Small Molecule Metabolites Research Articles

DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data

BackgroundMetabolomics is a high-throughput technology that measures small molecule metabolites in cells, tissues or biofluids. Analysis of metabolomics data is a multi-step process that involves data processing, quality control and normalization, followed by statistical and bioinformatics analysis. The latter step often involves pathway analysis to aid biological interpretation of the data. This approach is limited to endogenous metabolites that can be readily mapped to metabolic pathways. An alternative to pathway analysis that can be used for any classes of metabolites, including unknown compounds that are ubiquitous in untargeted metabolomics data, involves defining metabolite-metabolite interactions using experimental data. Our group has developed several network-based methods that use partial correlations of experimentally determined metabolite measurements. These were implemented in CorrelationCalculator and Filigree, two software tools for the analysis of metabolomics data we developed previously. The latter tool implements the Differential Network Enrichment Analysis (DNEA) algorithm. This analysis is useful for building differential networks from metabolomics data containing two experimental groups and identifying differentially enriched metabolic modules. While Filigree is a user-friendly tool, it has certain limitations when used for the analysis of large-scale metabolomics datasets.ResultsWe developed the DNEA R package for the data-driven network analysis of metabolomics data. We present the DNEA workflow and functionality, algorithm enhancements implemented with respect to the package’s predecessor, Filigree, and discuss best practices for analyses. We tested the performance of the DNEA R package and illustrated its features using publicly available metabolomics data from the environmental determinants of diabetes in the young. To our knowledge, this package is the only publicly available tool designed for the construction of biological networks and subsequent enrichment testing for datasets containing exogenous, secondary, and unknown compounds. This greatly expands the scope of traditional enrichment analysis tools that can be used to analyze a relatively small set of well-annotated metabolites.ConclusionsThe DNEA R package is a more flexible and powerful implementation of our previously published software tool, Filigree. The modular structure of the package, along with the parallel processing framework built into the most computationally extensive steps of the algorithm, make it a powerful tool for the analysis of large and complex metabolomics datasets.

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants.

The plant community has a strong track record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g. 10× genomics) has resulted in an explosion of single-cell and nuclei datasets that can be positioned in an in situ context within tissues (e.g. a cell atlas). In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due in part to upfront cost, ease-of-use, and access to expertise. Conversely, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis, as the search for plant-based natural products has played a significant role in improving human health throughout history. As the plant sciences field now aims to fully define cell states, cell-specific regulatory networks, metabolic asymmetry and phenotypes, the measurement of proteins and metabolites at the single-cell level will be paramount. As a result of these efforts, the plant community will unlock exciting opportunities to accelerate discovery and drive toward meaningful translational outcomes.

2-Hydroxyisobutyric acid targeted binding to MT-ND3 boosts mitochondrial respiratory chain homeostasis in hippocampus to rescue diabetic cognitive impairment

BackgroundThe prevalence of diabetic cognitive impairment (DCI) is significant, some studies have shown that it is related to mitochondrial respiratory chain homeostasis, but the specific mechanism is not clear. 2-hydroxyisobutyric acid (2-HIBA) is a novel short-chain fatty acid with potential applications in the treatment of metabolic diseases because it can regulate mitochondrial disorders. Our aim was to explore a novel mechanism of action for 2-HIBA in the treatment of DCI in mitochondrial respiratory chain homeostasis. MethodsMetabolic substances and differentially active metabolic pathways in the serum of diseased mice were identified based on multi-omics analysis. The nanoLC-Obitrap-MS technology was utilized to detect the content of selected small molecules with differential metabolic activity in the hippocampus and mitochondria of mice to evaluate their permeability through the blood-brain barrier (BBB) and outer mitochondrial membrane. A combination of behavioral, proteomic, and molecular biology approaches was used to explore specific regulatory mechanisms and identify potential pharmacological targets. Additionally, using techniques such as protein thermal shift, drug affinity responsive target stability (DARTS), hydrolase stability, and surface plasmon resonance (SPR) experiments, we demonstrated the direct binding effects of small molecule metabolites with protein targets. Results2-HIBA was found to directly ameliorate cognitive dysfunction in db/db mice by penetrating the blood-brain barrier and reversing the decrease in the protein content of NADH dehydrogenase 3 (MT-ND3) in the hippocampus through direct binding to ND3. This action helps maintain the stability of NAD+/NADH and regulate the mitochondrial respiratory chain balance. Furthermore, a combined medication plant agonist of 2-HIBA can enhance the expression of MT-ND3, thereby improving cognitive dysfunction in mice. ConclusionMT-ND3 is a crucial target for improving diabetic cognitive dysfunction, and 2-HIBA can directly bind to the MT-ND3 protein to alleviate the functional impairment of the mitochondrial respiratory chain in mice to treat DCI.

