO development. Functional predictions and metabolic profiling provide insights into the underlying mechanisms, highlighting potential pathways for therapeutic intervention. These findings suggest that modulating the gut microbiota might be a promising strategy for managing RVO and improving patient outcomes., Competing Interests: The authors declare no conflict of interest.

Ischemic stroke is the most important cause of disability and death worldwide, but current treatments remain limited. Traditional Chinese medicine (TCM) including the herb pair of Zhiqiao-Danggui (ZD) offers a multifaceted treatment approach through promoting blood circulation, yet its specific anti-ischemic mechanism remains unclear. This study used the photochemically induced thrombosis (PIT) mouse model and the oxygen glucose deprivation/reoxygenation (OGD/R) cell model to explore the therapeutic effect of ZD on ischemic stroke. Mice were treated with high and low doses of ZD extract or positive control. Behavior was assessed using the grid test. The brain tissue was then subjected to infarct volume assessment, histopathology, oxidative stress marker detection, LC/MS metabolomic analysis and qRT-PCR validation. The therapeutic effect of ZD-medicated serum on OGD/R model was tested on cells. Experimental results show that ZD can improve motor function, reduce infarct size, neuronal damage and apoptosis as well as alleviate oxidative stress in mice. ZD-medicated serum promotes endothelial cell proliferation, improves cell survival against OGD/R-induced injury, reduces oxidative damage and protects mitochondrial function. Metabolomics reveals ZD regulation of metabolites in energy metabolism, amino acid metabolism, TCA cycle, and angiogenesis signaling pathways. qRT-PCR results also showed that ZD could attenuate abnormal conduction of angiogenic signals and enhance vessel stability. This study confirmed the neuroprotective and vasoprotective effects of ZD, highlighted its potential in treating ischemic stroke, and provided a scientific basis for the traditional use of ZD., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Aim: Cisplatin causes acute kidney injury (AKI) in approximately one third of patients. Serum creatinine and urinary output are poor markers of cisplatin-induced AKI. Metabolomics was utilized to identify predictive or early diagnostic biomarkers of cisplatin-induced AKI., Methods: Thirty-one adult head and neck cancer patients receiving cisplatin (dose ≥70 mg/m 2 ) were recruited for metabolomics analysis. Urine and serum samples were collected prior to cisplatin (pre), 24-48 h after cisplatin (24-48 h) and 5-14 days (post) after cisplatin. Based on serum creatinine concentrations measured at the post timepoint, 11/31 patients were classified with clinical AKI. Untargeted metabolomics was performed using liquid chromatography-mass spectrometry (LC-MS)., Results: Metabolic discrimination was observed between "AKI" patients and "no AKI" patients at all timepoints. Urinary glycine, hippuric acid sulfate, 3-hydroxydecanedioc acid and suberate were significantly different between AKI patients and no AKI patients prior to cisplatin infusion. Urinary glycine and hippuric acid sulfate were lower (-2.22-fold and -8.85-fold), whereas 3-hydroxydecanedioc acid and suberate were higher (3.62-fold and 1.91-fold) in AKI patients relative to no AKI patients. Several urine and serum metabolites were found to be altered 24-48 h following cisplatin infusion, particularly metabolites involved with mitochondrial energetics., Conclusions: We propose glycine, hippuric acid sulfate, 3-hydroxydecanedioc acid and suberate as predictive biomarkers of predisposition to cisplatin-induced AKI. Metabolites indicative of mitochondrial dysfunction may serve as early markers of subclinical AKI., (© 2023 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy that alters the metabolites in human milk. Integrated Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS) were employed for comprehensive identification and comparison of metabolites in mature human milk (MHM) from women with and without GDM. A total of 268 differentially expressed metabolites (DEMs) were identified. Among these, linoleic acid, arachidonic acid, 9R-HODE and L-glutamic acid were significantly elevated and 12,13-DHOME was significantly decreased in MHM of women with GDM. These metabolites are significantly enriched in linoleic acid metabolism, fatty acid biosynthesis, galactose metabolism and ABC transporters pathways. Disorders in these metabolic pathways are associated with insulin resistance and poor glucose metabolism indicating these conditions may persist postpartum., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Growing clinical evidence reveals that systematic molecular alterations in the brain occur 20 years before the onset of AD pathological features. Apolipoprotein E4 (ApoE4) is one of the most significant genetic risk factors for Alzheimer's disease (AD), which is not only associated with the AD pathological features such as amyloid-β deposition, phosphorylation of tau proteins, and neuroinflammation but is also involved in metabolism, neuron growth, and synaptic plasticity. Multiomics, such as metabolomics and proteomics, are applied widely in identifying key disease-related molecular alterations and disease-progression-related changes. Despite recent advances in the development of analytical technologies, screening the entire profile of metabolites remains challenging due to the numerous classes of compounds with diverse chemical properties that require different extraction processes for mass spectrometry. In this study, we utilized Orbitrap Secondary Ion Mass Spectrometry (OrbiSIMS) as a chemical filtering screening tool to examine molecular alterations in ApoE4-carried neuroglioma cells compared to wild-type H4 cells. The findings were compared using liquid chromatography (LC)-MS/MS targeted metabolomics analysis for the confirmation of specific metabolite classes. Detected alterations in peptide fragments by OrbiSIMS provided preliminary indications of protein changes. These were extensively analyzed through proteomics to explore ApoE4's impact on proteins. Our metabolomics approach, combining OrbiSIMS and LC-MS/MS, revealed disruptions in lipid metabolism, including glycerophospholipids and sphingolipids, as well as amino acid metabolism, encompassing alanine, aspartate, and glutamate metabolism; aminoacyl-tRNA biosynthesis; glutamine metabolism; and taurine and hypotaurine metabolism. Further LC-MS/MS proteomics studies confirmed the dysfunction in amino acid and tRNA aminoacylation metabolic processes, and highlighted RNA splicing alterations influenced by ApoE4.

