Insulin, which is a hormone produced by the β-cells of the pancreas, regulates the glucose levels in the blood and can transport glucose into cells to produce glycogen or triglycerides. Insulin deficiency can lead to hyperglycemia and diabetes. Therefore, insulin detection is critical in clinical diagnosis. In this study, disposable Au electrodes were modified with copper(II) benzene-1,3,5-tricarboxylate (Cu-BTC)/leaf-like zeolitic imidazolate framework (ZIF-L) for insulin detection. The aptamers are easily immobilized on the Cu-BTC/ZIF-L composite by physical adsorption and facilitated the specific interaction between aptamers and insulin. The Cu-BTC/ZIF-L composite-based aptasensor presented a wide linear insulin detection range (0.1 pM to 5 μM) and a low limit of detection of 0.027 pM. In addition, the aptasensor displayed high specificity, good reproducibility and stability, and favorable practicability in human serum samples. For the in vivo tests, Cu-BTC/ZIF-L composite-modified electrodes were implanted in non-diabetic and diabetic mice, and insulin was quantified using electrochemical and enzyme-linked immunosorbent assay methods.
Objective: People with higher level of diabetes distress (DD) may have difficulty in managing their diabetes and possible higher A1c. In order to provide proper psychosocial care, we designed this study to understand the DD of participants in a diabetes clinic.
Methods: The study was a cross-sectional design conducted in a diabetes clinic in Taiwan. Diabetes distress (DD) was assessed by Diabetes Distress Scale and accompanied by a semi-structured interview to collect qualitative information. DD includes 4 dimensions which are emotional burden (EB), interpersonal (IP), physician related (PR) and regimen-related (RR) distress. The correlation analysis was conducted to portray the relationships between DD and sociodemographic variables. Emotional state using Hospital Anxiety and Depression Scale, quality of life using WHO Quality of Life-BREF, and HbA1C levels were also gathered as the dependent variables in regression models to understand how DD related to the adaptive index in people with diabetes.
Results: There were 71 (37 M and 34 F, 64 T2D and 7 T1D, 27 insulin treated) participants and mean age 51.6 ± 14.5 yrs. According to correlation analysis, age (r = -.30, p = .011) and taking insulin (r = .33, p = .005) were associated with the level of DD. Female participants had a higher level of EB (r = .26, p = .031) and IP distress (r = .29, p = .014). In the regression model with single independent variable, mean DD (β = .29, p = .016) and RR (β = .24, p = .040) was related to the level of HbA1C respectively, but they were not significant after entering control variables of taking insulin and new patients. Mean DD and EB distress were significant association with quality of life, the symptoms of depression and anxiety in the regression models.
Conclusions: Younger people and using insulin were associated with higher level of DD. The mean score of DD and RR dimension were also associated with the levels of A1c, however, using insulin and new patients might have a stronger association with the levels of A1c.
Disclosure
K. Chen: None. H. Chen: None. C. Hung: None. J. Hwang: None. Y. Chuang: None. Z. Chen: None.
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