Abstract 4113263: Serum Metabolomics Adds Predictive Value to Clinical and Polygenic Risk Scores for Atrial Fibrillation: A UK Biobank study of >240,000 Patients

Background: Atrial fibrillation (AF) poses substantial morbidity and mortality burdens globally. It is critical to identify individuals at high-risk for AF to implement both lifestyle modifications and close monitoring for initiation of oral anticoagulants. Currently, risk prediction in AF relies on clinical scores such as CHARGE-AF. Small molecule metabolites are thought to play a role in AF pathogenesis, but the additional predictive value of metabolomics over clinical and genetic risk factors is unknown. Using the UK Biobank (UKBB), we sought to perform this evaluation. Methods: We included all UKBB participants with complete 1 H-NMR metabolite measurements. We excluded participants with prior history of AF or with incomplete AF Polygenic Risk Score (AF-PRS) or CHARGE-AF components. The final cohort included 240,628 patients. In-patient records, primary care notes, and death registries were queried to identify patients who had developed incident AF within 5 years of enrollment. The cohort was divided into a 80/20:Train/Test split. We compared the performance of an Elastic-Net regularized Cox Proportional Hazards (EN-CPH) model trained on CHARGE-AF, AF-PRS, and the full 170 metabolite panel to a CPH model trained only on CHARGE-AF and AF-PRS. Results: Within 5 years, 4,174 (1.7%) patients developed AF. Compared to the control population, the incident AF cases were more likely to be older (62 vs. 56, p<0.001), male (65% vs 45%, p<0.001), and have higher CHARGE-AF and AF-PRS scores (p<0.001). After training the EN-CPH model on CHARGE-AF, AF-PRS, and 170 metabolites, the final model included 8 metabolites on top of CHARGE-AF (HR: 1.28) and AF-PRS (HR: 1.11). After adjusting for CHARGE-AF and AF-PRS, creatinine level was associated with increased risk of AF (HR: 1.01) while linoleic acid level (HR: 0.985) was associated with decreased risk. Furthermore, total cholesterol, esterified cholesterol, free cholesterol, cholesteryl esters in IDL, omega-6 fatty acids, and cholesterol in large LDL were associated with HR 0.993-0.999. The EN-CPH model out-performed the CPH model without metabolomics on the test set (AUC 0.786 vs 0.753, p < 0.001). Conclusions: The addition of metabolomics to clinical and genomic risk scores improves prediction of 5-year incident AF within a general population. This study highlights the significance of the metabolome as an independent prognosticator of AF risk. Further study of the mechanisms by which selected metabolites alter AF risk is needed.

Regulating role of Pleurotus ostreatus insoluble dietary fiber in high fat diet induced obesity in rats based on proteomics and metabolomics analyses

This study aims to reveal the effects of Pleurotus ostreatus insoluble dietary fiber (POIDF) on liver protein and cecal metabolites in obese rats and its potential mechanism by intestinal microbes. It was found that POIDF contained the structural characteristics of cellulose and hemicellulose, as well as amorphous diffraction peaks. POIDF could reduce the body weight and organ index of obese rats, regulate dyslipidemia, and improve the pathological changes of liver and epididymis fat. Further experimental results showed that POIDF could regulate the abundance of bacteria related to lipid metabolism, and maintain intestinal homeostasis. The metabolomics results showed that the fatty acyls pathway in the cecum contents was the pathway with the highest concentration of small molecule metabolites. POIDF supplementation regulated the expression of liver key proteins, as well as biosynthesis of amino acids, steroid biosynthesis, arachidonic acid metabolism and PPAR signaling pathway. Omics association analysis found that POIDF could further regulate liver proteins and their signaling pathways, regulate the levels of fatty acyls and amino acid metabolites in the gut and the enrichment of related pathways, and play a therapeutic or preventive role in obesity after degradation by intestinal microbiota.

