Tuberculosis is one of the world's most emerging public health problems, particularly in developing countries. Chromatography based methods have been used to tackle this epidemic by focusing on biomarker detection. Unfortunately, interferences from lipids in the sputum matrix, particularly cholesterol, adversely affect the identification and detection of the marker compounds. The present contribution describes the serial combination of normal phase liquid chromatography (NPLC) with thermally assisted hydrolysis and methylation followed by gas chromatography-mass spectrometry (THM-GC-MS) to overcome the difficulties of biomarker evaluation. The in-series combination consists of an LC analysis where fractions are collected and then transferred to the THM-GC-MS system. This was either done with comprehensive coupling, transferring all the fractions, or with hyphenated interfacing, i.e. off-line multi heart-cutting, transferring only selected fractions. Owing to the high sensitivity and selectivity of LC as a sample pre-treatment method, and to the high specificity of the MS as a detector, this analytical approach, NPLC × THM-GC-MS, is extremely sensitive. The results obtained indicate that this analytical set-up is able to detect down to 1 × 10(3) mycobacteria/mL of Mycobacterium tuberculosis strain 124, spiked in blank sputum samples. It is a powerful analytical tool and also has great potential for full automation. If further studies demonstrate its usefulness when applied blind in real sputum specimens, this technique could compete with the current smear microscopy in the early diagnosis of tuberculosis.
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http://dx.doi.org/10.1016/j.chroma.2015.10.054 | DOI Listing |
Kidney360
November 2024
The Departments of Medicine, Veterans Affairs Palo Alto Healthcare System and Stanford University, Palo Alto, CA, USA 94304.
Background: Hemodialysis may excessively remove valuable solutes. Untargeted metabolomics data from a prior study suggested that ergothioneine was depleted in the plasma of hemodialysis subjects. Ergothioneine is a dietary-derived solute with antioxidant properties.
View Article and Find Full Text PDFKidney360
January 2025
Departments of Medicine, Stanford University and VA Palo Alto HCS, Palo Alto CA USA.
Background: If the GFR falls far enough, uremic symptoms such as anorexia and nausea prompt the initiation of dialysis. Thrice weekly hemodialysis can prevent recurrence of these symptoms even when patients become anuric. To accomplish this it must maintain the plasma levels of the uremic solutes which cause these symptoms lower than they were when dialysis was initiated.
View Article and Find Full Text PDFJ Proteome Res
January 2025
Discovery Research, AbbVie, Inc., 1 North Waukegan Rd., North Chicago, Illinois 60064, United States.
Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis.
View Article and Find Full Text PDFAnal Chem
January 2025
Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstraße 5, 45141 Essen, Germany.
Compound-specific stable isotope analysis (CSIA) using liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is a powerful tool for determining the isotopic composition of carbon in analytes from complex mixtures. However, LC-IRMS methods are constrained to fully aqueous eluents. Previous efforts to overcome this limitation were unsuccessful, as the use of organic eluents in LC-IRMS was deemed impossible.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Cellular Stress Biology, Institute of Artificial Intelligence, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reliability and reproducibility of results. To address these challenges, we developed QuanFormer, a deep learning method based on object detection designed to accurately quantify peak signals.
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