Liquid Chromatography-high Resolution Mass Spectrometry Research Articles

Relative quantitation of chiral thiol compounds labeled based on isotope novel mass spectrometry probes: Monitoring of the dynamic changes of chiral thiol compounds in human urine during normal, exercise, and rest recovery states

Monitoring changes in the content of chiral thiol compounds in the human body is crucial for the early diagnosis of oxidative stress-related diseases and the exploration of their pathogenesis. To address this, we synthesized a novel isotope mass spectrometry (MS) probe, denoted as (R)-(5-(3-isothiocyanato (13C) pyrrolidin-1-yl)-5-oxopentyl) triphenylphosphonium (N13CS-OTPP), with triphenylphosphine as its parent structure. In this study, we established a new ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLCHRMS) relative quantitative method to monitor chiral thiol compounds in human urine under varying oxidative stress conditions. This method relies on the ratio of 12C/13C isotope-labeled peak areas. To assess the chiral separation efficiency of N13CS-OTPP, we employed three types of thiol compounds (D/L-GSH, D/L-Cys, and D/L-Hcy) and observed separation degrees (Rs) ranging from 1.82 to 1.89. We further validated the accuracy and feasibility of our relative quantitative methods using D/L-Cys-as a model compound. N12C/13CS-OTPP-Cys-exhibited excellent linearity (R2 = 0.9993–0.9994) across different molar ratios (D/L-Cys = 10:1, 4:1, 2:1, 1:1, 1:2, 1:4, 1:10) and achieved a low limit of detection (LOD) of 2.5 fmol. Additionally, we monitored the dynamic changes in urine D/L-Cys-and D/L-Hcy ratios in 12 healthy volunteers (six males and six females) under various oxidative stress states. We generated fitting curves and investigated the trends in chiral thiol compounds in vivo. This study introduces a novel method for the relative quantitative monitoring of chiral thiol compounds in different oxidative stress states within the human body. It also presents a new strategy for understanding the pathogenesis of related diseases resulting from the abnormal metabolism of thiol compounds.

Phytochemical investigation of Nigrospora zimmermanii isolated from Poincianella pluviosa (Sibipiruna): metabolites characterisation and screening for anti-inflammatory activity

Endophytic fungi residing symbiotically in plant tissues are promising sources of bioactive natural products. This study explored the anti-inflammatory potential of an endophytic fungus isolated from the Brazilian medicinal plant Poincianella pluviosa (Sibipiruna). The extract from the endophyte FPD13 exhibited potential ex vivo anti-inflammatory effects by inhibiting prostaglandin E2 (PGE2) release by 75.22%. Phytochemical analysis using High-Performance Liquid Chromatography (HPLC), Nuclear Magnetic Resonance (NMR), and Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) enabled the isolation and identification of three compounds, including the macrolide Nigrosporolide, the phenyl-propanol Tyrosol, and the terpene Decarestrictine A. Morphological characteristics and Internal Transcribed Spacers region (ITS) sequencing classified fungus FPD13 as Nigrospora zimmermanii. The results reveal the anti-inflammatory potential and chemical diversity of P. pluviosa endophytes, warranting further investigation into the bioactivity and structure elucidation of their bioactive metabolites.

Elucidating the therapeutic mechanism of Hengqing II decoction in Alzheimer's disease using network pharmacology and molecular docking techniques

PurposeThe aim of our research was to investigate the mechanism of the Hengqing II decoction in treating Alzheimer's disease (AD) through network pharmacology and experimental validation methods. MethodsFirstly, the major chemical compounds of Hengqing II decoction were characterized by ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-Q-TOF-MS/MS), and the gene sets related to AD treatment by Hengqing II decoction were collected through the database of PubChem, Swiss TargetPrediction, and DisGeNET. Secondly, a multi-level molecular network of “Traditional Chinese medicine (TCM)-compound-target-disease” was constructed and visualized using the STRING platform and Cytoscape 3.9.1 software, and the enrichment analysis based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases was performed to predict the potential active compounds and targets of Hengqing II decoction for treating AD. Finally, molecular docking simulation was applied to investigate the binding interactions between potential active compounds and key targets, and the western blotting technique was employed to examine the expression levels of AKT1, TNF-α, and NOS2 proteins affected by active compounds. ResultsTotally 120 compounds in Hengqing II decoction were characterized by UHPLC-Q-TOF-MS/MS. Network pharmacology results showed that potential active compounds in Hengqing II decoction in treating AD included catalpol, gastrodin, and rehmannioside D, etc., and the main target proteins were TNF-α, NOS2, and AKT1. Further functional enrichment analysis revealed that Hengqing II decoction mainly exerted its therapeutic effects on AD by regulating lipid and atherosclerosis signaling pathways, AD signaling pathways, AKT1 signaling pathways, and PTGS2 signaling pathways. ConclusionHengqing II decoction exerted therapeutic effects on AD through multi-component, multi-target, and multi-pathway regulation, and its action mechanisms were related to oxidative stress, neuroinflammation, autophagy, and other pathways. Our research laid the data foundation for further exploration of action mechanism and clarification of clinical positioning and provided new ideas and clues in TCM formula research.

MetabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics.

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a "primary" feature list is used as a template for matching compounds in "target" feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution's in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

Enhanced Photo/Electrocatalytic Hydrogen Evolution by Hydrothermally Derived Cu-Doped TiO2 Solid Solution Nanostructures.

Highly efficient nanocatalysts with a high specific surface area were successfully synthesized by a cost-effective and environmentally friendly hydrothermal method. Structural and elemental purity, size, morphology, specific surface area, and band gap of pristine and 1 to 5% Cu-doped TiO2 nanoparticles were characterized by powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance (EPR), energy dispersive X-ray analysis (EDAX), inductively coupled plasma mass spectrometry (ICP-MS), liquid chromatography-high resolution mass spectrometry (LC-HRMS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), BET surface area, Raman spectroscopy, photoluminescence spectroscopy (PL) and UV-visible diffused reflectance spectroscopy (UV-DRS) studies. The XPS and EPR findings indicated the successful integration of Cu ions into the TiO2 lattice. UV-DRS and BET surface area investigations revealed that with an increase in dopant concentration, Cu-doped TiO2 NPs show a decrease in band gap (3.19-3.08 eV) and an increase in specific surface area (169.9-188.2 m2/g). Among all compositions, 2.5% Cu-doped TiO2 has shown significant H2 evolution with an apparent quantum yield of 17.67%. Furthermore, the electrochemical water-splitting study shows that 5% Cu-doped TiO2 NPs have superiority over pristine TiO2 for H2 evolution reaction. It was thus revealed that the band gap tuning with the desired dopant concentration led to enhanced photo/electrocatalytic sustainable energy applications.

A green-footprint approach for parallel multiclass analysis of contaminants in roasted coffee via LC-HRMS

The development and validation of a simple, comprehensive, and environment-friendly procedure to determine pesticide residues, naturally occurring and processing contaminants in roasted coffee is presented. A solid-liquid extraction of pesticides and mycotoxins with ethyl acetate and the concurrent partition of acrylamide to an aqueous phase follows a parallel analytical strategy that requires a single analytical portion to determine contaminants that are typically analyzed by dedicated single residue methods. The partition rules the lipids out of the aqueous extract before an “in-tube” dispersive solid phase microextraction (dSPME) for acrylamide retention. This is followed by the elution with buffer prior to injection. This extract is independently introduced into the system front end followed by the injection of the compounds from the organic phase, yet all spotted in the same run. A novel liquid chromatography high-resolution mass spectrometry (LC-HRMS) method setup enables the quantification of 186 compounds at 10 µg/kg, 226 at 5 µg/kg, and the acrylamide at 200 µg/kg for a total of 414 molecules, with acceptable recoveries (70–120%) and precision (RSD < 20%) making this strategy significantly faster and cost-effective than the dedicated single residue methods. Even though the presence of chlorpyrifos, acrylamide, and ochratoxin A was confirmed on samples of different origins, the findings were below the limit of quantification. During the storage of raw coffee, no proof of masking of OTA was found; however, condensation with glucose was evidenced during thermal processing experiments with sucrose by using stable isotope labeling (SIL). No detected conjugates were found in roasted nor in commercial sugar-added torrefacto samples, an industrial processing usually carried out above the decomposition temperature of the disaccharide.Graphical abstract

Phytotoxic Effects and Potential Allelochemicals from Water Extracts of Paulownia tomentosa Flower Litter

