Liquid Chromatography-high Resolution Mass Spectrometry Research Articles

Fagopyrin F fraction from Fagopyrum tataricum demonstrates photodynamic inactivation of skin infecting bacterium and squamous cell carcinoma (A431) cells.

Photodynamic therapy (PDT) stands out as a noteworthy development as an alternative targeted treatment against skin ailments. While PDT has advanced significantly, research into photo-activatable "Green drugs" derived from plants which are less toxic than the synthetic drugs has not kept pace. This study investigates the potential of Fagopyrin F Containing Fraction (FCF) derived from Fagopyrum tataricum in mediating PDT against Staphylococcus aureus and skin cancer cells (A431). FCF was isolated from the plant extract using thin-layer chromatography, followed by identification of the compound through high-performance liquid chromatography and high-resolution liquid chromatography-mass spectrometry. FCF was tested to determine its antibacterial and anticancer efficacy. Results revealed that FCF-mediated PDT exhibited potent action against S. aureus, significantly reducing bacterial viability (MIC 19.5 μg/100 μL). Moreover, FCF-mediated PDT showed good efficacy against A431 cells, resulting in a notable reduction in cell viability (IC50 29.08μg/mL). Given the known association between S. aureus and squamous cell carcinoma (SCC), FCF shows the potential to effectively target and eradicate both SCC and the related S. aureus present within the lesions. In silico study reveals that Fagopyrin F effectively binds with the epidermal growth factor (EGFR), one among the highly expressed proteins in the A431 cells, with a binding energy of -9.6kcal/mol. The affinity of Fagopyrin F for EGFR on A431 cancer cells along with its cytotoxicity against skin cancer cells while safeguarding the normal cells (L929) plays a major part in the way it targets cancer cells. However, its safety, efficacy, and long-term advantages in treating skin conditions require more investigation, including in vivo investigations and clinical trials.

Comparative metabolite analysis of Piper sarmentosum organs approached by LC–MS-based metabolic profiling

Piper sarmentosum Roxb. (Piperaceae) is a traditional medicinal and food plant widely distributed in the tropical and subtropical regions of Asia, offering both health and culinary benefits. In this study the secondary metabolites in different organs of P. sarmentosum were identified and their relative abundances were characterized. The metabolic profiles of leaves, roots, stems and fruits were comprehensively investigated by liquid chromatography high-resolution mass spectrometry (LC-HR-MS) and the data subsequently analyzed using multivariate statistical methods. Manual interpretation of the tandem mass spectrometric (MS/MS) fragmentation patterns revealed the presence of 154 tentatively identified metabolites, mostly represented by alkaloids and flavonoids. Principle component analysis and hierarchical clustering indicated the predominant occurrence of flavonoids, lignans and phenyl propanoids in leaves, aporphines in stems, piperamides in fruits and lignan-amides in roots. Overall, this study provides extensive data on the metabolite composition of P. sarmentosum, supplying useful information for bioactive compounds discovery and patterns of their preferential biosynthesis or storage in specific organs. This can be used to optimize production and harvesting as well as to maximize the plant’s economic value as herbal medicine or in food applications.Graphical

In Vivo and In Vitro Metabolic Fate and Urinary Detectability of Five Deschloroketamine Derivatives Studied by Means of Hyphenated Mass Spectrometry

Ketamine derivatives such as deschloroketamine and deschloro-N-ethyl-ketamine show dissociative and psychoactive properties and their abuse as new psychoactive substances (NPSs) has been reported. Though some information is available on the biotransformation of dissociative NPSs, data on deschloro-N-cyclopropyl-ketamine deschloro-N-isopropyl-ketamine and deschloro-N-propyl-ketamine concerning their biotransformation and, thus, urinary detectability are not available. The aims of the presented work were to study the in vivo phase I and II metabolism; in vitro phase I metabolism, using pooled human liver microsomes (pHLMs); and detectability, within a standard urine screening approach (SUSA), of five deschloroketamine derivatives. Metabolism studies were conducted by collecting urine samples from male Wistar rats over a period of 24 h after their administration at 2 mg/kg body weight. The samples were analyzed using liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) and gas chromatography–mass spectrometry (GC-MS). The compounds were mainly metabolized by N-dealkylation, hydroxylation, multiple oxidations, and combinations of these metabolic reactions, as well as glucuronidation and N-acetylation. In total, 29 phase I and 10 phase II metabolites were detected. For the LC-HRMS/MS SUSA, compound-specific metabolites were identified, and suitable screening targets could be recommended and confirmed in pHLMs for all derivatives except for deschloro-N-cyclopropyl-ketamine. Using the GC-MS-based SUSA approach, only non-specific acetylated N-dealkylation metabolites could be detected.

