Isotopic dilution analysis. Cholesterol in gallstones and caffeine in tea, cola, and NoDoz

1969 ◽  
Vol 46 (11) ◽  
pp. 767 ◽  
Author(s):  
Addison Ault ◽  
Raymond Kraig
Talanta ◽  
1963 ◽  
Vol 10 (4) ◽  
pp. 375-381 ◽  
Author(s):  
Jiří Starý ◽  
Jaromír Ru̇žička ◽  
Milan Salamon

2009 ◽  
Vol 280 (2) ◽  
pp. 381-383
Author(s):  
T. Ünak ◽  
Ç. Çal ◽  
Y. Yildirim ◽  
U. Avcıbaşı ◽  
G. Ünak

2020 ◽  
Vol 64 (1) ◽  
pp. 169-183 ◽  
Author(s):  
Naila Rabbani ◽  
Paul J. Thornalley

Abstract Liquid chromatography-tandem mass spectrometry (LC-MS/MS) provides a high sensitivity, high specificity multiplexed method for concurrent detection of adducts formed by protein glycation, oxidation and nitration, also called AGEomics. Combined with stable isotopic dilution analysis, it provides for robust quantitation of protein glycation, oxidation and nitration adduct analytes. It is the reference method for such measurements. LC-MS/MS has been used to measure glycated, oxidized and nitrated amino acids – also called glycation, oxidation and nitration free adducts, with a concurrent quantitation of the amino acid metabolome in physiological fluids. Similar adduct residues in proteins may be quantitated with prior exhaustive enzymatic hydrolysis. It has also been applied to quantitation of other post-translation modifications, such as citrullination and formation of Nε-(γ-glutamyl)lysine crosslink by transglutaminases. Application to cellular and extracellular proteins gives estimates of the steady-state levels of protein modification by glycation, oxidation and nitration, and measurement of the accumulation of glycation, oxidation and nitration adducts in cell culture medium and urinary excretion gives an indication of flux of adduct formation. Measurement of glycation, oxidation and nitration free adducts in plasma and urine provides for estimates of renal clearance of free adducts. Diagnostic potential in clinical studies has been enhanced by the combination of estimates of multiple adducts in optimized diagnostic algorithms by machine learning. Recent applications have been in early-stage detection of metabolic, vascular and renal disease, and arthritis, metabolic control and risk of developing vascular complication in diabetes, and a blood test for autism.


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