Flowers of Paulownia spp. wither and fall on a large scale after blooming in spring and have potential allelopathic effects on surrounding plants, including crops and weeds. In this study, the phytotoxic effects of water extracts of Paulownia tomentosa flower litter (EPF) on wheat (Triticum aestivum L.), lettuce (Lactuca sativa L.), green bristlegrass (Setaria viridis L.) and purslane (Portulaca oleracea L.) were evaluated in the laboratory. The mode of action of the phytotoxicity of EPF on lettuce seedlings was studied and the secondary metabolites in EPF were analyzed by liquid chromatography high-resolution mass spectrometry (LC-HRMS). The results show that EPF significantly inhibited the seed germination and seedling growth of four target plants in a concentration-dependent manner. In addition, EPF could induce the excessive accumulation of reactive oxygen species (ROS) flowing with oxidative damage of the lipid bilayer of the biofilm, resulting in reduced cell viability and even apoptosis in lettuce. There were 66 secondary metabolites identified by LC-HRMS in P. tomentosa flowers. Among them, 10 compounds, including salicylic acid, caffeic acid, parthenolide, 7-hydroxycoumarin and abscisic acid (ABA), were all known allelochemicals. In summary, P. tomentosa flower litter displayed significant allelopathic effects, which were related to the accumulation of ROS in target plants. Phenolic acids, flavonoids as well as ABA are probably the main allelochemicals of P. tomentosa flowers.

'Sorrento' and 'Tulare' Walnut Cultivars: Morphological Traits and Phytochemical Enhancement of Their Shell Waste.

Walnut processing generates considerable quantities of by-products that could be reprocessed into value-added products that have food and non-food applications. In this context, the aim of this study is to characterize the 'Sorrento' and 'Tulare' walnut cultivars using the UPOV guidelines and analyze the chemical composition and antioxidant activity of their shells. Insight into the chemical composition of the different granulometric fractions of walnut shell, obtained by sieving, was obtained following ultrasound-assisted extraction by Ultra-High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UHPLC-HRMS). The total phenolic, flavonoid, and tannin content and antiradical capacity, obtained by DPPH and ABTS assays, and the Fe(III) reducing power of the extracts were also evaluated. The UHPLC-HRMS analysis indicated the presence of thirty-two compounds ascribable to four major classes of specialized metabolites. Furthermore, the extraction efficiency of gallic acid, ellagic acid derivatives, as well as glansreginin A, increased with the decrease in shell matrix particle size in contrast to chlorogenic acids and flavonoid glycosides. This is the first study to highlight new knowledge on the chemical composition of walnut shells. The results obtained demonstrate the feasibility of recovering valuable bioactive components from agro-waste that may be further valorized.

Metabolic Stability and Metabolite Identification of N-Ethyl Pentedrone Using Rat, Mouse and Human Liver Microsomes.

New Psychoactive Substances (NPSs) are defined as a group of substances produced from molecular modifications of traditional drugs. These molecules represent a public health problem since information about their metabolites and toxicity is poorly understood. N-ethyl pentedrone (NEP) is an NPS that was identified in the illicit market for the first time in the mid-2010s, with four intoxication cases later described in the literature. This study aims to evaluate the metabolic stability of NEP as well as to identify its metabolites using three liver microsomes models. To investigate metabolic stability, NEP was incubated with rat (RLM), mouse (MLM) and human (HLM) liver microsomes and its concentration over time evaluated by liquid chromatography-mass spectrometry. For metabolite identification, the same procedure was employed, but the samples were analyzed by liquid chromatography-high resolution mass spectrometry. Different metabolism profiles were observed depending on the model employed and kinetic parameters were determined. The in vitro NEP elimination half-lives (t1/2) were 12.1, 187 and 770 min for the rat, mouse and human models, respectively. Additionally, in vitro intrinsic clearances (Cl int, in vitro) were 229 for rat, 14.8 for mouse, and 3.6 μL/min/mg in the human model, and in vivo intrinsic clearances (Cl int, in vivo) 128, 58.3, and 3.7 mL/min/kg, respectively. The HLM model had the lowest rate of metabolism when compared to RLM and MLM. Also, twelve NEP metabolites were identified from all models, but at different rates of production.