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

The annotation of metabolites detected in LC-MS-based untargeted metabolomics studies routinely applies accurate m / z of the intact metabolite (MS1) as well as chromatographic retention time and MS/MS data. Electrospray ionization and transfer of ions through the mass spectrometer can result in the generation of multiple "features" derived from the same metabolite with different m / z values but the same retention time. The complexity of the different charged and neutral adducts, in-source fragments, and charge states has not been previously and deeply characterized. In this paper, we report the first large-scale characterization using publicly available data sets derived from different research groups, instrument manufacturers, LC assays, sample types, and ion modes. 271 m / z differences relating to different metabolite feature pairs were reported, and 209 were annotated. The results show a wide range of different features being observed with only a core 32 m / z differences reported in >50% of the data sets investigated. There were no patterns reporting specific m / z differences that were observed in relation to ion mode, instrument manufacturer, LC assay type, and mammalian sample type, although some m / z differences were related to study group (mammal, microbe, plant) and mobile phase composition. The results provide the metabolomics community with recommendations of adducts, in-source fragments, and charge states to apply in metabolite annotation workflows.

We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Clorobiocin is a well-known, highly effective inhibitor of DNA gyrase belonging to the aminocoumarin antibiotics. To identify potentially novel derivatives of this natural product, we conducted an untargeted investigation of clorobiocin biosynthesis in the known producer Streptomyces roseochromogenes DS 12.976 using LC-MS E , molecular networking, and analysis of fragmentation spectra. Previously undescribed clorobiocin derivatives uncovered in this study include bromobiocin, a variant halogenated with bromine instead of chlorine, hydroxylated clorobiocin, carrying an additional hydroxyl group on its 5-methyl-pyrrole 2-carboxyl moiety, and two other derivatives with modifications on their 3-dimethylallyl 4-hydroxybenzoate moieties. Furthermore, we identified several compounds not previously considered clorobiocin pathway products, which provide new insights into the clorobiocin biosynthetic pathway. By supplementing the medium with different concentrations of potassium bromide, we confirmed that the clorobiocin halogenase can utilize bromine instead of chlorine. The reaction, however, is impeded such that non-halogenated clorobiocin derivatives accumulate. Preliminary assays indicate that the antibacterial activity of bromobioin against Bacillus subtilis and efflux-impaired Escherichia coli matches that of clorobiocin. Our findings emphasize that yet unexplored compounds can be discovered from established strains and biosynthetic gene clusters by means of metabolomics analysis and highlight the utility of LC-MS E -based methods to contribute to unraveling natural product biosynthetic pathways., Importance: The aminocoumarin clorobiocin is a well-known gyrase inhibitor produced by the gram-positive bacterium Streptomyces roseochromogenes DS 12.976. To gain a deeper understanding of the biosynthetic pathway of this complex composite of three chemically distinct entities and the product spectrum, we chose a metabolite-centric approach. Employing high-resolution LC-MS E analysis, we investigated the pathway products in extracted culture supernatants of the natural producer. Novel pathway products were identified that expand our understanding of three aspects of the biosynthetic pathway, namely the modification of the noviose, transfer and methylation of the pyrrole 2-carboxyl moiety, and halogenation. For the first time, brominated products were detected. Their levels and the levels of non-halogenated products increased in medium supplemented with KBr. Based on the presented data, we propose that the enzyme promiscuity contributes to a broad product spectrum., Competing Interests: The authors declare no conflict of interest.

Purpose: The aim of this article was to investigate whether Schirmer strips gathered during clinical dry eye examinations can be prepared for omics analyses in a standardized way, to adjust for variations in tear volume and enable two separate omics analyses from the same sample. In addition, the intention was to investigate whether fluorescein dye instillation in the eyes gave bias effects on metabolomic analysis., Methods: Twelve samples from six individuals, with normal or reduced tear production, were collected. Half of the samples were harvested after instillation of fluorescein in the eye. Each strip was divided in half along the length and prepared with a new method for extracting tear content from the Schirmer strip. The new method was established to compensate for different dilutions of metabolites in varying Schirmer strip wetting levels when using identical extraction volume for all samples. Metabolomic data were compared in samples with and without fluorescein dye and Schirmer strips ranging from 1 to 35 mm wetting levels using a global LC-MS method., Results: All samples were successfully analyzed with an average of ∼350 relevant features detected per sample after using both positive and negative electrospray ionization mode, despite low tear volumes in some samples and that only one half of the Schirmer strips were used. Principal component analysis plots and heatmaps revealed no bias effects of fluorescein dye presence or different Schirmer strip values when using the proposed method., Conclusion: A high number of relevant metabolomic features can be extracted from longitudinally cut halves of Schirmer strips, which may enable analyses with more than one omics modality from the same sample. With the pre-analytical method described, Schirmer strips can be used for metabolomic analyses even in cases of very low or high tear volume with or without fluorescence.

