MS Data Research Articles

Cepathiolactols and Cepathiolactones─Two Newly Discovered Families of Organosulfur Compounds Fored in Cut Onion.

Isolation and structural characterization of two large families of organosulfur compounds spontaneously formed upon cutting of onion (Allium cepa) were carried out. The structures of these hitherto unknown species, trivially named cepathiolactols and cepathiolactones, were established based on NMR, MS, and IR data. It was found that cepathiolactols (CxHyOS3 and CxHyO2S4; x = 7-12, y = 14-24) are 3,4-dimethyl-γ-thiolactols bearing various side chains linked via a disulfanyl moiety at position C-5. On the other hand, cepathiolactones were shown to be 3,4-dimethyl-γ-thiolactones structurally analogous to cepathiolactols. Sensory properties of cepathiolactols were also evaluated, along with testing their ability to participate in the formation of pink discoloration of processed onion.

Innovative Discovery Studies of Anti Lungs Cancer Active Drug Substances in Medicinal Chemistry

The discovery study of anti cancer active drug substance of (2S,2′S)-2,2′-[[2,2′- Diamino-4,4′,6-trioxo-1,4,4′,6,7,7′-hexahydro-1′H,5H-5,6′-bipyrrolo[2,3-d]pyrimidine-5,5′- diyl]bis(ethylenebenzene-4,1-diylcarbonylimino)] dipentanedioic acid was synthesized and characterized by medicinal chemistry bath way, also this product was obtained via the associated with the synthesis of pemetrexed disodium was performed. The possibility of (2S,2′S)-2,2′-[[2,2′-Diamino-4,4′,6-trioxo-1,4,4′,6,7,7′- hexahydro-1′H,5H-5,6′-bipyrrolo[2,3-d]pyrimidine-5,5′-diyl]bis(ethylenebenzene-4,1-diylcarbonylimino)] dipentanedioic acid forming has been mentioned in literature, but no study on this structure has been published yet. This paper describes the development of the synthesis methods and preclinical studies for this compound and discusses their structure elucidation on the basis of NMR experiments and MS data. The identification of anti cancer drug activity of this compound by preclinical test, it should be useful for identify the new anticancer drug in pemetrexed generation.

MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data

Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. Methods: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. We designed a new descriptor, MCH (mode of carbon and hydrogen), to increase the specificity of lipid subclass prediction in nominal mass resolution MS data. Results: The model, trained with 6760 and 6862 manually curated MS/MS spectra for the positive and negative ion modes, respectively, classified queries into one or several of 97 lipid subclasses, achieving an accuracy of 97.4% in the test set. The program was further validated using various datasets from different instruments and curators, with the average accuracy exceeding 87.2%. Using an integrated approach with molecular spectral networking, we demonstrated the utility of MS2Lipid by annotating microbiota-derived esterified bile acids, whose abundance was significantly increased in fecal samples of obese patients in a human cohort study. This suggests that the machine learning model provides an independent criterion for lipid subclass classification, enhancing the annotation of lipid metabolites within known lipid classes. Conclusions: MS2Lipid is a highly accurate machine learning model that enhances lipid subclass annotation from MS/MS data and provides an independent criterion.

Isolation of new isoflavonoids derivatives from Genista carinalis Griseb. and biological activity

The genus Genista L. has been used in the treatment of rheumatic, diabetic and ulcerous diseases. Herein, the antioxidant, anticholinesterase, and antidiabetic activities of Genista carinalis Griseb. extracts were determined. The antioxidant activity was performed FRAP, DPPH, CUPRAC, and TEAC assays, while anticholinesterase activity was performed against acetylcholinesterase and butyrylcholinesterase, and antidiabetic activity against α-amylase and α-glucosidase, spectrophotometrically. The activity results allowed for the study of the phytochemistry of the ethyl acetate extract that exhibited the best activity. Three new isoflavonoids, 5-methyl-7-methoxy-4′-hydroxy isoflavone (3), 7-acetyl-5-hydroxy-4′-methoxy isoflavone (4) and 7-O-[β-D-glucopyranosyl-(6′′→6′′′)-β-D-glucopyranosyl]-5-4′-dihydroxy isoflavone (5), together with two known compounds, isoprunetin (1) and 6-hydroxy biochanin A (2) were isolated from the ethyl acetate extract. Their structures were elucidated by extensive 1D-, 2D-NMR, and MS data analyses. Compound (3) showed the highest antioxidant potential in TEAC, FRAP, and CUPRAC assays, while (2) exhibited higher butyrylcholinesterase enzyme inhibitory activity among the isolated compounds.

Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Qualitative and quantitative analysis of major components in Abelmoschus manihot flowers treated with different drying methods using UHPLC Q-exactive MS and HPLC-PDA

The flowers of Abelmoschus manihot (L.) Medic are commonly used in clinical practice in China to cure forms of chronic kidney disease. Despite a long history of traditional use, the flowers obtained by different drying technologies have never been fully chemically characterized, and the ranges of constituents between different drying methods have not been comprehensively reported. To establish a quality control and chemical characterization method, a total of 14 batches of samples corresponding to 14 postharvest treatments were studied. Seven flavonoids were quantified using a HPLC-PDA method. The method was validated in terms of linearity (r > 0.999), precision (intra- and inter-day: 0.7–1.4 %), accuracy (99.90–100.7 %), detection limit (0.34–0.46 µg/mL) and quantification limit (1.15–1.52 µg/mL). The contents of total flavonoids in manihot flowers were as follows in descending order: Infrared Drying (50.96 mg/g) > Microwave Drying (41.84 mg/g) ≈ Hot-air Drying (39.58 mg/g) ≈ Fresh (39.35 mg/g) ≈ Primary Drying (38.95 mg/g). Principal component analysis showed that samples processed with Fresh, Primary Drying, and the investigated three modern drying methods were well classified into three domains, indicating an important difference between drying methods. For the purpose of saving the flavonoids contents, infrared drying under 80–100 °C would be most acceptable. Furthermore, using UHPLC Q-Exactive Orbitrap MS data with targeted and non-targeted approaches, 28 compounds were identified in Abelmoschus manihot samples. Flavonoids were the main group of compounds found in Abelmoschus manihot flowers. The study could provide the scientific evidence for the selection and optimization of appropriate drying method for manihot flowers, and also provide the reference for the formation of generic primary drying processing technology for medicinal flowers containing flavonoids.

Thuwalamides A–E: polychlorinated amides from the marine sponge Lamellodysidea herbacea collected from the Saudi Arabian Red Sea

Thuwalamides A–E (1, 3, 5, 6 and 8), previously undescribed polychlorinated amides, along with ten previously reported related compounds (2, 4, 7 and 9–15), were isolated from the organic extract of the marine sponge Lamellodysidea herbacea (Keller), collected off the village of Thuwal in the Red Sea at Saudi Arabia. The structures of the isolated compounds have been determined through extensive analysis of their NMR and MS data, while their absolute stereochemistry was unequivocally established via single crystal X-ray diffraction. Additionally, the absolute stereochemistry of the previously reported compounds 2 and 4, whose configuration was not determined, has also been established using single-crystal X-ray crystallographic analysis. The antibacterial activity of compounds 1–15 was evaluated against Escherichia coli and Staphylococcus aureus. Among them, compound 14 displayed activity against S. aureus comparable to vancomycin that was used as a positive control with a MIC value of 4 μg/mL.

A Study On The Health Seeking Behavior Among Caregivers Of Under-Five Children In A Rural Area Of West Bengal