Characterization of Concanavalin A-based lectin sorbents for the extraction of the human chorionic gonadotropin glycoforms prior to analysis by nano liquid chromatography-high resolution mass spectrometry

Human chorionic gonadotropin (hCG) is constituted of the hCGα and hCGβ subunits and is a highly glycosylated protein. Affinity supports based on immobilized Concanavalin A (Con A) lectin were used in solid phase extraction (SPE) to fractionate the hCG glycoforms according to their glycosylation state. For the first time, the lectin SPE fractions were off-line analysed by a nano liquid chromatography - high-resolution mass spectrometry (nanoLC-HRMS) method keeping the glycoforms intact. For this, home-made Con A sorbents were prepared by immobilizing lectin on Sepharose with a mean grafting yield of 98.2% (relative standard deviation (RSD) of 3.5%, n = 15). A capacity of about 100 μg of purified urinary hCG (uhCG) per ml of sorbent, grafted with a density of 10 mg of Con A per ml, was estimated. Average extraction yields of around 60% for both hCGα and hCGβ glycoforms were obtained after optimization of the extraction protocol. Intra- and inter-assay evaluation led to average RSD values of around 10%, indicating a repeatable extraction procedure. Similar results were obtained with commercial Con A-based sorbents but only after their 3rd use or after an extensive pre-conditioning step. Finally, the Con A SPE led to the fractionation of some glycoforms of uhCG, allowing the detection of an hCGα glycoform with two tetra-antennary N-glycans that couldn’t be detected by direct analysis in nanoLC-HRMS without Con A SPE. Regarding a recombinant hCG, a fractionation was also observed leading to the detection of unretained hCGα glycoforms with tri-antennary N-glycans. Therefore, the combination of lectin SPE with intact protein analysis by nanoLC-HRMS can contribute to a more detailed glycosylation characterization of the hCG protein.

Effect of Essential Oil Components on the Activity of Steroidogenic Cytochrome P450.

Endocrine-disrupting chemicals (EDCs) may impact the development of prostate cancer (PCa) by altering the steroid metabolism. Although their exact mechanism of action in controlling tumor growth is not known, EDCs may inhibit steroidogenic enzymes such as CYP17A1 or CYP19A1 which are involved in the production of androgens or estrogens. High levels of circulating androgens are linked to PCa in men and Polycystic Ovary Syndrome (PCOS) in women. Essential oils or their metabolites, like lavender oil and tea tree oil, have been reported to act as potential EDCs and contribute towards sex steroid imbalance in cases of prepubertal gynecomastia in boys and premature thelarche in girls due to the exposure to lavender-based fragrances. We screened a range of EO components to determine their effects on CYP17A1 and CYP19A1. Computational docking was performed to predict the binding of essential oils with CYP17A1 and CYP19A1. Functional assays were performed using the radiolabeled substrates or Liquid Chromatography-High-Resolution Mass Spectrometry and cell viability assays were carried out in LNCaP cells. Many of the tested compounds bind close to the active site of CYP17A1, and (+)-Cedrol had the best binding with CYP17A1 and CYP19A1. Eucalyptol, Dihydro-β-Ionone, and (-)-α-pinene showed 20% to 40% inhibition of dehydroepiandrosterone production; and some compounds also effected CYP19A1. Extensive use of these essential oils in various beauty and hygiene products is common, but only limited knowledge about their potential detrimental side effects exists. Our results suggest that prolonged exposure to some of these essential oils may result in steroid imbalances. On the other hand, due to their effect on lowering androgen output and ability to bind at the active site of steroidogenic cytochrome P450s, these compounds may provide design ideas for novel compounds against hyperandrogenic disorders such as PCa and PCOS.

Intelligent chemical profiling of 73 edible flowers by liquid chromatography-high resolution mass spectrometry combined with HRMS database and their authentication based on large-scale fingerprints

A commercial high-resolution MS database “TCM-PCDL” was innovatively introduced to automatically identify multi-components in 73 edible flowers rapidly and accurately by liquid chromatography-high resolution mass spectrometry, which can be time-consuming and labor-intensive in traditional manual method. The database encompasses over 2565 natural products with various energy levels. Unknown compounds can be identified through direct matching and scoring MS2 spectra with database. A total of 870 compounds were identified from 73 flowers, with polyphenols constituting up to 75%. Focusing on polyphenols, a high performance liquid chromatography (HPLC) method was developed to generate fingerprints from 510 batches, establishing an “HPLC database” that enabled accurate authentication using similarity scores and rankings. This method demonstrated an accuracy rate of 100% when applied to 30 unknown samples. For flowers prone to confusion, additional statistical analysis methods could be employed as aids in authentication. This study provides valuable insights for large-scale sample chemical profiling and authentication.

Free Fatty Acid Determination in Broccoli Tissues Using Liquid Chromatography-High-Resolution Mass Spectrometry.