Henoch-Schönlein purpura nephritis (HSPN) is the most severe manifestation of Henoch-Schönlein purpura (HSP). This study aimed to determine the role of urine metabolomics in predicting HSPN and explore the potential mechanisms of HSP. A liquid chromatography-tandem mass spectrometry-based untargeted metabolomics analysis was performed to investigate the urinary metabolic profiles of 90 participants, comprising 30 healthy children (group CON) and 60 patients with HSP, including 30 HSP patients without renal involvement (group H) and 30 HSPN patients (group HSPN). The differentially expressed metabolites (DEMs) were identified using orthogonal partial least squares discriminant analysis (OPLS-DA), and subsequent bioinformatics analysis was conducted to elucidate the perturbed metabolic pathways. A total of 43 DEMs between H and HSPN groups were analyzed by the Kyoto Encyclopedia of Gene and Genome (KEGG) database, and the result indicates that glycine, serine and threonine metabolism, and cysteine and methionine metabolism were significantly disturbed. A composite model incorporating propionylcarnitine and indophenol sulfate was developed to assess the risk of renal involvement in pediatric patients with HSP.   Conclusion: This study reveals the metabolic alterations in healthy children, HSPN patients, and HSP patients without renal involvement. Furthermore, propionylcarnitine and indophenol sulfate may be potential predictive biomarkers of the occurrence of HSPN. What is Known: • HSP is the predominant type of vasculitis observed in children. The long-term prognosis of HSP is contingent upon the extent of renal impairment. In severe nephritis, a delay in appropriate treatment may lead to fibrosis progression and subsequent development of chronic kidney disease (CKD), even leading to renal failure. • The application of metabolomics in investigating diverse renal disorders has been documented. Urine is a robust and sensitive medium for metabolomics detection. What is New: • The metabolic profiles were identified in urine samples of healthy children and those with HSP at the early stage of the disease. Different metabolites were identified between HSP patients without nephritis and those who developed HSPN. • These different metabolites may affect oxidative stress in the progression of HSPN., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Cantharidin (CTD) is the main active component in the traditional Chinese medicine Mylabris and an effective anti-tumor agent. However, it is relatively toxic and exhibits nephrotoxicity, which limits its clinical use. However, its toxic mechanism is not clear. The toxic effects of CTD exposure on the kidney and the protective effect of resveratrol (RES) were studied in a mouse model, by determination of serum biochemical and renal antioxidant indicators, histopathological and ultrastructural observation, and metabonomics. After CTD exposure, serum uric acid, creatinine, and tissue oxidative stress indicators increased, and the renal glomerular and tubular epithelial cells showed clear pathological damage. Ultrastructure observation revealed marked mitochondrial swelling, endoplasmic reticulum dilation, and the presence of autophagy lysosomes in glomerular epithelial cells. RES ameliorated the renal injury induced by CTD. Metabonomics analysis indicated that CTD can induce apoptosis and oxidative damage in kidney cells, mainly by disrupting sphingolipid and glutathione metabolism, increasing sphingosine and sphingomyelin levels, and decreasing glutathione levels. RES counteracts these effects by regulating renal cell proliferation, the inflammatory response, oxidative stress, and apoptosis, by improving the levels of phosphatidylcholine (PC), LysoPC, and lysophosphatidyl glycerol in the glycerophospholipid metabolism pathway, thereby reducing CTD-induced nephrotoxicity. The mechanisms of CTD-induced renal injury and the protective effect of RES were revealed by metabonomics, providing a basis for evaluating clinical treatment regimens to reduce CTD-induced nephrotoxicity., (© 2024 John Wiley & Sons Ltd.)

Cerebrospinal fluid metabolomics is a promising research technology in the elucidation of nervous system disorders. Therefore, in this work, a cerebrospinal fluid (CSF) metabolomics method using liquid chromatography coupled to mass spectrometry was optimized and validated to cover a wide range of metabolites. An acceptable coefficient of variance regarding instrumental, within-lab and intra-assay precision was found for 95, 70 and 96 of 102 targeted metabolites, together with 1256, 676 and 976 untargeted compounds, respectively. Moreover, approximately 75% of targeted metabolites and 50% of untargeted compounds displayed good linearity across different dilution ranges. Consequently, metabolic alterations in CSF of dogs with idiopathic epilepsy (IE) were studied by comparing CSF of dogs diagnosed with IE (Tier II) to dogs with non-brain related disease. Targeted metabolome analysis revealed higher levels of cortisol, creatinine, glucose, hippuric acid, mannose, pantothenol, and 2-phenylethylamine (P values < 0.05) in CSF of dogs with IE, whereas CSF of dogs with IE showed lower levels of spermidine (P value = 0.02). Untargeted CSF metabolic fingerprints discriminated dogs with IE from dogs with non-brain related disease using Orthogonal Partial Least Squares Discriminant Analysis (R 2 (Y) = 0.997, Q 2 (Y) = 0.828), from which norepinephrine was putatively identified as an important discriminative metabolite., (© 2024. The Author(s).)

Australian fruits such as native currant ( Acrotriche depressa ) and lemon aspen ( Acronychia acidula ) are under-examined in terms of their therapeutic potential. In this study, the in vitro antiproliferative activity of native currant and lemon aspen extracts (water and ethanol) against MCF7 breast adenocarcinoma cells was determined using the Alamar blue assay. The most potent extracts (native currant water, NC-W; native currant ethanol, NC-Et; lemon aspen ethanol, LA-Et) were further evaluated using flow cytometry to detect the potential induction of apoptosis in MCF7 cells whereas 2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA) assay was implemented to understand the impact of the extracts on the intracellular reactive oxygen species (ROS) levels in MCF7 cells. Furthermore, the antioxidant activity of the extracts was assessed using ABTS [2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonate)], and CUPRAC (cupric reducing antioxidant capacity) assays. The antimicrobial susceptibility testing of NC-W, NC-Et, and LA-Et was carried out against Gram-positive ( Staphylococcus aureus ), Gram-negative ( Escherichia coli ), and yeast ( Candida albicans ) strains using a resazurin-based assay. Additionally, potential metabolites in the NC-W and NC-Et extracts were analysed with liquid chromatography-mass spectrometry (LC-MS) driven metabolomics and chemometrics to spot differential and major metabolites. A dose-dependent antiproliferative activity was conferred by the NC extracts against MCF7 cells. Of the two LA extracts, only LA-Et showed a dose-dependent antiproliferative activity at higher concentrations. Both NC extracts and LA-Et induced apoptosis in MCF7 cells. None of the extracts increased the production of ROS significantly in MCF7 cells compared to the untreated control. A dose-dependent antioxidant activity was observed in both antioxidant assays. Both NC and LA extracts showed a similar minimum inhibitory concentration (MIC) value against S. aureus . Only LA-Et showed activity against E. coli , while NC-W and NC-Et were less active. All extracts showed MIC values of >1500 μg mL -1 against C. albicans . The metabolomics analysis revealed an abundance of flavonoids, fatty acyl derivatives, carbohydrates, carboxylic acids and their derivatives, and alkaloid compounds as potential bioactive metabolites in the NC extracts. In conclusion, both NC and LA showed antiproliferative (against MCF7 breast adenocarcinoma cells through the induction of apoptosis), strong antioxidant and minimal antimicrobial properties.