Prevalence of Psychoactive Substance Use During Pregnancy in Argentine Women: A Pilot Study Testing Maternal Hair

Background: The use of psychoactive substances (PSs) during pregnancy is a major public health concern because of their increasing prevalence worldwide. This study examined the understudied issue of gestational PS consumption in a cohort of Argentine delivering mothers. Methods: A cross-sectional pilot study involving 51 women receiving delivery care was conducted at the Santa Rosa Hospital in La Pampa, Argentina. Information on maternal sociodemographic characteristics, pregnancy history, and drug use was obtained through standardized interviews. Maternal hair samples were analyzed for alcohol, tobacco, licit, illicit, and prescription substance biomarkers using ultra-high-performance liquid chromatography high-resolution mass spectrometry and gas chromatography mass spectrometry. Results: During pregnancy, 49.0% of participants reported alcohol consumption, 25.5% reported tobacco use, and 23.5% reported cannabis use. Hair samples from 56.9% of the women were positive for illicit PSs, with the most frequent being cocaine (41.2%) and cannabis (15.7%). Among the women, 47.1% consumed alcohol during pregnancy. Of the 24 women with hair ethyl glucuronide ≥5 pg/mg, 33.3% drank until the end of gestation and 58.3% started a social drinking habit in the second half. The analysis also detected prescription substances (anticonvulsants, antidepressants, methadone, opioids, antihistamines, antiemetics, and analgesics), caffeine (70.6%), lidocaine, and levamisole, some of which were cocaine or opioid adulterants. Conclusions: This is the first study to objectively assess the consumption of licit and illicit PSs during pregnancy in Argentina. In contrast to most nearby countries, cocaine was the most detected illicit PS in this cohort of Argentine delivering women. This finding highlights the importance of regular monitoring of local trends in PS use during pregnancy.

Enzyme-Driven LC-HRMS Approach for Specific Recognition of 12α-Hydroxy Bile Acids.

The synthesis of 12α-hydroxylated bile acids (12HBAs) and non-12α-hydroxylated bile acids (non-12HBAs) occurs via classical and alternative pathways, respectively. The composition of these BAs is a crucial index for pathophysiologic assessment. However, accurately differentiating 12HBAs and non-12HBAs is highly challenging due to the limited standard substances. Here, we innovatively introduce 12α-hydroxysteroid dehydrogenase (12α-HSDH) as an enzymatic probe synthesized by heterologous expression in Escherichia coli, which can specifically and efficiently convert 12HBAs in vitro under mild conditions. Coupled to the conversion rate determined by liquid chromatography-high resolution mass spectrometry (LC-HRMS), this enzymatic probe allows for the straightforward distinguishing of 210 12HBAs and 312 non-12HBAs from complex biological matrices, resulting in a BAs profile with a well-defined hydroxyl feature at the C12 site. Notably, this enzyme-driven LC-HRMS approach can be extended to any molecule with explicit knowledge of enzymatic transformation. We demonstrate the practicality of this BAs profile in terms of both revealing cross-species BAs heterogeneity and monitoring the alterations of 12HBAs and non-12HBAs under asthma disease. We envisage that this work will provide a novel pattern to recognize the shift of BA metabolism from classical to alternative synthesis pathways in different pathophysiological states, thereby offering valuable insights into the management of related diseases.