Broccoli (Brassica oleracea L. var. italica Plenck) is a widely consumed vegetable, very popular due to its various nutritional and bioactive components. Since studies on the lipid components of broccoli have been limited so far, the aim of the present work was the study of free fatty acids (FFAs) present in different broccoli parts, aerial and underground. The direct determination of twenty-four FFAs in broccoli tissues (roots, leaves, and florets) was carried out, using a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method in a 10 min single run. Linolenic acid was found to be the most abundant FFA in all different broccoli parts in quantities ranging from 0.76 to 1.46 mg/g, followed by palmitic acid (0.17-0.22 mg/g) and linoleic acid (0.06-0.08 mg/g). To extend our knowledge on broccoli's bioactive components, for the first time, the existence of bioactive oxidized fatty acids, namely hydroxy and oxo fatty acids, was explored in broccoli tissues adopting an HRMS-based lipidomics approach. 16- and 2-hydroxypalmitic acids were detected in all parts of broccoli studied, while ricinoleic acid was detected for the first time as a component of broccoli.

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer.

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

In vitro, invivo metabolism and quantification of the novel synthetic opioid N-piperidinyl etonitazene (etonitazepipne).

N-piperidinyl etonitazene (etonitazepipne) is a newly synthesized opioid related to the 2-benzylbenzimidazole analog class. Etonitazepipne has been formally notified and placed under intensive monitoring in Europe in January 2022. Nitazenes have high affinity at µ-opioid receptor (MOR). Etonitazepipne, specifically shows a EC50 of 2.49 nM, suggesting about 50 times higher potency combined with higher efficacy compared to morphine. Antinociceptive potency l ('hot plate test' with rats) was 192-fold greater than that of morphine. Here we report on a post-mortem case involving etonitazepipne and its quantification using a standard addition method (SAM) through liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, characterization and identification of phase I human metabolites using invitro assay based on pooled human liver microsomes (pHLM) was performed along with the analysis of authentic urine samples by means of high-performance liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). The concentration of etonitazepipne in post-mortem blood and urine was 8.3 and 11 ng/mL, respectively. SAM was validated by assessing the following parameters: intraday and interday repeatability, matrix effect and recovery rate in post-mortem blood. A total of 20 and 14 metabolites were identified after pHLM incubation and urine analysis, respectively. Most pronounced invitro and invivo transformations were O-deethylation, hydroxylation, ketone reduction, and combinations thereof. Considering small traces of the parent drug often found in real cases, the identification of metabolic biomarkers is crucial to identify exposure to this drug. O-deethylated, oxidated metabolites, and combination thereof are proposed as urinary biomarkers along with the parent compound.

PolyMatch: Novel Libraries, Algorithms, and Visualizations for Discovering Polymers and Chemical Series.

Polymers are integral components of everyday products, ranging from plastics and emulsifiers to lubricants and detergents. Characterization of these materials at the molecular level is essential to understanding their physicochemical properties and potential health impacts, considering factors such as the number of repeating units, chemical moieties, functional groups, and degree of unsaturation. This study introduces a free open-source vendor neutral software, PolyMatch, designed to annotate polysorbates, polysorbides, polyethylene glycols (PEGs), fatty acid esterified species, and related chemical species based on mass spectral and chromatographic patterns inherent in the repeating nature of chemical moieties. PolyMatch facilitates the generation of MS/MS libraries for polymeric chemical species characterization (with over 800 000 structures with associated fragment masses already built in) and covers the entire liquid chromatography-high-resolution mass spectrometry (LC-HRMS/MS) data-processing workflow. PolyMatch covers peak picking, blank filtering, annotation, data visualization, and sharing of interactive data sets via an HTML link to the community. The software was applied to a Tween 80 mixture, using LC-HRMS/MS on an Agilent 6546 Q-TOF instrument with iterative exclusion for comprehensive fragmentation coverage. PolyMatch automatically assigned 86 features with high confidence at the species level, 362 based on PEG containing fragments and accurate mass matching to a simulated polymer database, and over 10 000 based on being a member of a homologous series (three or more) with CH2CH2O repeating units. The ease of use of PolyMatch and comprehensive coverage with species level assignment is expected to contribute to the advancement of materials science, health research, and product development.

Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

Phytochemical analyses by LC-HRMS, FTIR spectral analysis, antioxidant, antidiabetic and antityrosinase activity of Crataegus orientalis Pall. ex M. Bieb fruit extracted with various solvents.

