Метаболическое профилирование карбоновых и аминокислот в биологических жидкостях пациентов с диагнозом эндометриоз методами жидкостной (ВЭЖХ-УФ) и газовой (ГХ-МС) хроматографии
This study developed sensitive GC-MS and HPLC methods to profile organic acids and amino acids in serum from endometriosis patients, identifying characteristic metabolic profiles.
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The paper develops high-sensitivity analytical approaches for profiling low-molecular fatty acids and amino acids in blood serum from patients diagnosed with endometriosis, using GC–MS and reversed-phase HPLC with a diode-array detector. For 23 amino acids, the authors optimized derivatization and chromatographic conditions (including effects of mobile phase pH, solvent/buffer composition, and gradient profile), while showing that the conventional GC determination in silyl derivatives suffers from low volatility during sample preparation, leading to significant losses and unreproducible results. They also optimized derivatization-free GC–MS conditions for organic acids on a polar stationary phase, pairing serum preparation (protein precipitation and lipid removal) with a 70–230°C temperature gradient, yielding characteristic organic acid profiles in endometriosis and in myoma uteri as a comparison group. This paper is centrally about endometriosis — it reports metabolomic profiling of carbonic/organic acids and amino acids in the blood serum of patients with endometriosis using optimized GC–MS and HPLC methods.
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References (19)
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- Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis via openalex
- Endometriosis via openalex
- Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages via openalex
- Metabolomics reveals perturbations in endometrium and serum of minimal and mild endometriosis via openalex
- Pathophysiologic processes have an impact on the plasma metabolomic signature of endometriosis patients via openalex
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