Plasma lipidome differences in patients with and without significant carotid plaque

BackgroundAtherosclerosis is a major cause of ischemic stroke, and early detection of advanced atherosclerosis in the carotid artery is important for reducing morbidity and mortality. What is even more important is not only detection of atherosclerosis but early determination whether the patients are at high risk of an event with adverse effects as the size of the plaque does not necessarily reflect its potential to trigger such events. AimWe studied whether plasma lipidomics profile can be used as a diagnostic tool for stratification of stable or unstable plaques without the need of removing the carotid plaque. MethodsThis study used liquid chromatography high-resolution tandem mass spectrometry lipidomics to characterize lipid profiles in patients' plasma and found that patients with significant and complicated (vulnerable) atherosclerotic plaque had distinct lipid profiles compared to those with insignificant plaques. ResultsThe lipid classes that were most predictive of vulnerable plaque were lysophosphoethanolamines, fatty acyl esters of hydroxy fatty acids, free fatty acids, plasmalogens, and triacylglycerols. Most of these compounds were found decreased in plasma of patients with unstable plaques which enabled sufficient performance of a statistical model used for patient stratification. ConclusionsPlasma lipidomes measured by liquid chromatography-mass spectrometry show differences in patients with stable and unstable carotid plaques, therefore these compounds could potentially be used as biomarkers for unstable plaque in future clinical diagnosis.

Abstract PO4-07-02: Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature

Abstract Background: Mammography is the current diagnostic standard for breast cancer screening and monitoring. However, accessibility challenges, accuracy issues and patient discomfort all contribute to reduced patient compliance and utilization, resulting in a need for more effective diagnostic tools. An artificial intelligence (AI)-based lipidomic blood test may add significant value to early breast cancer detection rate and improve outcomes for patients. We have previously reported a series of lipidomic studies (n=793) and derived a lipid signature from plasma-enriched extracellular vesicles (EVs) that effectively distinguished people with localized breast cancer from cancer-free controls. Here we report the development of a breast cancer detection AI model from lipidomic data assessed directly using plasma samples. Methods: Lipids in both EVs and plasma collected from fasted breast cancer and control blood samples (n=256) were extracted and analysed by liquid chromatography-high resolution mass spectrometry (LC-HRAM-MS). Over 400 manually curated lipids were quantified. A bootstrapped analysis using Boruta, a robust and statistically rigorous feature selection algorithm based on random forest feature importance, was employed to identify cancer discriminatory lipid signatures in EV and plasma lipidomes consistently selected across 2000 bootstrap samples. The resulting lipid signature was then used to train an ensemble of 18 distinct machine learning models for cancer status prediction using a majority vote to aggregate the individual predictions. Model performance and variability were assessed over 2000 iterations of leave-group-out cross-validation (LGOCV) using an 80/20 train-test split. Average patient-level predictions across LGOCV iterations were recorded for both EV-and plasma-derived models and the two modalities were compared using an exact paired samples test (McNemar’s test). Results: Both the EV- and plasma-derived lipid signatures performed well in distinguishing breast cancer samples from controls. The development of a bioinformatics AI pipeline enabled the creation of a robust ensemble model achieving an F1 score of 0.89 in plasma with LGOCV. The final plasma ensemble predictive performance of 86.1% (±4.5%) in accuracy, 91.4% (±5.4%) in sensitivity, and 78.7% (±8.6%) specificity was achieved, which is comparable to that of EV (accuracy: 86.1±4.4%, sensitivity: 90.4±5.3%, specificity: 80.2±8.7%). Paired samples analysis using McNemar’s test indicated no significant differences between models trained on EV- and plasma-derived lipid signatures in either the sensitivity (p=0.65), specificity (p=0.49), or accuracy (p=0.42). Conclusion: The initial study demonstrated the high performance of a plasma-enriched extracellular vesicle-derived lipid biomarker signature for early breast cancer detection. Direct assessment of the lipidomic signature from plasma showed promise in simplifying the test. Assessing plasma directly offered advantages in terms of scalability, higher throughput, and ease of implementation. Further verification of the lipid signature in an upcoming study involving 500 plasma samples is planned. Ongoing studies will further optimize the plasma lipidomic signature and strengthen our AI pipeline. These findings support the potential clinical application of AI-based lipidomic profiling as a blood-based screening tool for breast cancer detection. Citation Format: Ameline Lim, Cheka Kehelpannala, Fatemeh Vafaee, Forrest Koch, Dana Pascovici, Desmond Li, Kerry Heffernan, Gillian Lamoury, Amani Batarseh, Bruce Mann. Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-07-02.