Crataegus orientalis Pall. ex M. Bieb fruit (COPMB) is extensively used as a source of various products in the medicinal-aromatic field and holds the potential for erosion control, ornamental purposes, food source, and economic benefits for forest villagers from its fruits. This study aims to determine the chemical components and biological activities of extracts prepared from COPMB using different solvents. The present work was designed to define the antioxidant activity [phosphomolybdenum (total antioxidant capacity), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), ferric reducing antioxidant power (FRAP), cupric ion-reducing antioxidant capacity (CUPRAC) and metal chelating activity (MCA)], phytochemical screening analysis, enzyme inhibitor (α-amylase, α-glucosidase and tyrosinase) potential, and liquid chromatography-high resolution mass spectrometry (LC-HRMS) secondary metabolite profiling in different extracts of COPMB. The results of LC-HRMS revealed that fumaric acid was the main phenolic compound in all extracts. Among the extracts, ethyl acetate extract has the highest phytochemical and antioxidant properties [total phenolic content (TPC): 32.5 mg GAE/g, total flavonoid content (TFC): 12.2 mg QE/g, ABTS: 213.0 mg TE/g; CUPRAC: 126.0 mg TE/g, MCA: 145.0 mg EDTA/g; FRAP: 122.8 mg TE/g; TAC: 2.8 mmol TE/g]. Ethyl acetate and methanol extracts are more effective in α-amylase (0.27 ± 0.01 mg/mL; 0.12 ± 0.00 mg/mL), α-glucosidase (0.63 ± 0.02 mg/mL; 0.77 ± 0.02 mg/mL) and tyrosinase (0.03 ± 0.00 mg/mL; 0.03 ± 0.00 mg/mL) enzyme inhibition potentials compared to standard acarbose (0.75 ± 0.02 mg/mL for α-amylase; 1.11 ± 0.03 mg/mL for α-glucosidase) and kojic acid (0.04 ± 0.00 mg/mL). The findings from this study suggest that COPMB could serve as a valuable source of natural agents for the food and pharmaceutical industry. © 2024 Society of Chemical Industry.

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning

IntroductionPsoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.ObjectivesTo identify metabolites capable of classifying patients with PsA according to their disease activity.MethodsAn in-house solid-phase microextraction (SPME)—liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.ResultsThe best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.ConclusionSeveral lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

P104 Per- and poly-fluoroalkyl substances (PFAS) exposure in early life is associated with intestinal inflammation

Abstract Background Early life environmental exposures are linked with intestinal inflammation and inflammatory bowel disease (IBD) later in life. Per- and poly-fluoroalkyl substances (PFAS) are a large class of fluorinated organic chemicals used widely in consumer products that may be risk factors for IBD; however, the association between exposure to PFAS in early life and intestinal inflammation has not yet been studied. Dried blood spots (DBS) are archived neonatal capillary blood samples collected and stored as part of the New York State neonatal screening program and a cost-effective early life environmental exposure screening resource. Methods We measured 135 PFAS in DBS collected at birth from offsprings of women with and without IBD [n=37 (44%) and 47 (56%), respectively] enrolled in the MEChanisms Of disease traNsmission In Utero through the Microbiome (MECONIUM) cohort between January 2015 and November 2020, using untargeted metabolomics with liquid chromatography high-resolution mass spectrometry. In a subsample (n = 46), we also measured offspring fecal calprotectin (FC) at one year. We fitted exposome-wide regression models to estimate the association between each PFAS signal in the DBS and continuous FC at one year of age. For the significant associations (nominal p-value &amp;lt;0.05), we further explored potential effect modification by stratifying by maternal IBD status. All models were adjusted for relevant confounders. Results The mean (SE) of FC at age one year was 213.9 (23.8) ug/gm. The PFAS chemicals perfluoroundecanoic acid (PFUnDA) and N-ethyl-perfluorooctane sulfonamido acetic acid (N-Et-FOSAA) were significantly associated with increased scaled and log-transformed FC per decile increase in exposures [estimate (95% CI) = 0.52 (0.13,0.91) and 0.34 (0.05,0.63), Figure A]. Associations tended to be stronger in offspring of women with IBD relative to offspring of women without IBD (Figure B). estimate (95% CI) for the associations between PFUnDA and FC were 0.86 (0.34,1.39) and 0.12 (-0.47,0.71), respectively, and between N-Et-FOSAA and FC, these were 0.54 (-0.01,1.08) and 0.31(-0.07,0.68), respectively. Conclusion DBS can be used to measure early life exposure to toxins, and prenatal PFAS exposure is associated with elevated FC, with a slightly stronger effect in the offspring of women with IBD. Larger prospective studies are needed to validate these associations and understand potential underlying mechanisms through which early life PFAS exposures may contribute to IBD etiology.