COLMAR1d: A Web Server for Automated, Quantitative One-Dimensional Nuclear Magnetic Resonance-Based Metabolomics at Arbitrary Magnetic Fields.

The field of metabolomics, which is quintessential in today's omics research, involves the large-scale detection, identification, and quantification of small-molecule metabolites in a wide range of biological samples. Nuclear magnetic resonance spectroscopy (NMR) has emerged as a powerful tool for metabolomics due to its high resolution, reproducibility, and exceptional quantitative nature. One of the key bottlenecks of metabolomics studies, however, remains the accurate and automated analysis of the resulting NMR spectra with good accuracy and minimal human intervention. Here, we present the COLMAR1d platform, consisting of a public web server and an optimized database, for one-dimensional (1D) NMR-based metabolomics analysis to address these challenges. The COLMAR1d database comprises more than 480 metabolites from GISSMO enabling a database query of spectra measured at arbitrary magnetic field strengths, as is demonstrated for spectra acquired between 1H resonance frequencies of 80 MHz and 1.2 GHz of mouse serum, DMEM cell growth medium, and wine. COLMAR1d combines the GISSMO metabolomics database concept with the latest tools for automated processing, spectral deconvolution, database querying, and globally optimized mixture analysis for improved accuracy and efficiency. By leveraging advanced computational algorithms, COLMAR1d offers a user-friendly, automated platform for quantitative 1D NMR-based metabolomics analysis allowing a wide range of applications, including biomarker discovery, metabolic pathway elucidation, and integration with multiomics strategies.

Study on biotransformation and absorption of genistin based on fecal microbiota and Caco-2 cell.

Genistin, as a kind of natural isoflavone glycoside, has good biological activity, and its weak absorption makes it closely related to intestinal flora. However, the role of the intestinal flora is still unclear and whether the metabolites produced by the intestinal flora are absorbed systemically is also variable. Genistin was fermented for 24h based on fecal bacteria fermentation technology. The components were qualitatively and quantitatively analyzed by HPLC and UHPLC-Q-Exactive Orbitrap Mass spectrometry. The composition of intestinal flora in fermentation samples from fecal bacteria was detected by 16S rRNA sequencing. Five representative probiotics were cultured in vitro and fermented with genistin to determine similarities and differences in genistin metabolites by different bacteria at different times. Finally, the absorption results of metabolites by fermentation were verified by a Caco-2 cell monolayer. The HPLC results of fecal fermentation showed that genistein levels increased from 0.0139 ± 0.0057mg/mL to 0.0426 ± 0.0251mg/mL and two new metabolites were produced. A total of 46 metabolites following fecal fermentation were identified, resulting from various biotransformation reaction products, such as decarbonylation, hydroxylation, and methylation. Simultaneously, the 16S rRNA results showed that the intestinal flora changed significantly before and after fermentation and that the intestinal microorganisms in the control (Con) group and the fermentation (Fer) group showed a significant separation trend. Five genera, Lactobacillus, Bifidobacterium, Parabacteroides, Sutterella, and Dorea, were considered the dominant flora for genistin fermentation. The qualitative results of fermentation of genistin by five probiotics at different times showed that there were significant differences in small molecule metabolites by fermentation of different bacteria. Meanwhile, most metabolites could be identified following fecal bacteria fermentation, which verified the importance of the dominant bacteria in the feces for the biotransformation of components. Finally, the absorption results of the metabolites based on the Caco-2 cell monolayer showed that 14 metabolites could be absorbed into the circulation in vivo through the mesentery. The small molecule metabolites of genistin by fermentation of fecal bacteria can be well absorbed systemically by the body. These studies provide a reference value for explaining the transformation and absorption of flavonoid glycosides in the intestine.