Background- Children are most vulnerable and dependent groups on others in the society other than geriatric person .So appropriate healthcare seeking behavior of their caregivers are very much important to reduce morbidity & mortality and improve healthy life . Materials & Methods-This was a cross-sectional study was conducted at rural area of West Bengal among 180 caregivers of under 5 yr children with the help of predesigned pretested semistructured schedule. Study subject selected by systematic random sampling and data compilation were done MS Office Excel-2010 and data analysis were done by chi sq test in IBM SPSS version 2019 Results: Among 180 caregivers majority were 20-30yrs age gr(65%), joint family(64.4%), OBC(39.4%), Hindu(86.1%),Literate(71.1%), Homemaker(82.8%), having health insurance(76.1%),lower middle socio economic class(45%). Among children majority were 3-5yrs age gr(47.8%),female(50.6%), vaccinated not at par age (60.6%), second or more order child(59.4%). 20.6% caregivers had in appropriate healthcare seeking behavior for their children.Appropriate health seeking behavior among caregivers significantly associated with≤30yrs (ꭕ2=20.33,,df=1,p=.000007 ),nuclear family(ꭕ2=4.74, df=1,p=.029, )literate(ꭕ2=71.72,df=1,p=<.000001), homemaker(ꭕ2=28.19,df=1, p=.0000012), upper middle & upper lower SES(ꭕ2=4.44,df=1, p=.035),having insurance(ꭕ2=34.91,df=1, p=<.00001) but not significantly associate with religion(ꭕ2=1.58 ,df=1,p=.2) & gender of children(ꭕ2=.0058, df=1, p=.939). The majority of caregivers for children (71.7%) were depending generally on Govt health facility and a sizeable portion of caregivers(42.2%) collected medicine over the counter without consultation of medical professional and 35% caregivers generally approached AYUSH system of medicine. Conclusion- From this study it was concluded that appropriate health care seeking behavior among caregivers are significantly influenced by with ≤30yrs age gr , joint family ,occupation ,education , socio economic scale, health insurance In rural bengal primarily dependent on Govt health facility and a sizeable population still collected medicine over the counter with consultation of medical supervision

Stability and degradation mechanism of (−)-epicatechin in thermal processing

(−)-Epicatechin (EC) is a commonly dietary phytochemical that presents multi-physiological activities on human health. Thermal processing is a common method to extract EC, albeit likely to degrade EC considering its thermal instability. In this study, an 85-min non-durable bathing incubation assay was designed to simulate the state of EC in boiling water while cooking. Monitoring of degradation products was performed using ultra-performance liquid chromatography combined with electrospray ionization quadrupole tandem mass spectrometric detection (UPLC-ESI-TSQ-MS/MS). The results revealed that ca. 65.2 % loss of EC was detected in the first 10 min, and over 99.5 % of EC was degraded within 30 min. A total of 22 degradation products were identified based on retention time, full and tandem MS data were the first to be comprehensively reported. Isomerization, oxidation, hydroxylation, dimerization, and ring cleavage were the main chemical reactions that occurred for EC in boiling aqueous solution.

Green Construction of Novel 3‐(Benzo[d][1,3]dioxol‐5‐yl)‐1,8‐naphthyridin‐2‐yl)amino)quinazoline‐2,4(1H,3H)‐dione and Phenyl‐[1,2,4]triazolo[4,3‐a][1,8]naphthyridine and Their Antimicrobial Activity

ABSTRACTA straightforward and an efficient green synthetic method has been outlined for the construction of 3‐(benzo[d][1, 3] dioxol‐5‐yl)‐1,8‐naphthyridine derivatives in the presence of glacial acetic acid and Cu(OAc)2 catalyst accomplished excellent yields in short reaction time. The reaction proceeds efficiently by using a greener way under microwave conditions to elevate the quantity of pure products. The purity of all the synthesized compounds was confirmed by IR, 1H and 13CNMR, LC–MS data and also from the elemental analyses studies. The synthesized compounds 7d and 7f performed strongest antibacterial activity against pathogenic cell lines Bacillus subtilis (17.5, 20.5 mm), Escherichia coli (28.5, 30 mm), and antifungal cell lines Candida albicans (18, 22.5 mm), and Aspergillus Niger (28.5, 40.5 mm) which are compared with clinical drugs Penicillin, Grieseofulvin. We scrutinized the remaining molecules and found that their activity ranged from modest to exceptional.