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat.

The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

Dynamic protein composition of Saccharomyces cerevisiae ribosomes in response to multiple stress conditions reflects alterations in translation activity

Ribosomes, intercellular macromolecules responsible for translation in the cell, are composed of RNAs and proteins. While rRNA makes the scaffold of the ribosome and directs the catalytic steps of protein synthesis, ribosomal proteins play a role in the assembly of the subunits and are essential for the proper structure and function of the ribosome. To date researchers identified heterogeneous ribosomes in different developmental and growth stages. We hypothesized that under stress conditions the heterogeneity of the ribosomes may provide means to prepare the cells for quick recovery. Therefore the aim of the study was the identification of heterogeneity of ribosomal proteins within the ribosomes in response to eleven stress conditions in Saccharomyces cerevisiae, by means of a liquid chromatography/high resolution mass spectrometry (LC-HRMS) and translation activity tests. Out of the total of 74 distinct ribosomal proteins identified in the study 14 small ribosomal subunit (RPS) and 8 large ribosomal subunit (RPL) proteins displayed statistically significant differential abundances within the ribosomes under stress. Additionally, significant alterations in the ratios of 7 ribosomal paralog proteins were observed. Accordingly, the translational activity of yeast ribosomes was altered after UV exposure, during sugar starvation, cold shock, high salt, anaerobic conditions, and amino acid starvation.

Identification of major degradation products of Clorsulon drug substance including its degradation pathways by high resolution mass spectrometry and NMR

Clorsulon is an effective anthelmintic drug substance extensively used in the treatment of parasitic infestations in both cattle and sheep. An in-depth investigation of Clorsulon’s degradation products (DPs) was carried out through forced degradation study to comprehend its degradation path. A total of eight degradation products were separated under various stress degradation conditions. Structural elucidation of these DPs was conducted using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS), and their fragmentation patterns were compared to that of the parent compound. Adequate amount of DP-4 was isolated and purified by semi-preparative high-performance liquid chromatography (HPLC) methods. Subsequently, it was examined in detail using both 1D and 2D NMR (nuclear magnetic resonance spectroscopy). Most probable mechanistic pathways for the formation of degradation products under various stress degradation conditions were proposed to better understand the degradation profile. Based on the results of the stress study, Clorsulon drug substance was found to be unstable under photolytic and oxidative conditions. Understanding Clorsulon's degradation pathway is essential for determining shelf-life prediction of finished product, safety and efficacy assurance, and guiding the development of stable, high-quality formulations.

Metabolite profiling of chemically modified oligonucleotides in rat liver homogenates using hydrophilic interaction liquid chromatography-high resolution mass spectrometry

Metabolite profiling of chemically modified oligonucleotides in rat liver homogenates using hydrophilic interaction liquid chromatography-high resolution mass spectrometry

Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei.

Trypanosoma brucei (Tb) is the causative agent of human African trypanosomiasis (HAT), also known as sleeping sickness, which can be fatal if left untreated. An understanding of the parasite's cellular metabolism is vital for the discovery of new antitrypanosomal drugs and for disease eradication. Metabolomics can be used to analyze numerous metabolic pathways described as essential to Tb. brucei but has some limitations linked to the metabolites' physicochemical properties and the extraction process. To develop an optimized method for extracting and analyzing Tb. brucei metabolites, we tested the three most commonly used extraction methods, analyzed the extracts by hydrophilic interaction liquid chromatography high-resolution mass spectrometry (HILIC LC-HRMS), and further evaluated the results using quantitative criteria including the number, intensity, reproducibility, and variability of features, as well as qualitative criteria such as the specific coverage of relevant metabolites. Here, we present the resulting protocols for untargeted metabolomic analysis of Tb. brucei using (HILIC LC-HRMS). © 2024 Wiley Periodicals LLC. Basic Protocol 1: Culture of Trypanosoma brucei brucei parasites Basic Protocol 2: Preparation of samples for metabolomic analysis of Trypanosoma brucei brucei Basic Protocol 3: LC-HRMS-based metabolomic data analysis of Trypanosoma brucei brucei.