Background: Preeclampsia (PE) is a leading cause of maternal and fetal morbidity and mortality, with limited effective clinical treatment options. Active metabolomics offers a promising approach to uncover metabolic changes in PE and identify potential biomarkers or therapeutic targets. This study performed untargeted metabolomics using LC-MS to compare serum samples from preeclampsia and normal pregnancies., Methods: We performed untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) to compare serum samples from PE patients and normal pregnancies. We analyzed the alterations in metabolites and conducted functional experiments to assess the effects of LysoPE(16:0) on trophoblast cell invasion and migration. Mechanistic studies were performed to explore the potential targeting of GSK-3β by LysoPE(16:0)., Results: Our metabolomics analysis revealed significant alterations in several metabolites, including lysophosphatidylcholines and organic acids. Notably, LysoPE(16:0) was found to be downregulated in the serum of PE patients. Functional experiments demonstrated that LysoPE(16:0) could promote trophoblast cell invasion and migration. Mechanistic studies suggest that the protective effect of LysoPE(16:0) against PE might be mediated through the modulation of the GSK-3β/β-Catenin pathway, with LysoPE(16:0) potentially targeting the GSK-3β protein., Conclusions: Our findings highlight the potential role of LysoPE(16:0) in the pathophysiology of PE and its ability to modulate the GSK-3β/β-Catenin pathway. These results provide new insights into the metabolic changes associated with PE and suggest that LysoPE(16:0) could serve as a promising biomarker or therapeutic target for the prevention and treatment of PE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Long-term exposure to microgravity is considered to cause liver lipid accumulation, thereby increasing the risk of non-alcoholic fatty liver disease (NAFLD) among astronauts. However, the reasons for this persistence of symptoms remain insufficiently investigated. In this study, we used tandem mass tag (TMT)-based quantitative proteomics techniques, as well as non-targeted metabolomics techniques based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), to comprehensively analyse the relative expression levels of proteins and the abundance of metabolites associated with lipid accumulation in rat liver tissues under simulated microgravity conditions. The differential analysis revealed 63 proteins and 150 metabolites between the simulated microgravity group and the control group. By integrating differentially expressed proteins and metabolites and performing pathway enrichment analysis, we revealed the dysregulation of major metabolic pathways under simulated microgravity conditions, including the biosynthesis of unsaturated fatty acids, linoleic acid metabolism, steroid hormone biosynthesis and butanoate metabolism, indicating disrupted liver metabolism in rats due to weightlessness. Finally, we examined differentially expressed proteins associated with lipid metabolism in the liver of rats exposed to stimulated microgravity. These findings contribute to identifying the key molecules affected by microgravity and could guide the design of rational nutritional or pharmacological countermeasures for astronauts.

Introduction: Emerging evidence suggests that the gut microbiota is closely associated with bone homeostasis. However, little is known about the relationships among the bone mineral density (BMD) index, bone turnover markers, and the gut microbiota and its metabolites in postmenopausal women., Methods: In this study, to understand gut microbiota signatures and serum metabolite changes in postmenopausal women with reduced BMD, postmenopausal individuals with normal or reduced BMD were recruited and divided into normal and OS groups. Feces and serum samples were collected for 16S rRNA gene sequencing, liquid chromatography coupled with mass spectrometry (LC-MS)-based metabolomics and integrated analysis., Results: The results demonstrated that bacterial richness and diversity were greater in the OS group than in the normal group. Additionally, distinguishing bacteria were found among the two groups and were closely associated with the BMD index and bone turnover markers. Metabolomic analysis revealed that the expression of serum metabolites, such as etiocholanolone, testosterone sulfate, and indole-3-pyruvic acid, and the corresponding signaling pathways, especially those involved in tryptophan metabolism, fatty acid degradation and steroid hormone biosynthesis, also changed significantly. Correlation analysis revealed positive associations between normal group-enriched Bacteroides abundance and normal group-enriched etiocholanolone and testosterone sulfate abundances; in particular, Bacteroides correlated positively with BMD. Importantly, the tryptophan-indole metabolism pathway was uniquely metabolized by the gut bacteria-derived tnaA gene, the predicted abundance of which was significantly greater in the normal group than in the control group, and the abundance of Bacteroides was strongly correlated with the tnaA gene., Discussion: Our results indicated a clear difference in the gut microbiota and serum metabolites of postmenopausal women. Specifically altered bacteria and derived metabolites were closely associated with the BMD index and bone turnover markers, indicating the potential of the gut microbiota and serum metabolites as modifiable factors and therapeutic targets for preventing osteoporosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yan, Wang, Yu, Qi, Li, Nan, Wang, Luo, Hua and Wang.)

