New Digital Health Technologies for Insulin Initiation and Optimization for People With Type 2 Diabetes

ObjectiveThe health and economic burden of type 2 diabetes is of global significance. Many people with type 2 diabetes eventually need insulin to help reduce their risk of serious associated complications. However, barriers to the initiation and/or optimization of insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigated how new and future technologies may provide opportunities to help overcome these barriers to the initiation and/or optimization of insulin.MethodsA focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support the initiation and/or optimization of insulin were identified by manually filtering >300 publications and conference abstracts.ResultsMost software tools have been developed for smartphone platforms. At present, published data suggest that the use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care, with additional benefits such as reduced time burden and improved knowledge of diabetes among health care providers. However, there remains paucity of good-quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin.ConclusionNew digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, and titration advice as well as records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve adherence to titration and treatment, resulting in better outcomes for people with diabetes.     

SERS-based sensor for direct L-selectin level determination in plasma samples as alternative method of tumor detection

Selectin ligands are present on the surface of tumor cells, for this reason lowering the L-selectin level in the blood and lymph can indicate presence of the tumor. Therefore the selectin level in the plasma are potential targets for anticancer therapy. We demonstrate the surface enhanced Raman spectroscopy (SERS)-based sensor for the determination of L-selectin level in biological samples that can be used in medical diagnosis. The combination of SERS with the method of multivariate analysis as principle component analysis (PCA) allows to strengthen the presented data analysis. The loadings of PCA permit to indicate those vibration modes, that are the most important for the assumed identification (bands at 1574, 1450, 1292 cm⁻¹). Two bands at 1286 and 1580 cm⁻¹ were selected for the determination of the calibration curve (bands intensities I₁₂₈₆/I₁₅₈₀ ratio). The L-selectin level of biological samples can be read, directly from the calibration curve. The presented sensor is as a sensitive tool with good specificity and selectivity of L-selectin, even in the case of coexistence of P- and E-selectin.