Symptoms of depression, perceived social support, and medical coping modes among middle-aged and elderly patients with type 2 diabetes

Objective: To understand the prevalence of depression in diabetes population, explore the relationship between diabetes and depression, and the impact of comprehensive psychological and behavioral intervention on depression related to diabetes and glucose metabolism.Methods: 71 middle-aged and elderly patients with type 2 diabetes were investigated and evaluated with Self Rating Depression Scale (SDS), Medical Coping Scale (MCWQ) and Social Support Scale (PSSS). Patients who met the research criteria were randomly divided into an experimental group and a control group. The number of effective cases in the two groups was 36 and 35 respectively. In addition to conventional diabetes drug treatment, the experimental group was supplemented with comprehensive psychological and behavioral intervention, while the control group was only given conventional treatment. The fasting blood glucose, 2-h postprandial blood glucose, body weight and depression index were measured before and after treatment in the two groups.Results: The prevalence of depression in patients with diabetes was as high as 60%, and that in the elderly control group was 5%; In type 2 diabetes population, depression is negatively related to the total score of social support and medical coping surface, and positively related to avoidance, blood sugar, women, course of disease, education level below junior high school, body mass index, and number of complications in medical coping; The fasting blood glucose, 2-h postprandial blood glucose, body mass index, and depression index of the two groups decreased, and the range and speed of decline in the experimental group were higher than those in the control group; There were significant differences between the two groups in fasting blood glucose, 2-h postprandial blood glucose and depression index; During the follow-up period, the blood glucose and depression index of the experimental group increased.Conclusion: Depression has a high prevalence rate in middle-aged and elderly people with type 2 diabetes, and has a negative impact on blood sugar control in diabetes patients; Psychological and behavioral comprehensive intervention can improve the glucose metabolism and depressive symptoms of middle-aged and elderly patients with type 2 diabetes

Efficacy of polyethylene glycol loxenatide versus insulin glargine on glycemic control in patients with type 2 diabetes: a randomized, open-label, parallel-group trial

Objective: This trial aimed to evaluate the glycemic control of polyethylene glycol loxenatide measured with continuous glucose monitoring (CGM) in patients with type 2 diabetes mellitus (T2DM), with the hypothesis that participants given PEG-Loxe would spend more time in time-in-range (TIR) than participants were given insulin glargine after 24 weeks of treatment.Methods: This 24-week, randomized, open-label, parallel-group study was conducted in the Department of Endocrine and Metabolic Diseases, Longhu Hospital, Shantou, China. Participants with T2DM, who were ≥45 years of age, HbA1c of 7.0%–11.0%, and treated at least 3 months with metformin were randomized (1:1) to receive PEG-Loxe or insulin glargine. The primary endpoint was TIR (blood glucose range: 3.9–10.0 mmol/L) during the last 2 weeks of treatment (weeks 22–24).Results: From March 2020 to April 2022, a total of 107 participants with T2DM were screened, of whom 78 were enrolled into the trial (n = 39 per group). At the end of treatment (weeks 22–24), participants given PEG-Loxe had a greater proportion of time in TIR compared with participants given insulin glargine [estimated treatment difference (ETD) of 13.4% (95% CI, 6.8 to 20.0, p < 0.001)]. The tight TIR (3.9–7.8 mmol/L) was greater with PEG-Loxe versus insulin glargine, with an ETD of 15.6% (95% CI, 8.9 to 22.4, p < 0.001). The time above range (TAR) was significantly lower with PEG-Loxe versus insulin glargine [ETD for level 1: −10.5% (95% CI: −14.9 to −6.0), p < 0.001; ETD for level 2: −4.7% (95% CI: −7.9 to −1.5), p = 0.004]. The time below range (TBR) was similar between the two groups. The mean glucose was lower with PEG-Loxe versus insulin glargine, with an ETD of −1.2 mmol/L (95% CI, −1.9 to −0.5, p = 0.001). The SD of CGM glucose levels was 1.88 mmol/L for PEG-Loxe and 2.22 mmol/L for insulin glargine [ETD -0.34 mmol/L (95% CI: −0.55 to −0.12), p = 0.002], with a similar CV between the two groups.Conclusion: The addition of once-weekly GLP-1RA PEG-Loxe to metformin was superior to insulin glargine in improving glycemic control and glycemic variability evaluated by CGM in middle-aged and elderly patients with T2DM

