Some oscillatory phenomena of blood glucose regulation: An exploratory pilot study in pigs

Bioprinted 3D Bionic Scaffolds with Pancreatic Islets as a New Therapy for Type 1 Diabetes-Analysis of the Results of Preclinical Studies on a Mouse Model

Recently, tissue engineering, including 3D bioprinting of the pancreas, has acquired clinical significance and has become an outstanding potential method of customized treatment for type 1 diabetes mellitus. The study aimed to evaluate the function of 3D-bioprinted pancreatic petals with pancreatic islets in the murine model. A total of 60 NOD-SCID (Nonobese diabetic/severe combined immunodeficiency) mice were used in the study and divided into three groups: control group; IsletTx (porcine islets transplanted under the renal capsule); and 3D bioprint (3D-bioprinted pancreatic petals with islets transplanted under the skin, on dorsal muscles). Glucose, C-peptide concentrations, and histological analyses were performed. In the obtained results, significantly lower mean fasting glucose levels (mg/dL) were observed both in a 3D-bioprint group and in a group with islets transplanted under the renal capsule when compared with untreated animals. Differences were observed in all control points: 7th, 14th, and 28th days post-transplantation (129, 119, 118 vs. 140, 139, 140; p < 0.001). Glucose levels were lower on the 14th and 28th days in a group with bioprinted petals compared to the group with islets transplanted under the renal capsule. Immunohistochemical staining indicated the presence of secreted insulin-living pancreatic islets and neovascularization within 3D-bioprinted pancreatic petals after transplantation. In conclusion, bioprinted bionic petals significantly lowered plasma glucose concentration in studied model species.

Dynamic properties of glucose complexity during the course of critical illness: a pilot study

Methods to control the blood glucose (BG) levels of patients in intensive care units (ICU) improve the outcomes. The development of continuous BG levels monitoring devices has also permitted to optimize these processes. Recently it was shown that a complexity loss of the BG signal is linked to poor clinical outcomes. Thus, it becomes essential to decipher this relation to design efficient BG level control methods. In previous studies the BG signal complexity was calculated as a single index for the whole ICU stay. Although, these approaches did not grasp the potential variability of the BG signal complexity. Therefore, we setup this pilot study using a continuous monitoring of central venous BG levels in ten critically ill patients (EIRUS platform, Maquet Critical CARE AB, Solna, Sweden). Data were processed and the complexity was assessed by the detrended fluctuation analysis and multiscale entropy (MSE) methods. Finally, recordings were split into 24 h overlapping intervals and a MSE analysis was applied to each of them. The MSE analysis on time intervals revealed an entropy variation and allowed periodic BG signal complexity assessments. To highlight differences of MSE between each time interval we calculated the MSE complexity index defined as the area under the curve. This new approach could pave the way to future studies exploring new strategies aimed at restoring blood glucose complexity during the ICU stay.