The Echinococcus granulosus sensu lato species complex is responsible for the neglected zoonotic disease known as cystic echinococcosis (CE). Humans and livestock are infected via fecal-oral transmission. CE remains prevalent in Western China, Central Asia, South America, Eastern Africa, and the Mediterranean. Approximately one million individuals worldwide are affected, influencing veterinary and public health, as well as social and economic matters. The infection causes slow-growing cysts, predominantly in the liver and lungs, but can also develop in other organs. The exact progression of these cysts is uncertain. This study aimed to understand the survival mechanisms of liver and lung CE cysts from cattle by determining their metabolite profiles through metabolomics and multivariate statistical analyses. Non-targeted metabolomic approaches were conducted using quadrupole-time-of-flight liquid chromatography/mass spectrometry (LC-QTOF-MS) to distinguish between liver and lung CE cysts. Data processing to extract the peaks on complex chromatograms was performed using XCMS. PCA and OPLS-DA plots obtained through multiple statistical analyses showed interactions of metabolites within and between groups. Metabolites such as glutathione, prostaglandin, folic acid, and cortisol that cause different immunological reactions have been identified both in liver and lung hydatid cysts, but in different ratios. Considering the differences in the metabolomic profiles of the liver and lung cysts determined in the present study will contribute research to enlighten the nature of the cyst and develop specific therapeutic strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The leaves of Araucaria cunninghamii are known to be nonedible and toxic. Previous studies have identified biflavones in various Araucaria species. This study aimed to investigate the in vitro cytotoxicity of the isolated compounds from Araucaria cunninghamii after metabolomics and network pharmacological analysis. Methanol extract of Araucaria cunninghamii leaves was subjected to bioassay-guided fractionation. The active fraction was analyzed using LC-HRMS, through strategic database mining, by comparing the data to the Dictionary of Natural Products to identify 12 biflavones, along with abietic acid, beta-sitosterol, and phthalate. Eight compounds were screened for network pharmacology study, where in silico ADME analysis, prediction of gene targets, compound-gene-pathway network and hierarchical network analysis, protein-protein interaction, KEGG pathway, and Gene Ontology analyses were done, that showed PI3KR1, EGFR, GSK3B, and ABCB1 as the common targets for all the compounds that may act in the gastric cancer pathway. Simultaneously, four biflavones were isolated via chromatography and identified through NMR as dimeric apigenin with varying methoxy substitutions. Cytotoxicity study against the AGS cell line for gastric cancer showed that AC1 biflavone (IC 50 90.58 μM) exhibits the highest cytotoxicity and monomeric apigenin (IC 50 174.5 μM) the lowest. Besides, the biflavones were docked to the previously identified targets to analyze their binding affinities, and all the ligands were found to bind with energy ≤-7 Kcal/mol., (© 2024 John Wiley & Sons Ltd.)

Broccoli is commonly consumed as food and as medicine. However, comprehensive metabolic profiling of two broccoli varieties, Romanesco broccoli (RB) and purple broccoli (PB), in relation to their anticholinergic activity has not been fully disclosed. A total of 110 compounds were tentatively identified using UPLC-Q-TOF-MS metabolomics. Distinctively different metabolomic profiles of the two varieties were revealed by principal component analysis (PCA). Furthermore, by volcano diagram analysis, it was found that PB had a significantly higher content of phenolic acids, flavonoids, and glucosinolates, indicating the different beneficial health potentials of PB that demonstrated higher antioxidant and anticholinergic activities. Moreover, Pearson's correlation analysis revealed 18 metabolites, mainly phenolic and sulfur compounds, as the main bioactive. The binding affinity of these biomarkers to the active sites of acetyl- and butyryl-cholinesterase enzymes was further validated using molecular docking studies. Results emphasize the broccoli significance as a functional food and nutraceutical source and highlight its beneficial effects against Alzheimer's disease., (© 2024. The Author(s).)

Introduction: Diabetes (T3cDM) secondary to chronic pancreatitis (CP) arises due to endocrine dysfunction and metabolic dysregulations. Currently, diagnostic tests are not available to identify patients who may progress from normoglycemia to hyperglycemia in CP. We conducted plasma metabolomic profiling to diagnose glycemic alterations early in the course of disease., Methods: Liquid chromatography-tandem mass spectrometry was used to generate untargeted, targeted plasma metabolomic profiles in patients with CP, controls (n = 445) following TRIPOD guidelines. Patients were stratified based on glucose tolerance tests following ADA guidelines. Multivariate analysis was performed using partial least squares discriminant analysis to assess discriminatory ability of metabolites among stratified groups. COMBIROC and logistic regression were used to derive biomarker signatures. AI-ML tool (Rapidminer) was used to verify these preliminary results., Results: Ceramide, lysophosphatidylethanolamine, phosphatidylcholine, lysophosphatidic acid (LPA), phosphatidylethanolamine, carnitine, and lysophosphatidylcholine discriminated T3cDM CP patients from healthy controls with AUC 93% (95% CI 0.81-0.98, P < 0.0001), and integration with pancreatic morphology improved AUC to 100% (95% CI 0.93-1.00, P < 0.0001). LPA, phosphatidylinositol, and ceramide discriminated nondiabetic CP with glycemic alterations (pre-diabetic CP); AUC 66% (95% CI 0.55-0.76, P = 0.1), and integration enhanced AUC to 74% (95% CI 0.55-0.88, P = 0.86). T3cDM was distinguished from prediabetic by LPA, phosphatidylinositol, and sphinganine (AUC 70%; 95% CI 0.54-0.83, P = 0.08), and integration improved AUC to 83% (95% CI 0.68-0.93, P = 0.05). CombiROC cutoff identified 75% and 78% prediabetes in validation 1 and 2 cohorts. Random forest algorithm assessed performance of integrated panel demonstrating AUC of 72% in predicting glycemic alterations., Discussion: We report for the first time that a panel of metabolites integrated with pancreatic morphology detects glycemia progression before HbA1c in patients with CP., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)