Bacterial small molecule metabolites implicated in gastrointestinal cancer development.

Numerous associations have been identified between cancer and the composition and function of the human microbiome. As cancer remains the second leading global cause of mortality, investigating the carcinogenic contributions of microbiome members could advance our understanding of cancer risk and support potential therapeutic interventions. Although fluctuations in bacterial species have been associated with cancer progression, studying their small molecule metabolites offers one avenue to establish support for causal relationships and the molecular mechanisms governing host-microorganism interactions. In this Review, we explore the expanding repertoire of small molecule metabolites and their mechanisms implicated in the risk of developing gastrointestinal cancers.

Riboswitch Mechanisms for Regulation of P1 Helix Stability.

Riboswitches are highly structured RNA regulators of gene expression. Although found in all three domains of life, they are particularly abundant and widespread in bacteria, including many human pathogens, thus making them an attractive target for antimicrobial development. Moreover, the functional versatility of riboswitches to recognize a myriad of ligands, including ions, amino acids, and diverse small-molecule metabolites, has enabled the generation of synthetic aptamers that have been used as molecular probes, sensors, and regulatory RNA devices. Generally speaking, a riboswitch consists of a ligand-sensing aptamer domain and an expression platform, whose genetic control is achieved through the formation of mutually exclusive secondary structures in a ligand-dependent manner. For most riboswitches, this involves formation of the aptamer's P1 helix and the regulation of its stability, whose competing structure turns gene expression ON/OFF at the level of transcription or translation. Structural knowledge of the conformational changes involving the P1 regulatory helix, therefore, is essential in understanding the structural basis for ligand-induced conformational switching. This review provides a summary of riboswitch cases for which ligand-free and ligand-bound structures have been determined. Comparative analyses of these structures illustrate the uniqueness of these riboswitches, not only in ligand sensing but also in the various structural mechanisms used to achieve the same end of regulating switch helix stability. In all cases, the ligand stabilizes the P1 helix primarily through coaxial stacking interactions that promote helical continuity.

Artemisia Argyi essential oil ameliorates acetaminophen-induced hepatotoxicity via CYP2E1 and γ-glutamyl cycle reprogramming

BackgroundThe hepatotoxicity induced by acetaminophen (APAP), a commonly used antipyretic, analgesic and anti-inflammatory drug in clinical practice, has received accumulated attention. Artemisia argyi essential oil (AAEO), a volatile oil component extracted from traditional Chinese medicine Artemisia argyi H.Lév. & Vaniot, has great hepatoprotective effects. However, the potential role of AAEO in APAP-induced hepatotoxicity has not been characterized. The present study aimed to investigate the effects of AAEO on hepatic metabolic changes in mice exposed to APAP. MethodsIn this study, 300.00 mg/kg acetaminophen was used to establish liver injury model in C57BL/6 J mice. Hepatoprotective effect of AAEO on APAP-induced hepatotoxicity in mice was investigated by detecting liver function enzymes and histopathological examination. Secondly, UPLC-MS/MS was used to analyze the to analyze the small molecule metabolites and metabolic pathways induced by AAEO treatment; In addition, the effect of AAEO on APAP-induced oxidative stress and inflammation were evaluated by detecting the levels of glutathione peroxidase 4, malondialdehyde, reactive oxygen species and inflammatory factors. Finally, the active components of AAEO were preliminarily screened by cellular assays. The hepatoprotective effect of AAEO against APAP-induced hepatotoxicity was examined through the Western blotting, after the CYP2E1 gene was knocked down in AML12 cells by siRNA transfection. ResultsCompared with the APAP group, AAEO could reduce the abnormal increase in the levels of liver function enzymes caused by APAP. AAEO could enhance the antioxidant capacity by down-regulating the biosynthesis pathway of unsaturated fatty acids and promoting the activity of antioxidant enzymes SOD and CAT in liver tissue induced by APAP. Our study revealed that AAEO promoted GSH synthesis and covalently combined to form APAP-GSH conjugates to reduce the accumulation of APAP in liver tissue. In addition, the chemical constituents in AAEO were analyzed by GC–MS/MS, and it was determined to identify that dihydro-beta-ionone and (-)-verbenone in AAEO might have a significant protective effect on hepatocyte survival after APAP exposure. Further studies on the hepatoprotective mechanism of AAEO indicated that it might reduce the production of toxic metabolites by regulating CYP2E1 levels. ConclusionAAEO exerted hepatoprotective effects on acetaminophen-induced hepatotoxicity in mice via regulating the activity of CYP2E1 and regulating the γ-glutamyl cycle pathway.