Antimicrobial activity of blue mold (Penicillium italicum) Filtrates against some species of pathogenic bacteria

Background: Penicillium saprophytic species, which primarily consume organic biodegradable materials, is a common example of a fungal species. The preparation filtrates of Penicillium italicum, a saprophyte on citrus fruits frequently linked to post-harvest diseases in this crop, were included in the current investigation. Objective: This investigation aimed determine the most efficient culture medium for the production of antibacterial secondary metabolites. Patients and Methods: included identifying the growth medium for P. italicum and produce its metabolites through the use of gas chromatography-mass spectrometry (GC MS) for both solid-state fermentation filtrate (SSFF) and liquid fermentation filtrate (LFF). Additionally, the antimicrobial activity of the mold filtrate against certain pathogenic bacteria was assessed using the agar well diffusion method. Results: indicated that the biomass used for mold growth was heavier in SSFF than LFF, and according to the findings, the selective active isolate's crude filtrate from two duplicates of the P. italicum Yeast Extract Sucrose YES culture medium was 0.063 mg, while the crude extract from rotten orange (as a solid medium) containing P. italicum was 0.11 mg. Tetracosane and other substances with a track record of therapeutic activity were found in the two mold extracts, according to GC MS data. Overall, both SSFF and LFF demonstrated antibacterial activity against Klebsiella pneumonia, Escherichia coli, Acinetobacter baumannii, Pseudomonas aeruginosa and Staphylococcus aureus, with the inhibition zones± standard deviation (IZ± SD) being 24.7± 0.57, 18.2± 0.28, 26.3± 0.59, 21.6± 0.51, and 32.8± 0.21 (for SSFF) mm and 0.0, 12.3±0.57, 28.16±0.20, 19.3±1.15, and 28±0.2 (for LFF) mm, respectively. Conclusion: the filtrate of P. italicum from a natural medium (rotted orange) as a solid state fermentation was more weighted and gave many effective metabolites compared to what was produced by liquid fermentation on a synthetic medium, and both liquid and solid fermentation filtrates demonstrated efficacy against harmful bacteria.

The Molecules Gateway: A Homogeneous, Searchable Database of 150k Annotated Molecules from Actinomycetes.

Natural products are a sustainable resource for drug discovery, but their identification in complex mixtures remains a daunting task. We present an automated pipeline that compares, harmonizes and ranks the annotations of LC-HRMS data by different tools. When applied to 7,400 extracts derived from 6,566 strains belonging to 86 actinomycete genera, it yielded 150,000 molecules after processing over 50 million MS features. The web-based Molecules Gateway provides a highly interactive access to experimental and calculated data for these molecules, along with the metadata related to extracts and producer strains. We show how the Molecules Gateway can be used to rapidly identify known hard to find microbial products, unreported analogs of known families and not yet described metabolites. The Molecules Gateway, which complements available repositories, contains annotated MS data, both acquired and computationally processed under an identical workflow, making it suitable for global analyses which reveal a large and untapped chemical diversity afforded by actinomycetes.

Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data.

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and address challenges of complete annotation of molecules in untargeted metabolomics. "Molecular networks" (MNs), as used in the Global Natural Products Social Molecular Networking platform, are a prominent strategy for exploring and visualizing molecular relationships and improving annotation. MNs are mathematical graphs showing the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated with a single molecular identity. This paper introduces "molecular hypernetworks" (MHNs) as more complex MN models able to natively represent multiway relationships among observations. Compared to MNs, MHNs can more parsimoniously represent the inherent complexity present among groups of observations, initially supporting improved exploratory data analysis and visualization. MHNs also promise to increase confidence in annotation propagation, for both human and analytical processing. We first illustrate MHNs with simple examples, and build them from liquid chromatography- and ion mobility spectrometry-separated MS data. We then describe a method to construct MHNs directly from existing MNs as their "clique reconstructions", demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

DIFFERENTIAL CELL SURFACE PROTEOMICS OF FLOTILLIN-1, HMGB1 AND AMINOPEPTIDASE N IN H3 MUTATED PAEDIATRIC HIGH-GRADE GLIOMAS