Revealing mechanism of phenolic-amine reaction to form humus in compost based on high-resolution liquid chromatography mass spectrometry and spectroscopy

Revealing mechanism of phenolic-amine reaction to form humus in compost based on high-resolution liquid chromatography mass spectrometry and spectroscopy

The effect of extraction method on biological activity and phytochemical content of Artocarpus heterophyllus (jackfruit) leaves extract concurrent with its principal component analysis

Artocapus heterophyllus (jackfruit) is available in abundance in tropical regions. The present study explored the effect of different extraction method i.e. maceration, ultrasonication and both of ultrasonication and maceration on its biological activity (antioxidant, antidiabetes and antibacterial activities) and phytochemical content of Artocarpus heterophyllus (jackfruit) leaves extract. Jackfruit leaves were extracted using ethanol as solvent. The capability of jackfruit leaves extract to scavenge radicals was evaluated using a DPPH (2,2-diphenyl-1-picryl-hydrazyl) assay, β-carotene bleaching assay and reducing power assay. The total phenolic content (TPC) was assessed using the Folin- Ciocalteau method. Its antibacterial activity was assessed using the disc diffusion and microdilution method against Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Salmonella typhimurim and Escherichia coli. The α-glucosidase inhibitor assay was conducted using α-glucosidase from Saccharomyces cerevisiae. The results revealed that ulrasonication method give the highest antioxidant activity in three metode used, i.e. DPPH assay with IC50 of 42.51 µg/mL, β-carotene bleaching assay of 57.64%, reducing power assay of 919 mg GAE/g. Meanwhile, for α-glucosidase inhibitory assay, ultrasonication method also had the highest value of 83.44% at concentration of 1000 µg/mL. Furthermore, antibacterial assay using disk diffusion method showed ultrasonication had the highest inhibition zone of 7.81 mm at 5 mg/mL against P. aeruginosa, while maceration method had the highest inhibition zone of 8.02 mm at 5 mg/mL against E. coli. These results in accordance with total phenolic content (TPC) of ultrasonication extract which was the highest of 125.06 mg GAE/g. The liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis suggested that several bioactive compounds such as phenolic, flavonoid and its derivatives was present in the jackfruit leaves extract. Further analysis using principal component analysis (PCA) revealed that the extraction process affected the metabolite composition of the samples which was confirmed by significant separation of the score plots of extraction methods. The present study revealed that jackfruit leaves is a potent source of natural antibacterial, antioxidants and antidiabetic medicines in functional foods and pharmaceutical industries.

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography—high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5′-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.

Impact of four different extraction methods and three different reconstitution solvents on the untargeted metabolomics analysis of human and rat urine samples

Unsuitable sample preparation may result in loss of important analytes and consequently affect the outcome of untargeted metabolomics. Due to species differences, different sample preparations may be required within the same biological matrix.The study aimed to compare the in-house sample preparation method for urine with methods from literature and to investigate the transferability of sample preparation from human urine to rat urine. A total of 12 different conditions for protein precipitation were tested, combining four different extraction solvents and three different reconstitution solvents using an untargeted liquid-chromatography high resolution mass spectrometry (LC-HRMS) metabolomics analysis. Evaluation was done based on the impact on feature count, their detectability, as well as the reproducibility of selected compounds.Results showed that a combination of methanol as extraction and acetonitrile/water (75/25) as reconstitution solvent provided improved results at least regarding the total feature count. Additionally, it was found that a higher amount of methanol was most suitable for extraction of rat urine among the tested conditions. In comparison, human urine requires significantly less volume of extraction solvent.Overall, it is recommended to systematically optimize both, the extraction method, and the reconstitution solvent for the used biofluid and the individual analytical settings.

A Proof-of-Concept Study to Develop a Peptide-Based Vaccine against Salmon Lice Infestation in Atlantic Salmon (Salmo salar L.)