Untargeted metabolomics investigations have characterized metabolic disturbances associated with various diseases in domestic cats. However, the pre-analytic stability of serum metabolites in the species is unknown. Our objective was to compare serum metabolomes from healthy cats stored at -20°C for up to 12 months to samples stored at -80°C. Serum samples from 8 adult, healthy cats were stored at -20°C for 6 months, -20°C for 12 months, or -80°C for 12 months. Untargeted liquid chromatography-mass spectrometry was used to generate serum metabolite profiles containing relative abundances of 733 serum metabolites that were compared among storage conditions. Unsupervised analysis with principal component analysis and hierarchical clustering of Euclidian distances revealed separation of samples from individual cats regardless of storage condition. Linear mixed-effects models identified 75 metabolites that differed significantly among storage conditions. Intraclass correlation analysis (ICC) classified most serum metabolites as having excellent (ICC ≥ 0.9; 33%) or moderate (ICC 0.75-0.89; 33%) stability, whereas 13% had poor stability (ICC < 0.5). Biochemicals that varied significantly among storage conditions and classified with poor stability included glutathione metabolites, amino acids, gamma-glutamyl amino acids, and polyunsaturated fatty acids. The benzoate; glycine, serine and threonine; tryptophan; chemical (xenobiotics); acetylated peptide, and primary bile acid sub pathways were enriched among highly stable metabolites, whereas the monohydroxy fatty acid, polyunsaturated fatty, and monoacylglycerol sub-pathways were enriched among unstable metabolites. Our findings suggest that serum metabolome profiles are representative of the cat of origin, regardless of storage condition. However, changes in specific serum metabolites, especially glutathione, gamma-glutamyl amino acid, and fatty acid metabolites were consistent with increased sample oxidation during storage at -20°C compared with -80°C. By investigating the pre-analytic stability of serum metabolites, this investigation provides valuable insights that could aid other investigators in planning and interpreting studies of serum metabolomes in cats., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Barko et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aspergillus cristatus is a crucial edible fungus used in tea fermentation. In the industrial fermentation process, the fungus experiences a low to high osmotic pressure environment. To explore the law of material metabolism changes during osmotic pressure changes, NaCl was used here to construct different osmotic pressure environments. Liquid chromatography-mass spectrometry (LC-MS) combined with multivariate analysis was performed to analyze the distribution and composition of A. cristatus under different salt concentrations. At the same time, the in vitro antioxidant activity was evaluated. The LC-MS metabolomics analysis revealed significant differences between three A. cristatus mycelium samples grown on media with and without NaCl concentrations of 8% and 18%. The contents of gibberellin A3, A124, and prostaglandin A2 related to mycelial growth and those of arabitol and fructose-1,6-diphosphate related to osmotic pressure regulation were significantly reduced at high NaCl concentrations. The biosynthesis of energy-related pantothenol and pantothenic acid and antagonism-related fluvastatin, aflatoxin, and alternariol significantly increased at high NaCl concentrations. Several antioxidant capacities of A. cristatus mycelia were directly related to osmotic pressure and exhibited a significant downward trend with an increase in environmental osmotic pressure. The aforementioned results indicate that A. cristatus adapts to changes in salt concentration by adjusting their metabolite synthesis. At the same time, a unique set of strategies was developed to cope with high salt stress, including growth restriction, osmotic pressure balance, oxidative stress response, antioxidant defense, and survival competition.

The burgeoning field of metabolomics has piqued the interest of researchers in the context of benign gallbladder diseases, which include conditions such as gallbladder polyps, gallstones, and cholecystitis, which are common digestive system disorders. As metabolomics continues to advance, researchers have increasingly focused their attention on its applicability in the study of benign gallbladder diseases to provide new perspectives for diagnostic, therapeutic, and prognostic evaluation. This comprehensive review primarily describes the techniques of liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance and their respective applications in the study of benign gallbladder disease. Metabolomics has made remarkable progress in various aspects of these diseases, ranging from early diagnosis, etiological research, assessment of disease progression and prognosis, and optimization of therapeutic strategies. However, challenges remain in the field of metabolomics in the study of benign gallbladder diseases. These include issues related to data processing and analysis, biomarker discovery and validation, interdisciplinary research integration, and the advancement of personalized medicine. This article attempts to summarize research findings to date, highlight future research directions, and provide a reference point for metabolomics research in benign gallbladder disease., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Introduction: Prader-Willi syndrome (PWS) is a rare disease, which shows a peculiar clinical phenotype, including obesity, which is different from essential obesity (EOB). Metabolomics might represent a valuable tool to reveal the biochemical mechanisms/pathways underlying clinical differences between PWS and EOB. The aim of the present (case-control, retrospective) study was to determine the metabolomic profile that characterizes PWS compared to EOB., Methods: A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted metabolomic approach was used to measure a total of 188 endogenous metabolites in plasma samples of 32 patients with PWS (F/M = 23/9; age: 31.6 ± 9.2 years; body mass index [BMI]: 42.1 ± 7.0 kg/m 2 ), compared to a sex-, age- and BMI-matched group of patients with EOB (F/M = 23/9; age: 31.4 ± 6.9 years; BMI: 43.5 ± 3.5 kg/m 2 )., Results: Body composition in PWS was different when compared to EOB, with increased fat mass and decreased fat-free mass. Glycemia and HDL cholesterol were higher in patients with PWS than in those with EOB, while insulinemia was lower, as well as heart rate. Resting energy expenditure was lower in the group with PWS than in the one with EOB, a difference that was missed after fat-free mass correction. Carrying out a series of Tobit multivariable linear regressions, adjusted for sex, diastolic blood pressure, and C reactive protein, a total of 28 metabolites was found to be associated with PWS (vs. non-PWS, i.e., EOB), including 9 phosphatidylcholines (PCs) ae, 5 PCs aa, all PCs aa, 7 lysoPCs a, all lysoPCs, 4 acetylcarnitines, and 1 sphingomyelin, all of which were higher in PWS than EOB., Conclusions: PWS exhibits a specific metabolomic profile when compared to EOB, suggesting a different regulation of some biochemical pathways, fundamentally related to lipid metabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Rigamonti, Polledri, Favero, Caroli, Bondesan, Grugni, Mai, Cella, Fustinoni and Sartorio.)

