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1.
Molecules ; 28(15)2023 Aug 07.
Article in English | MEDLINE | ID: mdl-37570898

ABSTRACT

The aim of this study was to improve the extraction method for urinary organic acids by miniaturizing and automating the process. Currently, manual extraction methods are commonly used, which can be time-consuming and lead to variations in test results. To address these issues, we reassessed and miniaturized the in-house extraction method, reducing the number of steps and the sample-to-solvent volumes required. The evaluated miniaturized method was translated into an automated extraction procedure on a MicroLab (ML) Star (Hamilton Technologies) liquid handler. This was then validated using samples obtained from the ERNDIM External Quality Assurance program. The organic acid extraction method was successfully miniaturized and automated using the Autosampler robot. The linear range for most of the thirteen standard analytes fell between 0 to 300 mg/L in spiked synthetic urine, with low (50 mg/L), medium (100 mg/L), and high (500 mg/L) levels. The correlation coefficient (r) for most analytes was >0.99, indicating a strong relationship between the measured values. Furthermore, the automated extraction method demonstrated acceptable precision, as most organic acids had coefficients of variation (CVs) below 20%. In conclusion, the automated extraction method provided comparable or even superior results compared to the current in-house method. It has the potential to reduce solvent volumes used during extraction, increase sample throughput, and minimize variability and random errors in routine diagnostic settings.


Subject(s)
Liquid-Liquid Extraction , Gas Chromatography-Mass Spectrometry/methods , Automation , Miniaturization , Liquid-Liquid Extraction/methods , Solvents
2.
Metabolomics ; 17(9): 75, 2021 08 19.
Article in English | MEDLINE | ID: mdl-34409503

ABSTRACT

INTRODUCTION: Metabolome variations have long been associated with normal hormonal fluctuations, and similar effects, related to the use of early generation synthetic hormones as a means of contraception, have also been identified. OBJECTIVE: We investigated the serum amino acid and acylcarnitine profiles induced by the use of combined oral contraceptives (COCs) consisting of Ethinylestradiol (EE) and a 4th generation progestin, Drospirenone (DRSP). METHOD: Gas chromatography mass spectrometry and liquid chromatography with tandem mass spectrometry was used to identify and quantify the serum amino acids and acyl carnitine levels in 24 controls, 25 DRSP/20EE users and 26 DRSP/30EE users. RESULTS: Of the 26 amino acid compounds measured, 13 showed significant variations in abundance between the control and COC user groups. Although none of the 21 acylcarnitine compounds detected were statistically significant with regards to group variations, a trend, related the EE concentration, was observed. The detected metabolome disparities corresponded to that identified for earlier generation COCs, all pointing toward increased oxidative stress levels in the user groups. CONCLUSION: These findings suggest that the clinical complications associated with these COCs could, to some extent, be alleviated by the simultaneous use of antioxidants. The study also highlights the role that targeted metabolomics could play in the elucidation of the underlying mechanisms of drug-induced severe effects.


Subject(s)
Contraceptives, Oral, Combined , Ethinyl Estradiol , Amino Acids , Androstenes , Carnitine/analogs & derivatives , Female , Humans
3.
Gut Pathog ; 16(1): 14, 2024 Mar 12.
Article in English | MEDLINE | ID: mdl-38475868

ABSTRACT

BACKGROUND: The pathogenesis of tuberculous meningitis (TBM) involves infection by Mycobacterium tuberculosis in the meninges and brain. However, recent studies have shown that the immune response and inflammatory processes triggered by TBM can have significant effects on gut microbiota. Disruptions in the gut microbiome have been linked to various systemic consequences, including altered immunity and metabolic dysregulation. Inflammation caused by TBM, antibiotic treatment, and changes in host immunity can all influence the composition of gut microbes. This complex relationship between TBM and the gut microbiome is of great importance in clinical settings. To gain a deeper understanding of the intricate interactions between TBM and the gut microbiome, we report innovative insights into the development of the disease in response to treatment. Ultimately, this could lead to improved outcomes, management strategies and quality of life for individuals affected by TBM. METHOD: We used a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach to investigate metabolites associated with gut metabolism in paediatric participants by analysing the urine samples collected from a control group (n = 40), and an experimental group (n = 35) with confirmed TBM, which were subdivided into TBM stage 1 (n = 8), stage 2 (n = 11) and stage 3 (n = 16). FINDINGS: Our metabolomics investigation showed that, of the 78 initially selected compounds of microbiome origin, eight unique urinary metabolites were identified: 2-methylbutyrlglycine, 3-hydroxypropionic acid, 3-methylcrotonylglycine, 4-hydroxyhippuric acid, 5-hydroxyindoleacetic acid, 5-hydroxyhexanoic acid, isobutyrylglycine, and phenylacetylglutamine as urinary markers of dysbiosis in TBM. CONCLUSION: These results - which are supported by previous urinary studies of tuberculosis - highlight the importance of gut metabolism and of identifying corresponding microbial metabolites as novel points for the foundation of improved management of TBM patients.

4.
STAR Protoc ; 4(2): 102181, 2023 Mar 22.
Article in English | MEDLINE | ID: mdl-36961819

ABSTRACT

Purine and pyrimidine disorders are often difficult to diagnose. Here, we present a 1H-NMR analysis protocol for the quantification of purines and pyrimidines in urine to diagnose associated disorders. We describe steps for pH adjustment, sample preparation, and 1H-NMR analysis and data analysis. The use of 1H-NMR requires a relatively small sample volume (1 mL) and minimal sample preparation. Analysis time produces accurate and reproducible data within 2 h.

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