Metabolite and microbial community composition of normal and sensory defect Nuodeng hams characterized based on metabolomics and high-throughput sequencing

Sensory defects dry-cured ham usually has an unpleasant taste and smell. To deepen the understanding of the formation mechanism of sensory defect ham, the metabolites and microbial community composition were investigated between normal and sensory defect ham. The results of high-throughput sequencing showed that the excessive accumulation of Enterobacteriaceae and Yeasts and reduced abundance of flavor-related microorganisms may be one of the reasons for the sensory defect hams. 42 differential metabolites were screened by metabolomics, among which amino acids and their derivatives and organic acids were the key metabolites to distinguish sensory defect hams from normal hams. KEGG pathway analysis showed that amino acid metabolism, TCA cycle, purine metabolism and pyrimidine metabolism were the main metabolic pathways of defect hams. These results indicated that small molecule metabolites and microorganisms were closely related to the quality of Nuodeng ham, which provides a scientific basis for the quality control of Nuodeng ham.

Bifidogenic properties of polysaccharides isolated from mushroom Lentinula edodes and enhanced immunostimulatory activities through Bifidobacterial fermentation

Polysaccharides from Lentinula edodes mushrooms (LePS) are well-known for their immunomodulatory activities, which may have a functional connection with probiotic fermentation in the gut microbiota. This study was to evaluate the bifidogenic properties and impact of Bifidobacterial fermentation on the LePS molecules and immunoactivities. Two LePS fractions, LePS-40 (3.97 × 107 Da) and LePS-80 (1.43 × 105 Da) with differences in molecular weight (MW) and chemical composition were isolated from the mushroom hot-water extract and fermented with a Bifidobacterium breve strain. The higher-MW fraction LePS-40 was more significantly consumed and utilized by the bacteria for growth and acetic acid production during the fermentation, due probably to its higher total carbohydrate content and glucose-abundant composition. The Bifidobacterial fermentation caused a notable MW reduction of both LePS fractions and, more interestingly, also led to a higher immunostimulatory activity in RAW 264.7 macrophage cells. Further assessment of the separated fractions by ultrafiltration of the fermentation liquid (digesta) suggested that the immunoactivity was mainly attributed to the partially degraded LePS instead of the small-molecule metabolite products derived from the Bifidobacterial fermentation. In summary, monosaccharide composition was a more significant determinant than MW on the bifidogenic properties of LePS and the immunomodulatory activities after fermentation.

Isotope-Labeled Chemoselective Probes for Labeling, Separation, and Comprehensive Quantitative Analysis of Sub-Metabolome.

The significance of small molecule metabolites as biomarkers for disease diagnosis and prognosis is growing increasingly evident, necessitating the development of highly sensitive qualitative and quantitative methods. Herein, multi-chemoselective probes are synthesized and applied for profiling metabolites, including carboxyl, phosphate, hydroxyl, amino, thiol, and carbonyl compounds. This approach seamlessly integrates magnetic solid-phase materials, orthogonal cleavage sites, isotopic tags, and selective coupling sites, minimizes matrix interference, and enhances quantitative accuracy. Meanwhile, a homemade program, High-Resolution Isotope-Assisted Identification and Quantitative (HRIAIQuant) is developed to process the data, which adeptly filters through 33,874 ion pairs present in human serum, leading to the identification of 701 known metabolites and a remarkable 1,062 potential novel ones. This method is successfully applied to analyze metabolites in multiple brain regions of SAMP8 and SAMR1 models, offering a novel tool for Alzheimer's disease research.