Abstract AIMS High-grade gliomas (HGG) are central nervous system tumour in children, where treatment options remain elusive, leaving children with a dismal prognosis. Histone H3.3 mutations, K27M and G34V/R have been identified as the two most common recurrent somatic mutations in paediatric HGG (pHGG). These mutations are present in 50% of pHGG compared to only 1% in adult gliomas. Our previous proteomic research on cell membrane protein through protein MS data analyses have identified different signatures of differentially expressed cell membrane proteins in H3-G34R/V mutated pHGG cells, in comparison to H3 wild type tumour cells in culture. Among these proteins we have identified flotillin-1, HMGB1 (High mobility group box 1) and aminopeptidase N. Flotillin-1 is associated with numerous malignancies and HMGB1 also functions as an oncogene and aminopeptidase N is a cell surface metalloprotease involved in tumour progression. Our aim is to study the expression and localisation of these cell surface proteins in H3 mutated and wild type tumour cells, to validate them as targets for developing novel therapeutics. METHOD Expression and localisation of flotillin-1, HMGB1 and aminopeptidase N in H3.3 mutated pHGG cell lines in comparison to H3 wildtype glioma and control cells was analysed, using different protein expression assays including immunofluorescence microscopy and western blotting. RESULTS Results showed statistically significant differential protein expression and localisation of these proteins. Flotillin-1 had increased cell membrane localization in H3 mutated cells. HMGB1 expression was increased, while aminopeptidase N expression was decreased in the H3 mutated cells in comparison to wildtype pHGG. CONCLUSION This new knowledge of the cell membrane proteomics of H3 mutated pHGG may help us utilise Flotillin- 1,HMGB1 and aminopeptidase N, as potential therapeutic targets for these unique H3 mutated children’s brain tumours.

CMSSP: A Contrastive Mass Spectra-Structure Pretraining Model for Metabolite Identification.

A pivotal challenge in metabolite research is the structural annotation of metabolites from tandem mass spectrometry (MS/MS) data. The integration of artificial intelligence (AI) has revolutionized the interpretation of MS data, facilitating the identification of elusive metabolites within the metabolomics landscape. Innovative methodologies are primarily focusing on transforming MS/MS spectra or molecular structures into a unified modality to enable similarity-based comparison and interpretation. In this work, we present CMSSP, a novel Contrastive Mass Spectra-Structure Pretraining framework designed for metabolite annotation. The primary objective of CMSSP is to establish a representation space that facilitates a direct comparison between MS/MS spectra and molecular structures, transcending the limitations of distinct modalities. The evaluation on two benchmark test sets demonstrates the efficacy of the approach. CMSSP achieved a remarkable enhancement in annotation accuracy, outperforming the state-of-the-art methods by a significant margin. Specifically, it improved the top-1 accuracy by 30% on the CASMI 2017 data set and realized a 16% increase in top-10 accuracy on an independent test set. Moreover, the model displayed superior identification accuracy across all seven chemical categories, showcasing its robustness and versatility. Finally, the MS/MS data of 30 metabolites from Glycyrrhiza glabra were analyzed, achieving top-1 and top-3 accuracies of 86.7 and 100%, respectively. The CMSSP model serves as a potent tool for the dissection and interpretation of intricate MS/MS data, propelling the field toward more accurate and efficient metabolite annotation. This not only augments the analytical capabilities of metabolomics but also paves the way for future discoveries in understanding of complex biological systems.

Coupling Image-Fusion Techniques with Machine Learning to Enhance Dynamic Monitoring of Nitrogen Content in Winter Wheat from UAV Multi-Source

