Development of a HILIC-MS/MS method for the quantification of histamine and its main metabolites in human urine samples

Nelis, Maxim; Decraecker, Lisse; Boeckxstaens, Guy E.; Augustijns, Patrick; Cabooter, Deirdre

doi:10.1016/j.talanta.2020.121328

Cited by 23 publications

(6 citation statements)

References 26 publications

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“…Even though RPLC is still the main separation mode in LC, due to its broad applicability and generally well-understood separation mechanism, HILIC has become increasingly popular in recent years, also for pharmaceutical applications. , This is due to its excellent suitability for compounds that are not well retained in RPLC, such as drugs and their polar metabolites, flavonoids, amino acids, peptides, nucleosides, and nucleotides. − The number of commercially available stationary phases for HILIC applications has increased tremendously, further promoting its use . The retention mechanism in HILIC was originally attributed to a partitioning process between a water-rich layer, adsorbed onto the polar surface of the stationary phase, and an acetonitrile-rich mobile phase .…”

Section: Introductionmentioning

confidence: 99%

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

et al. 2021

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Machine learning is a popular technique to predict the retention times of molecules based on descriptors. Descriptors and associated labels (e.g., retention times) of a set of molecules can be used to train a machine learning algorithm. However, descriptors are fixed molecular features which are not necessarily optimized for the given machine learning problem (e.g., to predict retention times). Recent advances in molecular machine learning make use of so-called graph convolutional networks (GCNs) to learn molecular representations from atoms and their bonds to adjacent atoms to optimize the molecular representation for the given problem. In this study, two GCNs were implemented to predict the retention times of molecules for three different chromatographic data sets and compared to seven benchmarks (including two state-of-the art machine learning models). Additionally, saliency maps were computed from trained GCNs to better interpret the importance of certain molecular sub-structures in the data sets. Based on the overall observations of this study, the GCNs performed better than all benchmarks, either significantly outperforming them (5–25% lower mean absolute error) or performing similar to them (<5% difference). Saliency maps revealed a significant difference in molecular sub-structures that are important for predictions of different chromatographic data sets (reversed-phase liquid chromatography vs hydrophilic interaction liquid chromatography).

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Section: Introductionmentioning

confidence: 99%

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

et al. 2021

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“…The endogenous occurrence of the target and the lack of labeled internal standard prompted the use of the standard addition method as a viable alternative for evaluating ME. 65 Specifically, ME was evaluated with reference to the method of Lv et al and was calculated according to formula 1. 66 The ME (%) obtained was - 5.17%, which is within ± 15%, so that it can be considered as no significant ME.…”

Section: Resultsmentioning

confidence: 99%

Biosynthesis of Nanoparticles with Green Tea for Inhibition of β-Amyloid Fibrillation Coupled with Ligands Analysis

Zhang,

Li,

Han

et al. 2024

IJN

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Background: Inhibition of amyloid β protein fragment (Aβ) aggregation is considered to be one of the most effective strategies for the treatment of Alzheimer's disease. (-)-Epigallocatechin-3-gallate (EGCG) has been found to be effective in this regard; however, owing to its low bioavailability, nanodelivery is recommended for practical applications. Compared to chemical reduction methods, biosynthesis avoids possible biotoxicity and cumbersome preparation processes. Materials and Methods:The interaction between EGCG and Aβ42 was simulated by molecular docking, and green tea-conjugated gold nanoparticles (GT-Au NPs) and EGCG-Au NPs were synthesized using EGCG-enriched green tea and EGCG solutions, respectively. Surface active molecules of the particles were identified and analyzed using various liquid chromatography-tandem triple quadrupole mass spectrometry methods. ThT fluorescence assay, circular dichroism, and TEM were used to investigate the effect of synthesized particles on the inhibition of Aβ42 aggregation. Results: EGCG as well as apigenin, quercetin, baicalin, and glutathione were identified as capping ligands stabilized on the surface of GT-Au NPs. They more or less inhibited Aβ42 aggregation or promoted fibril disaggregation, with EGCG being the most effective, which bound to Aβ42 through hydrogen bonding, hydrophobic interactions, etc. resulting in 39.86% and 88.50% inhibition of aggregation and disaggregation effects, respectively. EGCG-Au NPs were not as effective as free EGCG, whereas multiple thiols and polyphenols in green tea accelerated and optimized heavy metal detoxification. The synthesized GT-Au NPs conferred the efficacy of diverse ligands to the particles, with inhibition of aggregation and disaggregation effects of 54.69% and 88.75%, respectively, while increasing the yield, enhancing water solubility, and decreasing cost. Conclusion: Biosynthesis of nanoparticles using green tea is a promising simple and economical drug-carrying approach to confer multiple pharmacophore molecules to Au NPs. This could be used to design new drug candidates to treat Alzheimer's disease.

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“…In the second metabolic pathway, N-methylhistamine produced by HNMT is oxidised by monoamine oxidase B leading to N-methyl imidazole acetaldehyde that is further transformed into methyl-imidazole acetic acid by ADH. Histamine can also be metabolised to Nω-acetylhistamine by gut bacteria [ 4 , 6 ].…”

Section: Histamine Metabolismmentioning

confidence: 99%

Histamine Intolerance in Children: A Narrative Review

et al. 2021

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Histamine intolerance is defined as a disequilibrium of accumulated histamine and the capacity for histamine degradation. This clinical term addresses a non-immunologically mediated pathology when histamine ingested with food is not particularly high, however its degradation is decreased. This paper aims to provide a narrative review on etiopathology, epidemiology, possible diagnostic algorithms and diagnostic challenges of histamine intolerance in children. The clinical picture of histamine intolerance in children is similar to that observed in adults apart from male predominance found in paediatric patients. Both in children and adults, a histamine-reduced diet is typically the treatment of choice. Diamine oxidase supplementation offers another treatment option. There is no symptom or test pathognomonic for histamine intolerance. Nevertheless, manifestations of chronic gastrointestinal symptoms, measurements of diamine oxidase deficits, positive results of histamine provocation tests and improvement in symptoms with histamine-reduced diet considerably increase the probability of histamine intolerance diagnosis. These factors have been included in the proposed diagnostic algorithm for histamine intolerance. In children histamine intolerance most likely co-occurs with allergies and bowel diseases, which creates an additional diagnostic challenge. As the evidence for children is poor further research is needed the determine epidemiology, validate diagnostic algorithms and establish possible treatment options regarding histamine intolerance.

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Development of a HILIC-MS/MS method for the quantification of histamine and its main metabolites in human urine samples

Cited by 23 publications

References 26 publications

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

Biosynthesis of Nanoparticles with Green Tea for Inhibition of β-Amyloid Fibrillation Coupled with Ligands Analysis

Histamine Intolerance in Children: A Narrative Review

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