Biochemical approaches for decoding the information stored with metabolites

Molecular data storage is an emerging supplement to conventional information storage methods. In addition to the information storage with DNA or synthetic polymers, a recently proposed strategy that uses small molecule mixtures as information carriers has sparked interest since it is a synthesis-free method. Here, we demonstrate two methods for decoding digital information stored in two sets of small-molecule metabolites. The information is stored as binary code, 0 or 1, based on the absence or presence of each particular metabolite in the mixture. In the first approach, the information was encoded by five metabolites (sarcosine, cholesterol, xanthine, glucose, and galactose) and stored as mixture solutions in a 384-well microplate. The information was read out by cascade enzymatic reactions that can specifically convert the metabolites to a colorimetric product, which was then assayed by a microplate reader. We stored a 60×32-pixel picture (1920 bits) with 384 mixtures of small molecules with a reading accuracy of 96.68 %, and also demonstrated the encoding of a 220-bit text message. Alternatively, another set of six metabolites (bilirubin, uric acid, urea, creatinine, glucose, and triglyceride) was deployed to encode a 78×102-pixel picture (7956 bits) with 1326 mixtures, which was decoded automatically by a biochemistry analyzer with a 98.96 % accuracy. This work showcases that common metabolites can be used as digital molecules for information storage, and the information decoding can be done by accessible instruments in an ordinary biochemical laboratory.

Analysis of Biogenic Amines and Small Molecule Metabolites in Human Diabetic Wound Ulcer Exudate.

Diabetic foot ulcers (DFUs) pose a significant challenge in wound care due to their chronic nature and impaired healing processes. This study examines the biogenic amines and small molecule metabolites present in DFU wound exudates to identify their potential roles in wound healing. Under an IRB-approved protocol, wound fluid samples were collected from 25 diabetic patients and analyzed using ultrahigh-pressure liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry. The analysis identified 721 metabolites, with 402 confirmed through stringent criteria. Key metabolites significantly contributing to the wound exudates include betaine, lactic acid, carnitine, choline, creatine, and metformin (a widely used first-line treatment for type 2 diabetes). These molecules are known to influence wound healing processes, such as collagen synthesis, angiogenesis, inflammation modulation, and energy metabolism. Notably, the presence of drugs such as metformin and beclomethasone in the exudates suggests significant pharmacodynamic interactions that could influence wound healing. Specifically, we discovered that the combined use of insulin and metformin administered systemically significantly increased the concentration of metformin in the wound exudates (from 0.3% ± 0.0 to 3.1% ± 3.4; p = 0.00 49). This study highlights the complexity of DFU exudate composition and underscores the potential for targeted metabolic profiling to develop personalized wound care strategies.

In situ metabolomic analysis of osteonecrosis of the femoral head (ONFH) using MALDI MSI.

Osteonecrosis of the femoral head (ONFH) is a common orthopedic disease characterized by disability and deformity. To better understand ONFH at molecular level and to explore the possibility of early diagnosis, instead of diagnosis based on macroscopic spatial characteristics, a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) method was developed for ONFH disease for the first time. The most challenging step for ONFH MSI is to deal with human bone tissues which are much harder than the other biological samples studied by the reported MSI studies. In this work, the MSI sectioning method of hard bone tissues was established using tender acids and a series of test criteria. Small-molecule metabolites, such as lipids and amino acids, were detected in bone sections, realizing the in situ detection of spatial distribution of biometabolites.By comparing the distribution of metabolites from different regions of normal femoral head, ONFH bone tissue (ONBT), and adjacent ONFH bone tissue (ANBT), the whole process of femoral head from normal stage to necrosis was monitored and visualized at molecular level. Moreover, this developed MSI method was used for metabolomics study of ONFH. 72 differential metabolites were identified, suggesting that disturbances in energy metabolism and lipid metabolism affected the normal life activities of osteoblasts and osteoclasts. This study provides new perspectives for future pathological studies of ONFH.

