Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus.

BACKGROUND: The cardiometabolic index (CMI) is a new metric derived from the triglyceride-glucose index and body mass index and is considered a potential marker for cardiovascular risk assessment. This study aimed to examine the correlation between the CMI and the presence and severity of arteriosclerosis in patients with type 2 diabetes mellitus (T2DM). METHODS: This study involved 2243 patients with T2DM. The CMI was derived by dividing the triglyceride level (mmol/L) by the high-density lipoprotein level (mmol/L) and then multiplying the quotient by the waist-to-height ratio. Multivariate logistic regression was used to analyze the correlations between the CMI and BMI blood biomarkers, blood pressure, and brachial-ankle pulse wave velocity (baPWV). RESULTS: Patients were categorized into three groups based on their CMI: Group C1 (CMI < 0.775; n = 750), Group C2 (CMI: 0.775-1.355; n = 743), and Group C3 (CMI > 1.355; n = 750). Increased BMI, fasting glucose, insulin (at 120 min), total cholesterol (TC), and baPWV values were observed in Groups C2 and C3, with statistically significant trends (all trends P < 0.05). The CMI was positively correlated with systolic blood pressure (r = 0.74, P < 0.001). Multivariate analysis revealed that an increased CMI contributed to a greater risk for arteriosclerosis (OR = 1.87, 95%CI: 1.66-2.10, P < 0.001). Compared to the C1 group, the C2 group and C3 group had a greater risk of developing arteriosclerosis, with ORs of 4.55 (95%CI: 3.57-5.81, P<0.001) and 5.56 (95%CI: 4.32-7.17, P<0.001), respectively. The association was notably stronger in patients with a BMI below 21.62 kg/m² than in those with a BMI of 21.62 kg/m² or higher (OR = 4.53 vs. OR = 1.59). CONCLUSIONS: These findings suggest that the CMI is a relevant and independent marker of arteriosclerosis in patients with T2DM and may be useful in the risk stratification and management of these patients.

Discrimination of Single Living Rat Pancreatic α, ß, δ, and Pancreatic Polypeptide (PP) Cells Using Raman Spectroscopy.

Primary pancreatic α, ß, δ, and pancreatic polypeptide (PP) cells are reliable cell models for diabetes research. However, the separation and purification of these cells in living conditions remains an obstacle for researchers. The interaction of visible light with cellular molecules can produce Raman scattering, which can be analyzed to obtain cellular intrinsic molecular fingerprints. It has been speculated that primary pancreatic α, ß, δ, and PP cells can be identified and separated from each other according to their spectral differences. To test this hypothesis, Raman spectra detection was performed on rat islet cells. Single islet cells identified by Raman scattering under living conditions were verified using immunohistochemistry. Thus, Raman data were acquired from a pure line of islet cells as a training sample and then used to establish the discriminant function. Then, using the principal component analysis-linear discriminate analysis (PCA-LDA) method, the four types of islet cells could be identified and discriminated by Raman spectroscopy. This study provides a label-free and noninvasive method for discriminating islet cell types in a randomly distributed mixed islet cell population via their physical properties rather than by using antibodies or fluorescence labeling.

Real-Time, Label-Free Detection of Local Exocytosis Outside Pancreatic ß Cells Using Laser Tweezers Raman Spectroscopy.

The examination of insulin (Ins) exocytosis at the single-cell level by conventional methods, such as electrophysiological approaches, total internal reflection imaging, and two-photon imaging technology, often requires an invasive microelectrode puncture or label. In this study, high concentrations of glucose and potassium chloride were used to stimulate ß cell Ins exocytosis, while low concentrations of glucose and calcium channel blockers served as the blank and negative control, respectively. Laser tweezers Raman spectroscopy (LTRS) was used to capture the possible Raman scattering signal from a local zone outside of the cell edge. The results show that the frequencies of the strong signals from the local zones outside the cellular edge in the stimulated groups are greater than those of the control. The Raman spectra from the cellular edge, Ins and cell membrane were compared. Thus, local Ins exocytosis activity outside pancreatic ß cells might be observed indirectly using LTRS, a non-invasive optical method.

Different Raman spectral patterns of primary rat pancreatic ß cells and insulinoma cells.

As a noninvasive and label-free analytical technique, Raman spectroscopy has been widely used to study the difference between malignant cells and normal cells. Insulinomas are functional ß-cell tumors of pancreatic islet cells. They exhibit many structural and immunohistochemical features in common with normal pancreatic ß cells; thus, they are typically difficult to distinguish under the microscope, especially in vivo. We investigated insulinoma and primary rat pancreatic ß-cell populations using Raman spectroscopy. The details of the optical heterogeneity between these two populations were determined based on different Raman regions primarily involving nucleic acid and protein contents, which are the most distinct cellular contents in these two types of cells. Using principal component analysis­linear discriminant analysis, these two cell types can be readily separated. The results of this work indicate that Raman spectroscopy is a promising tool for the noninvasive and label-free differentiation of insulinoma cells and normal pancreatic ß cells.