Efficacy of metformin combined with liraglutide on the glucose and lipid metabolism, vascular endothelial function, and oxidative stress of patients with T2DM and metabolic syndrome.

Objective: This study evaluates the impact of metformin combined with liraglutide on the glucose and lipid metabolism, oxidative stress, and vascular endothelium of patients with type-2 diabetes mellitus (T2DM) and metabolic syndrome. Methods: Medical records of 78 patients with T2DM and metabolic syndrome, admitted to Caoxian People's Hospital from July 2021 to July 2022, were retrospectively analysed. Thirty five patients were treated with metformin (control group), and 43 patients were treated with metformin combined with liraglutide (observation group). Indexes of glucose and lipid metabolism, function of vascular endothelium and the oxidative stress of both groups were compared before and after the treatment. Results: There was a significant decrease in the levels of fasting plasma glucose (FPG), Glycosylated Hemoglobin A1c (HbA1c), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP) and waist circumference in both groups three months after the treatment, These indexes were significantly lower in the observation group compared to the control group (P<0.05). High-density lipoprotein cholesterol (HDL-C) levels were higher in the observation group (P<0.05). There was a significant improvement in the levels of nitric oxide (NO), endothelin-1 (ET-1), superoxide dismutase (SOD), and malondialdehyde (MDA) after the treatment, and these indexes were markedly better in the observation group compared to the control group (P<0.05). Conclusions: Metformin combined with liraglutide treatment is associated with better outcomes than metformin alone in patients with T2DM and metabolic syndrome. Combined treatment results in improved glucose and lipid metabolism, vascular endothelial function, and oxidative stress index values.

Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process.

The neuropsychological characteristics inside the brain are still not sufficiently understood in previous Gestalt psychological analyses. In particular, the extraction and analysis of human brain consciousness information itself have not received enough attention for the time being. In this paper, we aim to investigate the features of EEG signals from different conscious thoughts. Specifically, we try to extract the physiologically meaningful features of the brain responding to different contours and shapes in images in Gestalt cognitive tests by combining persistent homology analysis with electroencephalogram (EEG). The experimental results show that more brain regions in the frontal lobe are involved when the subject perceives the random and disordered combination of images compared to the ordered Gestalt images. Meanwhile, the persistence entropy of EEG data evoked by random sequence diagram (RSD) is significantly different from that evoked by the ordered Gestalt (GST) images in several frequency bands, which indicate that the human cognition of the shape and contour of images can be separated to some extent through topological analysis. This implies the feasibility to digitize the neural signals while preserving the whole and local features of the original signals, which are further verified by our extensive experiments. In general, this paper evaluates and quantifies cognitively related neural correlates by persistent homology features of EEG signals, which provides an approach to realizing the digitization of neural signals. Preliminary verification of the analyzability of human consciousness signals provides reliable research ideas and directions for the realization of feature extraction and analysis of human brain consciousness cognition.