Genitourinary syndrome of menopause: Evaluation of symptoms, using a questionnaire, in a research setting, before and after treatment.

Genitourinary syndrome of menopause (GSM) is a common condition, yet there is no defined, objective, and reproducible intervention with which to make a diagnosis. There are many different treatment options available, but without the correct diagnosis, affected women are unable to access the right therapy. This paper reports on the questionnaire arm of the VAN study (VAginal Health - What's Normal?) which aimed to evaluate the performance and acceptability of the methods of assessment of GSM, described below. To determine the value of the Day-to-Day Impact of Vaginal Aging (DIVA) questionnaire: a multidimensional measure of the impact of vaginal symptoms on functioning and well-being in postmenopausal women, in a prospective, observational, feasibility study. 60 women were recruited to the study (20 premenopausal, asymptomatic women (control group) and 40 peri- and postmenopausal, symptomatic women). All women had a baseline assessment, using three different interventions, in addition to the DIVA questionnaire and symptomatic women were offered treatment, followed by a second assessment undertaken at 16weeks, using the same interventions. This paper focusses on the outcomes for the questionnaire and specifically on the paired data sets, before and after treatment. An improvement in the score for all four sections of DIVA (Activities of daily living, Emotions, Sexual Activity, and Feelings about yourself and your body (female embodiment)) was observed, following any treatment. Additional questions were added to DIVA, to assess patient preference in relation to the different diagnostic interventions. These included a speculum examination as part of the clinical assessment, a smear taken from the lateral vaginal wall to assess the vaginal maturation index, both undertaken by a clinician and a self-administered tampon to collect vaginal secretions, to determine the small molecule metabolite profile, using NMR spectroscopy, and to enable analysis of the vaginal microbiome. The medical standard tampon was the preferred intervention, before and after treatment, for women eligible for treatment. The VAN study demonstrates that DIVA, a previously tested questionnaire, is an easily accessible intervention, to assess the impact of urogenital symptoms on quality-of-life indicators in women in the United Kingdom with GSM and that women prefer to use a tampon themselves, rather than have a clinician performed vaginal speculum examination or a vaginal smear.

NMR-based metabolomics analysis reveals the effect of environmental contamination exposure on fishermen living around the Mundaú Lagoon in Maceió (Alagoas, Brazil)

The Mundaú lagoon in Maceió (Alagoas, Brazil) is a crucial resource for the local population, particularly fishing communities. Recent studies have revealed potential toxic metal contamination in the lagoon, particularly with mercury (Hg) levels exceeding the maximum regulated values. This inorganic contaminant may be impacting the health of fishermen and the local population. In this context, metabolomics, a study of small-molecule metabolites, can offer insights into the physiological impact of environmental contamination on humans. Thus, volunteers from the control and exposed groups were selected, considering the main exposure criteria primarily defined by their proximity and interaction with the lagoon. Blood and urine samples were collected from the volunteers and subjected to analysis using NMR spectroscopy. The data underwent Principal Component Analysis (PCA) and Orthogonal Partial Least-Squares Discriminant Analysis (OPLS-DA) based on metabolic patterns to establish group discrimination or identification. Metabolic pathways were assessed through enrichment analysis. The study revealed several metabolic disturbances in the exposed group's urine and plasma samples compared to control group. Noteworthy findings included arginine and proline metabolism disruptions, indicative of ammonia recycling and urea cycle impairment. These changes suggest compromised ammonia detoxification in the exposed group. Disturbances in the tricarboxylic acid (TCA) cycle and the transfer of acetyl groups into mitochondria suggested systemic metabolic stress in energy metabolism. Furthermore, elevated carnitine and ketone levels may indicate compensatory responses to low TCA cycle activity. Alterations in glutamate and glutathione metabolism and imbalances in glutathione levels indicate oxidative stress and impaired detoxification. This study highlights significant metabolic changes in fishermen exposed to contaminated environments, which can affect various metabolic pathways, including energy metabolism and antioxidant processes, potentially making individuals more vulnerable to the adverse effects of environmental contaminants. Finally, this work highlights insights into the relationship between environmental contamination and metabolic pathways, particularly in regions with limited studies.