Epigenome-Wide Histone Acetylation Changes in Peripheral Blood Mononuclear Cells in Patients with Type 2 Diabetes and Atherosclerotic Disease

There is emerging evidence of an association between epigenetic modifications, glycemic control and atherosclerosis risk. In this study, we mapped genome-wide epigenetic changes in patients with type 2 diabetes (T2D) and advanced atherosclerotic disease. We performed chromatin immunoprecipitation sequencing (ChIP-seq) using a histone 3 lysine 9 acetylation (H3K9ac) mark in peripheral blood mononuclear cells from patients with atherosclerosis with T2D (n = 8) or without T2D (ND, n = 10). We mapped epigenome changes and identified 23,394 and 13,133 peaks in ND and T2D individuals, respectively. Out of all the peaks, 753 domains near the transcription start site (TSS) were unique to T2D. We found that T2D in atherosclerosis leads to an H3K9ac increase in 118, and loss in 63 genomic regions. Furthermore, we discovered an association between the genomic locations of significant H3K9ac changes with genetic variants identified in previous T2D GWAS. The transcription factor 7-like 2 (TCF7L2) rs7903146, together with several human leukocyte antigen (HLA) variants, were among the domains with the most dramatic changes of H3K9ac enrichments. Pathway analysis revealed multiple activated pathways involved in immunity, including type 1 diabetes. Our results present novel evidence on the interaction between genetics and epigenetics, as well as epigenetic changes related to immunity in patients with T2D and advanced atherosclerotic disease.Peer reviewe

Carbon benefits of wolfberry plantation on secondary saline land in Jingtai oasis, Gansu:A case study on application of the CBP model

The largest global source of anthropogenic CO2 emissions comes from the burning of fossil fuel and approximately 30% of total net emissions come from land use and land use change. Forestation and reforestation are regarded worldwide as effective options of sequestering carbon to mitigate climate change with relatively low costs compared with industrial greenhouse gas (GHG) emission reduction efforts. Cash trees with a steady augmentation in size are recognized as a multiple-beneficial solution to climate change in China. The reporting of C changes and GHG emissions for sustainable land management (SLM) practices such as afforestation is required for a variety of reasons, such as devising land management options and making policy. The Carbon Benefit Project (CBP) Simple Assessment Tool was employed to estimate changes in soil organic carbon (SOC) stocks and GHG emissions for wolfberry (Lycium barbarum L.) planting on secondary salinized land over a 10 year period (2004–2014) in the Jingtai oasis in Gansu with salinized barren land as baseline scenario. Results show that wolfberry plantation, an intensively managed ecosystem, served as a carbon sink with a large potential for climate change mitigation, a restorative practice for saline land and income stream generator for farmers in soil salinized regions in Gansu province. However, an increase in wolfberry production, driven by economic demands, would bring environmental pressures associated with the use of N fertilizer and irrigation. With an understanding of all of the components of an ecosystem and their interconnections using the Drivers-Pressures-State-Impact-Response (DPSIR) framework there comes a need for strategies to respond to them such as capacity building, judicious irrigation and institutional strengthening. Cost benefit analysis (CBA) suggests that wolfberry cultivation was economically profitable and socially beneficial and thus well-accepted locally in the context of carbon sequestration. This study has important implications for Gansu as it helps to understand the role cash trees can play in carbon emission reductions. Such information is necessary in devising management options for sustainable land management (SLM)

