Back

Evaluation of Some Serum Minerals in Type 2 Diabetic Patients Attending Federal Medical Centre Owo.

Ajao, F. O.; Olusegun, T. G.-G.; Oyeromi, B. O.; Obeagu, E. I.

2024-10-08 endocrinology
10.1101/2024.10.07.24315051 medRxiv
Show abstract

Minerals and trace elements play crucial roles in physiological processes, and alterations in their levels can have significant consequences for metabolic health. This study aimed to investigate serum mineral levels in patients with type 2 diabetes mellitus (T2DM) compared to healthy controls and explore their potential implications for disease pathophysiology. A total of 50 T2DM patients and 30 healthy individuals were included in the study. Serum levels of iron, copper, calcium, magnesium, and zinc were analysed using flame atomic absorption spectrometry. The results revealed significantly higher levels of iron and copper in T2DM patients compared to controls, while lower levels of calcium, magnesium, and zinc were observed in the T2DM group. These findings are consistent with previous research, highlighting the importance of mineral homeostasis in T2DM. Further analysis showed weak interrelationships among the studied minerals in T2DM patients, suggesting complex mechanisms underlying mineral metabolism in the disease. The discussion delved into potential mechanisms contributing to these alterations, including glycosuria-induced urinary loss of zinc and calciuresis due to hyperglycemia. Additionally, the study emphasised the importance of zinc and manganese in insulin production and release, as well as the contradictory findings regarding calcium levels in T2DM. Overall, this study provides valuable insights into serum mineral levels in T2DM and highlights the need for further research to elucidate their roles in disease progression and management.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.