Background: Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia., Methods: Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia., Results: 16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia., Conclusions: Our study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia., (© 2024. The Author(s).)

Background: Fluoride-resistant Streptococcus mutans (S. mutans) strains have developed due to the wide use of fluoride in dental caries prevention. However, the metabolomics of fluoride-resistant S. mutans remains unclear., Objective: This study aimed to identify metabolites that discriminate fluoride-resistant from wild-type S. mutans., Materials and Methods: Cell supernatants from fluoride-resistant and wild-type S. mutans were collected and analyzed by liquid chromatography-mass spectrometry. Principal components analysis and partial least-squares discriminant analysis were performed for the statistical analysis by variable influence on projection (VIP > 2.0) and p value (Mann-Whitney test, p < 0.05). Metabolites were assessed qualitatively using the Human Metabolome Database version 2.0 ( http://www.hmdb.ca ), or Kyoto Encyclopedia of Genes and Genomes ( http://www.kegg.jp ), and Metaboanalyst 6.0 ( https://www.metaboanalyst.ca )., Results: Fourteen metabolites differed significantly between fluoride-resistant and wild-type strains in the early log phase. Among these metabolites, 5 were identified. There were 32 differential metabolites between the two strains in the stationary phase, 13 of which were identified. The pyrimidine metabolism for S. mutans FR was matched with the metabolic pathway., Conclusions: The fructose-1,6-bisphosphate concentration increased in fluoride-resistant strains under acidic conditions, suggesting enhanced acidogenicity and acid tolerance. This metabolite may be a promising target for elucidating the cariogenic and fluoride resistant mechanisms of S. mutans., (© 2024. The Author(s).)

Erythrodermic psoriasis (EP) is a rare and life-threatening disease, the pathogenesis of which remains to be largely unknown. Metabolomics analysis can provide global information on disease pathophysiology, candidate biomarkers, and potential intervention strategies. To gain a better understanding of the mechanisms of EP and explore the serum metabolic signature of EP, we conducted an untargeted metabolomics analysis from 20 EP patients and 20 healthy controls. Furthermore, targeted metabolomics for focused metabolites were identified in the serum samples of 30 EP patients and 30 psoriasis vulgaris (PsV) patients. In the untargeted analysis, a total of 2992 molecular features were extracted from each sample, and the peak intensity of each feature was obtained. Principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) revealed significant difference between groups. After screening, 98 metabolites were found to be significantly dysregulated in EP, including 67 down-regulated and 31 up-regulated. EP patients had lower levels of L-tryptophan, L-isoleucine, retinol, lysophosphatidylcholine (LPC), and higher levels of betaine and uric acid. KEGG analysis showed differential metabolites were enriched in amino acid metabolism and glycerophospholipid metabolism. The targeted metabolomics showed lower L-tryptophan in EP than PsV with significant difference and L-tryptophan levels were negatively correlated with the PASI scores. The serum metabolic signature of EP was discovered. Amino acid and glycerophospholipid metabolism were dysregulated in EP. The metabolite differences provide clues for pathogenesis of EP and they may provide insights for therapeutic interventions., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

This study aimed to determine the effect of different frozen temperatures during storage on the quality of Antarctic krill (Euphausia superba) and assess the change at the metabolite level via a combination of physicochemical property analysis, liquid chromatography-tandem mass spectrometry (LC-MS) based non-targeted metabolomics profiling. Regarding samples stored at -20 °C, the expressions of 7055 metabolites were elevated, while 2313 were downregulated. Lipids and lipid molecules had the highest proportion of differential metabolites. A total of 432 discriminatory metabolites with Kyoto Encyclopedia of Genes and Genomes (KEGG) IDs was obtained. We also observed that the concentrations of differential bitter free amino acids (FAAs) and oxidation products of arachidonic and linoleic acid increased. Moreover, as the storage temperature increased, the freshness, umami, and sweetness components were considerably reduced. Furthermore, results indicated that the color, pH and water-holding capacity (WHC) were potential indicators of quality deterioration, while inosinic acid was a probable biomarker for umami degradation of frozen Antarctic krill. In conclusion, this study demonstrates that storage at lower temperatures can be beneficial for maintaining the freshness of Antarctic krill from macro and micro perspectives., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