Plant nitrogen concentration (PNC) is a key indicator reflecting the growth and development status of plants. The timely and accurate monitoring of plant PNC is of great significance for the refined management of crop nutrition in the field. The rapidly developing sensor technology provides a powerful means for monitoring crop PNC. Although RGB images have rich spatial information, they lack the spectral information of the red edge and near infrared bands, which are more sensitive to vegetation. Conversely, multispectral images offer superior spectral resolution but typically lag in spatial detail compared to RGB images. Therefore, the purpose of this study is to improve the accuracy and efficiency of crop PNC monitoring by combining the advantages of RGB images and multispectral images through image-fusion technology. This study was based on the booting, heading, and early-filling stages of winter wheat, synchronously acquiring UAV RGB and MS data, using Gram–Schmidt (GS) and principal component (PC) image-fusion methods to generate fused images and evaluate them with multiple image-quality indicators. Subsequently, models for predicting wheat PNC were constructed using machine-selection algorithms such as RF, GPR, and XGB. The results show that the RGB_B1 image contains richer image information and more image details compared to other bands. The GS image-fusion method is superior to the PC method, and the performance of fusing high-resolution RGB_B1 band images with MS images using the GS method is optimal. After image fusion, the correlation between vegetation indices (VIs) and wheat PNC has been enhanced to varying degrees in different growth periods, significantly enhancing the response ability of spectral information to wheat PNC. To comprehensively assess the potential of fused images in estimating wheat PNC, this study fully compared the performance of PNC models before and after fusion using machine learning algorithms such as Random Forest (RF), Gaussian Process Regression (GPR), and eXtreme Gradient Boosting (XGB). The results show that the model established by the fusion image has high stability and accuracy in a single growth period, multiple growth periods, different varieties, and different nitrogen treatments, making it significantly better than the MS image. The most significant enhancements were during the booting to early-filling stages, particularly with the RF algorithm, which achieved an 18.8% increase in R2, a 26.5% increase in RPD, and a 19.7% decrease in RMSE. This study provides an effective technical means for the dynamic monitoring of crop nutritional status and provides strong technical support for the precise management of crop nutrition.

A dataset for developing proteomic tools for pathogen detection via differential cell lysis of whole blood samples

This data descriptor presents a curated dataset for pathogen detection and identification (Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans) directly from whole-blood samples. The dataset was created using differential cell lysis combined with rapid extraction, digestion, and mass spectrometry-based proteomics. Our method offers a rapid diagnostic alternative to traditional culture, enabling timely disease management, such as sepsis. Highlighting our dataset’s uniqueness, it features a three-tier structure: Spectral Libraries of Pathogens for identifying peptide peaks for putative biomarkers; Spiked pathogen in blood MS data for biomarker panel optimization through varied concentration samples; and Parallel Reaction Monitoring (PRM) data from sepsis patients for validating our biomarker panel, achieving 83.3% sensitivity within seven hours without microbial enrichment culture. This dataset serves as a comprehensive reference for bioinformatic tool development and biomarker panel proposals, advancing microbial detection, antimicrobial resistance, and epidemiological studies.

An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species

BackgroundDespite the widespread implementation of analytical hardware capable of recording large-scale datasets for botanical natural products, the data processing procedures for compound annotation remain a bothersome obstacle that demand a tremendous amount of time and expert knowledge. MethodsHerein, an automatic LC-MS/MS data analysis workflow with AutoAnnotatoR was introduced for the compound annotation of plant derived natural products, which has the merits of great efficiency, high accuracy, saving time and simplified process. This procedure enabled automatic matching of MS2 data with characteristic fragment ions, as well as MS1 data with compound libraries, which improves the accuracy of structural elucidation. Notably, the optimization of collision energy for each target ion was successfully performed for the first time, facilitating the acquisition of comprehensive fragmentation information. ResultsThe automatic analysis workflow with AutoAnnotatoR was successfully applied for the annotation of alkaloids from 10 botanical origins of Fritillaria species. Consequently, a total of 2684 chemical constituents were tentatively characterized, with 23 components being unambiguously validated by reference standards and 2434 being probable novel chemicals. ConclusionThe entire data analysis procedure takes only a few hours, vastly improving analysis speed while assuring high accuracy. This method provides a powerful tool for the rapid and precise annotation of complex natural products. The workflow is publicly accessible on Github as an open-source R package called AutoAnnotatoR (https://github.com/anyaling2022/AutoAnnotatoR).

