Intracellular free magnesium concentration in healthy horses.
Judith Christine WinterG SponderR MerleJ R AschenbachHeidrun GehlenPublished in: Journal of animal physiology and animal nutrition (2018)
Equine metabolic syndrome (EMS) is a worldwide disease in horses that parallels human diabetes mellitus type 2. In both diseases, patients show an altered peripheral insulin sensitivity as a key feature. In humans, multiple studies have demonstrated the beneficial effect of magnesium supplementation on insulin sensitivity. However, serum magnesium levels vary and are therefore not a reliable indicator of the patients' magnesium status. Determining the intracellular free magnesium concentration appears to be a more sensitive diagnostic indicator. In this study, the free intracellular magnesium concentration was measured using mag-fura 2 spectrophotometry in blood lymphocytes in 12 healthy, non-obese horses at 9 a.m., 12 a.m. and 4 p.m. to establish reference ranges according to a protocol designed for human blood lymphocytes. Additionally, the serum magnesium concentration was measured. In all horses, the total serum magnesium concentration was within the reference range. The mean free magnesium concentration in blood lymphocytes of all horses was 0.291 ± 0.067 mmol/L with no significant difference between the time points. The reference range for the free intracellular magnesium concentration in equine lymphocytes was set at 0.16-0.42 mmol/L. The established values are slightly lower than those in healthy humans. The designed protocol for the measurement of the intracellular free magnesium concentration might be an excellent research tool to assess the cellular magnesium status and to reliably diagnose an altered magnesium homeostasis in EMS. Further studies shall elucidate possible alterations in cellular magnesium status in horses with EMS.
Keyphrases
- metabolic syndrome
- end stage renal disease
- endothelial cells
- randomized controlled trial
- type diabetes
- peripheral blood
- chronic kidney disease
- ejection fraction
- newly diagnosed
- adipose tissue
- reactive oxygen species
- machine learning
- skeletal muscle
- bariatric surgery
- prognostic factors
- neural network
- patient reported
- emergency medical