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Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography–tandem mass spectrometry (GC-MS/MS), liquid chromatography–tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease. [ABSTRACT FROM AUTHOR]

Background: Urinary interleukin-18 and cystatin-C are suggested to be biomarkers for predicting acute kidney injury (AKI). The aims of this study are to examine whether the urinary concentrations of interleukin-18 and cystatin-C vary with gestational age and other factors in non-AKI control neonates, and to determine whether urinary interleukin-18 and cystatin-C can predict AKI development in non-septic critically ill neonates, independently of potential confounders. Methods: We enrolled 62 non-septic critically ill neonates. Urine was collected every 48-72 h during the first 10 days of life. Results: Urinary concentration of cystatin-C, but not interleukin-18, decreased with increasing gestational age and body weight, but not with increasing postnatal age in non-AKI control neonates. Both urinary interleukin-18 and cystatin-C were associated with AKI, even after controlling for gestational and postnatal age, birth weight, gender, Apgar score and the score for neonatal acute physiology in non-septic critically ill neonates. Urinary interleukin-18 and cystatin-C had odds ratios of 2.27 and 2.07, and achieved the area under-the-receiver-operating-characteristic curve of 0.72 and 0.92, respectively, for predicting AKI. Conclusions: The urinary concentration of cystatin-C, but not interleukin-18, may decrease with increasing renal maturity. Both urinary interleukin-18 and cystatin-C are independently predictive of AKI in non-septic critically ill neonates. [ABSTRACT FROM AUTHOR]