Proteins present in blood samples from Atlantic salmon (Salmo salar) infected with salmon lice (Lepeophtheirus salmonis) were analyzed using liquid chromatography–high-resolution mass spectrometry. Bioinformatic analyses revealed 1820 proteins, of which 58 were assigned to lice. Among these, peroxiredoxin-2, an antioxidant protein, was found relevant with respect to blood feeding of the parasite. The three-dimensional structure analysis of the protein revealed a surface amino acid sequence of interest. A 13-amino-acid peptide was selected as a potential antigen due to its predicted solubility, antigenicity, probable non-allergenic, and non-toxic nature. This peroxiredoxin-2-derived peptide was synthesized, combined with a commercially available adjuvant, and used for vaccination. The test vaccine demonstrated a 60–70% protection rate against early-stage Lepeophtheirus salmonis infection in a challenge trial in Norway. Additionally, the vaccine was tested against salmon lice (Caligus rogercresseyi) in Chile, where a remarkable 92% reduction in the number of adult lice was observed. Thus, in combination with the selected adjuvant, the peptide showed antigenic potential, making it a suitable candidate for future vaccine development. The approach described holds promise for the development of peptide vaccines against various ectoparasites feeding on blood or skin secretions of their hosts.

Improved analysis of grape seed extract by liquid chromatography–high resolution mass spectrometry (LC-HRMS) reveals that proanthocyanidin-protein interaction mechanisms in cream depend on degree of polymerization

This study aimed to comprehensively characterize chemical profiles of proanthocyanidins (PACs) from grape seed extract (GSE), examine their interactions with proteins in a cream system, and define the mechanisms mediating PAC-protein interactions. GSE PACs were fractionated and characterized by thiolysis followed by liquid chromatography–high resolution mass spectrometry (LC-HRMS) analysis. New PACs with a degree of polymerization (DP) up to 16 were identified by improved HRMS data processing methods. In the model cream system, high-DP PACs exhibited greater precipitation capacity and protein binding than low-DP PACs. Low-DP PACs primarily engaged in hydrogen bonding, while high-DP PACs predominantly utilized multiple hydrophobic interaction sites to form cream protein aggregates. Furthermore, particle size and viscosity measurement of cream revealed a progressively DP-dependent increase in aggregated fat globules and cream viscosity. These findings enhanced our understanding of PACs’ structural intricacies and highlighted their functional role as PAC-rich natural ingredients in creating structured cream systems.

Deciphering the chemical constituents of Phlomis monocephala extracts using UHPLC-HRMS and their antioxidant, neuroprotective, antidiabetic and toxic potentials

In the current study, five different extracts (n-hexane, ethyl acetate, dichloromethane, ethanol, and water) of Phlomis monocephala were analyzed for the first time by ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) to identify their phenolic compounds. The extracts were also evaluated for their non-enzyme antioxidant activities using a variety of methods, including DPPH and, ABTS•+ scavenging activities, reduction of ferric (Fe3+), and cupric ions (Cu2+), metal chelating (MCA) activities, and phosphomolybdenum (PBD). Additionally, the extracts were assessed for their in vitro enzyme inhibition potential (acetylcholinesterase (AChE)/butyrylcholinesterase (BChE), α-amylase, α-glucosidase, and tyrosinase). Furthermore, cell viability was evaluated on HepG2 (human hepatocellular carcinoma), S17 cells (murine bone marrow stromal) and RAW (murine macrophages). UHPLC-HRMS allowed for the identification of 115 compounds from different chemical groups including flavonoids, iridoid glycosides, phenylethanoid glycosides and others. Most of the extracts had strong antioxidant potential and were rich in phenolic compounds. Ethanol and water extracts appear as the most promising antioxidant extracts providing the highest values followed by ethyl acetate by all the methodologies employed in this study. Furthermore, all the extracts, except the aqueous extract, inhibited all the enzymes significantly. Surprisingly, the aqueous extract did not show a prominent inhibition (low or no inhibition) against these enzymes. Hexane, ethyl acetate, and dichloromethane exhibited extremely significant cytotoxic effects against all cell lines at a higher concentration. The HepG2 cells demonstrated lower sensitivity to the extracts than RAW and S17 cells. In conclusion, P. monocephala can be considered as a valuable ingredient for the production of functional applications including nutraceuticals.

A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study.

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.