Metabolomic biomarkers and altered phenylalanine metabolic pathway in preschool children with atopic dermatitis - A pilot study.

Background Atopic dermatitis (AD) has high prevalence in children. Current AD diagnosis and management focuses only on clinical phenotypes, but do not explore the endophenotypes, which are more important because they are a series of biomarkers linking clinical phenotype and genotype Aims Metabolomics can qualitatively and quantitatively capture real-time dynamic changes in a wide range of small molecule metabolites. This pilot study evaluated metabolomics biomarkers and altered metabolic pathways in preschool children with AD, aiming to explore the underlying molecular mechanisms and signalling pathways of the disease. Methods Blood samples of 23 preschool children with AD and 23 healthy children without AD or any other skin disease were collected. The untargeted metabolomic measurements were performed on a SCIEX-AD ultraperformance liquid chromatography system coupled with an AB SCIEX X500B QTOF system. Characteristics of small molecules in AD children were assessed and their associations with AD clinical index were evaluated. Altered metabolic pathways in AD children were also analysed using a comprehensive metabolomics platform. Results A total of 1,969 metabolites were identified, of which AD children exhibited 377 significantly altered metabolites. Multivariate statistical analysis demonstrated that the AD group and the control group could be clearly separated. Volcano plot analysis illustrated that 144 metabolites were up-regulated and 233 metabolites were down-regulated in AD children. The Severity Scoring of Atopic Dermatitis (SCORAD index) showed a moderate-to-strong association with estrogens, carotenes, leukotrienes, flavonols and keto acids in AD children (|r|=0.440-0.557). Several pathways, including the phenylalanine metabolism, were identified as altered in AD children. Limitations A small group of children was included in the study; the results need to be validated in larger sample sizes. Conclusion Results of this study illustrate potential alterations in metabolites and the phenylalanine metabolic pathway in preschool children with AD. Although this is a pilot study with a limited sample size, it may provide a new perspective for exploring the pathogenesis of AD, and for personalised treatment modalities.

Nuclear-Magnetic-Resonance-Spectroscopy-Derived Serum Biomarkers of Metabolic Vulnerability Are Associated with Disability and Neurodegeneration in Multiple Sclerosis.

Metabolic vulnerabilities can exacerbate inflammatory injury and inhibit repair in multiple sclerosis (MS). The purpose was to evaluate whether blood biomarkers of inflammatory and metabolic vulnerability are associated with MS disability and neurodegeneration. Proton nuclear magnetic resonance spectra were obtained from serum samples from 153 healthy controls, 187 relapsing-remitting, and 91 progressive MS patients. The spectra were analyzed to obtain concentrations of lipoprotein sub-classes, glycated acute-phase proteins, and small-molecule metabolites, including leucine, valine, isoleucine, alanine, and citrate. Composite indices for inflammatory vulnerability, metabolic malnutrition, and metabolic vulnerability were computed. MS disability was measured on the Expanded Disability Status Scale. MRI measures of lesions and whole-brain and tissue-specific volumes were acquired. Valine, leucine, isoleucine, alanine, the Inflammatory Vulnerability Index, the Metabolic Malnutrition Index, and the Metabolic Vulnerability Index differed between healthy control and MS groups in regression analyses adjusted for age, sex, and body mass index. The Expanded Disability Status Scale was associated with small HDL particle levels, inflammatory vulnerability, and metabolic vulnerability. Timed ambulation was associated with inflammatory vulnerability and metabolic vulnerability. Greater metabolic vulnerability and inflammatory vulnerability were associated with lower gray matter, deep gray matter volumes, and greater lateral ventricle volume. Serum-biomarker-derived indices of inflammatory and metabolic vulnerability are associated with disability and neurodegeneration in MS.