Multi-platform analysis revealed the substance basis and mechanism of Wei-Tong-Xin in ameliorating ENS dysfunction for dyspepsia treatment

Ethnopharmacological relevanceDuodenal motility disorder is a contributing factor to dyspepsia. The traditional Chinese medicine (TCM) formula Wei-Tong-Xin (WTX), originated from the famous ancient Chinese formula “Wan Ying Yuan”, has been demonstrated efficacy in alleviating dyspepsia. Aim of the studyThe current study aims to elucidate the chemical composition of WTX to establish the pharmacodynamic material basis. On the basis of component, in depth to illuminate the mechanism by which WTX treats dyspepsia via constructing the comprehensive analysis of multi-platform. Materials and methodsThe chemical constituents of WTX were systematically analyzed by UHPLC-Q-TOF-MS/MS data processing methods. Based on this, network pharmacology was employed to predict the mechanism by which WTX improved dyspepsia. The dyspepsia mouse model was constructed, and histopathology as well as intestinal permeability were assessed using H&E staining, PAS staining and FITC-dextran assay. Protein expression was detected using Western blot, immunofluorescence, immunohistochemistry and ELISA kits. ResultsA total of 100 chemical components of WTX were preliminarily identified. Network pharmacological analysis indicated that the therapeutic mechanism of WTX in treating dyspepsia may be related to the regulation of inflammation and oxidative stress-related signaling pathways. In vivo studies showed that WTX mitigated duodenal inflammation and oxidative stress responses, repairing the intestinal mucosal barrier damaged by cisplatin (CIS). Additionally, WTX restored the number of glial cells diminished by inflammatory damage, and ameliorated the serotoninergic neuronal dysfunction caused by insufficient secretion of glia-derived neurotrophic factor (GDNF), and enhanced intestinal transit. ConclusionsIn this study, a total of 100 components of the WTX extract were identified through literature review and mass spectrometry database search. Utilizing computer technology, in conjunction with pharmacodynamic and mechanistic studies, WTX has been found to restore serotoninergic neuronal function by reducing intestinal mucosal inflammatory and oxidative damage, ultimately promoting intestinal transport and treating dyspepsia.

Impact of formulation and home storage conditions on the content of furan and derivatives in powdered infant formula

While autoxidation of Polyunsaturated Fatty Acids (PUFAs) is a potential source of furan and its derivatives, the regulatory obligation to enrich powdered infant formulae (PIF) with some of these compounds might raise safety issues. The aim of this study was to investigate the impact of formulation and home storage conditions on the generation of furan and its derivatives in PIF. Furan, 2-methylfuran (2-MF) and 3-methylfuran (3-MF) were monitored by a validated SHS-GC-Q Exactive-Orbitrap MS method in six PIF formulated with high or low concentrations of different PUFAs (ALA, ARA, DHA), pro-oxidants (iron) and anti-oxidants (vitamins) and stored for 21 days under more or less oxidizing home storage conditions, including temperature (19 °C or 40 °C) and oxygen exposure (protected or not from ambient air). For the three compounds, the quality of the measurements in PIF was first confirmed with suitable linearity, limits of quantification, precision and recoveries. In a second step, the impact of the formulation was evaluated on six PIF commercial samples differing significantly in their composition in ALA, ARA, DHA, iron and/or vitamin E and C. While furan was quantifiable (2.8 µg/kg) in only one PIF with high content of DHA and iron and low level of vitamins, 2-MF was only quantifiable in two other PIF which were distinguished by a 15 to 20 % higher ALA content and 3-MF was not detected in any of the six PIF studied.. In a third step, the effect of storage conditions was studied on the six PIFs and the increase in storage temperature to 40 °C led to an increase of up to 33 % in the 2-MF concentration in the two PIF formulations where it was quantifiable. Nevertheless, the estimation of the Margin of Exposure (MOE) showed that the risk related to furan and its derivatives could be ruled out regardless of the formulation or storage conditions. Finally, in order to explore other derivatives and to investigate the mechanisms involved in the generation of furan compounds in PIF, a suspect screening approach was implemented on the SHS-GC-Q Exactive Orbitrap MS data. It made it possible on the one hand to point out two additional furan derivatives in PIF, 2-ethylfuran and 2-pentylfuran. On the other hand, it enabled to discuss the oxidation pathways involved in the generation of furan compounds in PIF from profiling of known PUFA oxidation markers also detected in the samples.