Low hemoglobin, even within the normal range, is associated with diabetic kidney disease.

Aim: To investigate the association between hemoglobin (Hb) levels and incident diabetic kidney disease (DKD) in patients with type 2 diabetes.

Methods: This retrospective cohort study included 1,657 patients with diabetes, without DKD at baseline, recruited from six clinics affiliated with Lee's United Clinic in Taiwan. Demographic data and laboratory results were collected and analyzed.

Moderate resistance training reduces intermuscular adipose tissue and risk factors of atherosclerotic cardiovascular disease for elderly patients with type 2 diabetes.

Aim: This study aimed to assess the impact of moderate resistance training on intermuscular adipose tissue (IMAT) in elderly patients with type 2 diabetes and the independent effect of IMAT reduction on metabolic outcomes.

Methods: In this randomized controlled trial, 85 patients with type 2 diabetes were assigned to either the resistance training group (42 participants) or the control group (43 participants) for a 6-month intervention. The primary outcome was changes in IMAT measured by computed tomography scan and magnetic resonance imaging using the interactive decomposition of water and fat with echo asymmetry and least squares qualification sequence.

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

Backgruound: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing.

Remodeling cancer stemness by collagen/fibronectin the AKT and CDC42 signaling pathway crosstalk in glioma.

Cancer development is a complex set of proliferative progression, which arises in most cases via multistep pathways associated with various factors, including the tumor microenvironment and extracellular matrix. However, the underlying mechanisms of cancer development remain unclear and this study aimed to explore the role of extracellular matrix in glioma progression. The expression of type I collagen and fibronectin in tumor tissues from glioma patients was examined by immunofluorescence staining.