To utilize metabolomics in conjunction with RNA sequencing to identify biomarkers in the blood of sepsis patients and discover novel targets for diagnosing and treating sepsis. In January 2019 and December 2020, blood samples were collected from a cohort of 16 patients diagnosed with sepsis and 11 patients diagnosed with systemic inflammatory response syndrome (SIRS). Non-targeted metabolomics analysis was conducted using liquid chromatography coupled with mass spectrometry (LC-MS/MS technology), while gene sequencing was performed using RNA sequencing. Afterward, the metabolite data and sequencing data underwent quality control and difference analysis, with a fold change (FC) greater than or equal to 2 and a false discovery rate (FDR) less than 0.05.Co-analysis was then performed to identify differential factors with consistent expression trends based on the metabolic pathway context; KEGG enrichment analysis was performed on the crossover factors, and Meta-analysis of the targets was performed at the transcriptome level using the public dataset. In the end, a total of five samples of single nucleated cells from peripheral blood (two normal controls, one with systemic inflammatory response syndrome, and two with sepsis) were collected and examined to determine the cellular location of the essential genes using 10× single cell RNA sequencing (scRNA-seq). A total of 485 genes and 1083 metabolites were found to be differentially expressed in the sepsis group compared to the SIRS group. Among these, 40 genes were found to be differentially expressed in both the metabolome and transcriptome. Functional enrichment analysis revealed that these genes were primarily involved in biological processes related to inflammatory response, immune regulation, and amino acid metabolism. Furthermore, a meta-analysis identified four genes, namely ITGAM, CD44, C3AR1, and IL2RG, which were highly expressed in the sepsis group compared to the normal group (P < 0.05). Additionally, scRNA-seq analysis revealed that the core genes ITGAM and C3AR1 were predominantly localized within the macrophage lineage. The primary genes ITGAM and C3AR1 exhibit predominant expression in macrophages, which play a significant role in inflammatory and immune responses. Moreover, these genes show elevated expression levels in the plasma of individuals with sepsis, indicating their potential as valuable subjects for further research in sepsis., (© 2024. The Author(s).)

Liver cirrhosis (LC) represents a significant hepatic disorder that persistently commands the attention of the scientific community, especially concerning its pathogenesis and therapeutic approaches. Metabolomics, the comprehensive profiling of an organism's metabolome, has been increasingly applied in the research of cirrhosis over the past decade. This review summarizes the recent advancements and applications of metabolomics within the context of LC research, in recent five years. It highlights the role of metabolomics in the diagnosis of LC, the assessment of prognostic markers, and the evaluation of therapeutic outcomes. The discussion focuses on the potential and challenges of metabolomics in LC research, including the evolution of analytical technologies, advancements in bioinformatics, and the challenges impeding clinical implementation. Additionally, the review anticipates the forthcoming developments in metabolomics related to LC research, with the objective of facilitating innovative approaches for early detection and intervention in LC., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Studies of gastrointestinal physiology and the gut microbiome often consider the influence of intestinal region on experimental endpoints. However, this same consideration is not often applied to the gut metabolome. Understanding the contribution of gut regionality may be critically important to the rapidly changing metabolic environments, such as during pregnancy., Objectives: We sought to characterize the difference in the gut metabolome in pregnant mice stratified by region-comparing the small intestine, cecum, and feces. Pre-pregnancy feces were collected to understand the influence of pregnancy on the fecal metabolome., Methods: Feces were collected from CD-1 female mice before breeding. On gestation day (GD) 18, gut contents were collected from the small intestine, cecum, and descending colon. Metabolites were analyzed with LC-MS/MS using the Biocrates MetaboINDICATOR™ MxP® Quant 500 kit., Results: Of the 104 small molecule metabolites meeting analysis criteria, we found that 84 (81%) were differentially abundant based on gut region. The most significant regional comparison observed was between the cecum and small intestines, with 52 (50%) differentially abundant metabolites. Pregnancy itself altered 41 (39.4%) fecal small molecule metabolites., Conclusions: The regional variation observed in the gut metabolome are likely due to the microbial and physiological differences between the different parts of the intestines. Additionally, pregnancy impacts the fecal metabolome, which may be due to evolving needs of both the dam and fetus., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Peak alignment is a crucial data-processing step in untargeted metabolomics analysis that aims to integrate metabolite data from multiple liquid chromatography-mass spectrometry (LC-MS) batches for enhanced comparability and reliability. However, slight variations in the chromatographic separation conditions can result in retention time (RT) shifts between consecutive analyses, adversely affecting peak alignment accuracy. In this study, we present a retention index (RI)-based chromatographic peak-shift correction (CPSC) strategy to address RT shifts and align chromatographic peaks for metabolomics studies. A series of N -acyl glycine homologues (C2-C23) was synthesized as calibrants, and an LC RI system was established. This system effectively corrected RT shifts arising from variations in flow rate, gradient elution, instrument systems, and chromatographic columns. Leveraging the RI system, we successfully adjusted the RT of raw data to mitigate RT shifts and then implemented the Joint Aligner algorithm for peak alignment. We assessed the accuracy of the RI-based CPSC strategy using pooled human fecal samples as a test model. Notably, the application of the RI-based CPSC strategy to a long-term dataset spanning 157 d as an illustration revealed a significant enhancement in peak alignment accuracy from 15.5% to 80.9%, indicating its ability to substantially improve peak-alignment precision in multibatch LC-MS analyses.

This study aimed to explore the relationship between alterations in plasma metabolites and treatment responses amongst antipsychotic-naïve female patients with schizophrenia. A total of 38 antipsychotic-naïve female schizophrenia patients (ANS) and 19 healthy female controls (HC) were recruited. Plasma samples were obtained from all participants, and targeted metabolomics were measured with FIA-MS/MS and LC-MS/MS. The positive and negative syndrome scale (PANSS) was used to assess the severity of psychotic symptoms before and after eight weeks of treatment. Receiver operator characteristics (ROC) curves were used to predict diagnostic and therapeutic responses. A total of 186 metabolites passed quality control procedures and were used in statistical analysis to identify potential biomarkers. Before treatment, the ANS patients had lower levels of γ -Aminobutyric Acid (GABA) and higher levels of Cholesteryl esters (CE) (20:3), Cholic Acid (CA) and Glycocholic Acid (GCA) compared to the HCs. These four differential metabonomic markers were synthesised into a combinatorial biomarker panel. This panel significantly distinguished ANS from HC. Moreover, this biomarker panel was able to effectively predict therapeutic responses. Our results suggest that plasma CE (20:3), CA, GCA, and GABA levels may be useful for diagnosing and predicting antipsychotic efficacy amongst female schizophrenia patients.