interactive image completion with perspective constraint

In this paper, we present a portable interactive system for image completion with perspective constraint. Image completion arises in many image filling and editing problems, but it is seldom applied in the scenario regarding to the features of perspective. In our system, basic perspective information can be obtained through user interaction in 2D on a single image, simply through picking up a few points on the image. We propose a constraint method, by building up a perspective mesh, to convey perspective structure in the whole workflow. Instead of using the common approaches in image completion, image inpainting and texture synthesis, we employ image warping to fulfill the filling process. The method is proven to be more rational for generating better visual result. Our image completion technique is portable, user-friendly and can be used to achieve good visual consistency in the perspective constrained filling tasks. We demonstrate the validity of our method by various images and applications. © 2012 ACM.ACM SIGGRAPHIn this paper, we present a portable interactive system for image completion with perspective constraint. Image completion arises in many image filling and editing problems, but it is seldom applied in the scenario regarding to the features of perspective. In our system, basic perspective information can be obtained through user interaction in 2D on a single image, simply through picking up a few points on the image. We propose a constraint method, by building up a perspective mesh, to convey perspective structure in the whole workflow. Instead of using the common approaches in image completion, image inpainting and texture synthesis, we employ image warping to fulfill the filling process. The method is proven to be more rational for generating better visual result. Our image completion technique is portable, user-friendly and can be used to achieve good visual consistency in the perspective constrained filling tasks. We demonstrate the validity of our method by various images and applications. © 2012 ACM

MHMDA : Human Microbe-Disease Association Prediction by Matrix Completion and Multi-Source Information

Microbes are vital in human health. It is helpful to promote diagnostic and treatment of human disease and drug development by identifying microbe-disease associations. However, knowledge in this area still needs to be further improved. In this paper, a new computational model using matrix completion to predict human microbe-disease associations (mHMDA, Fig. 1) is developed. First, we extract the disease feature by Gaussian kernel-based similarity and symptom-based similarity. Meanwhile, the microbe feature is computed by Gaussian kernel-based similarity. As treating potential association as the missing elements of a matrix, the matrix completion is adopted to get the potential microbe-disease associations. Leave-one-out cross-validation (LOOCV) is carried out which get the AUC (The area under ROC curve) of 0.928 showing the effectiveness of mHMDA. Furthermore, 5-fold CV get the AUCs of 0.8838 ± 0.0044 (mean ± standard deviation). Moreover, through the four case studies (asthma, inflammatory bowel disease (IBD), type 2 diabetes (T2D), and type 1 diabetes (T1D)), we find that nine, ten, nine, and eight of top-ten inferred microorganisms for the four diseases are previously verified by experiments. All these results indicate the effectiveness of mHMDA. mHMDA might be helpful to infer the disease-related microorganisms

A novel model for protein sequence similarity analysis based on spectral radius

Advances in sequencing technologies led to rapid increase in the number and diversity of biological sequences, which facilitated development in the sequence research. In this paper, we present a new method for analyzing protein sequence similarity. We calculated the spectral radii of 20 amino acids (AAs) and put forward a novel 2-D graphical representation of protein sequences. To characterize protein sequences numerically, three groups of features were extracted and related to statistical, dynamics measurements and fluctuation complexity of the sequences. With the obtained feature vector, two models utilizing Gaussian Kernel similarity and Cosine similarity were built to measure the similarity between sequences. We applied our method to analyze the similarities/dissimilarities of four data sets. Both proposed models received consistent results with improvements when compared to that obtained by the ClustalW analysis. The novel approach we present in this study may therefore benefit protein research in medical and scientific fields

PTPD : Predicting therapeutic peptides by deep learning and word2vec

Background In the search for therapeutic peptides for disease treatments, many efforts have been made to identify various functional peptides from large numbers of peptide sequence databases. In this paper, we propose an effective computational model that uses deep learning and word2vec to predict therapeutic peptides (PTPD).∗: Results Representation vectors of all k-mers were obtained through word2vec based on k-mer co-existence information. The original peptide sequences were then divided into k-mers using the windowing method. The peptide sequences were mapped to the input layer by the embedding vector obtained by word2vec. Three types of filters in the convolutional layers, as well as dropout and max-pooling operations, were applied to construct feature maps. These feature maps were concatenated into a fully connected dense layer, and rectified linear units (ReLU) and dropout operations were included to avoid over-fitting of PTPD. The classification probabilities were generated by a sigmoid function. PTPD was then validated using two datasets: an independent anticancer peptide dataset and a virulent protein dataset, on which it achieved accuracies of 96% and 94%, respectively.∗: Conclusions PTPD identified novel therapeutic peptides efficiently, and it is suitable for application as a useful tool in therapeutic peptide design