Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients.

Objective: The co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major public health challenge. Although early detection and intervention can prevent or slow down the progression, the commonly used estimated glomerular filtration rate (eGFR) based on serum creatinine may be influenced by factors unrelated to kidney function. Therefore, there is a need to identify novel biomarkers that can more accurately assess renal function in T2D patients.

The association between plasma free amino acids and type 2 diabetes mellitus complicated with infection in Chinese patients.

Background: Type 2 diabetes mellitus (T2DM), one of the most common public diseases threatening human health, is always accompanied by infection. Though there are still a variety of flaws in the treatment of some infectious diseases, metabolomics provides a fresh perspective to explore the relationship between T2DM and infection. Our research aimed to investigate the association between plasma free amino acids (PFAAs) and T2DM complicated with infection in Chinese patients.

A Metabolism-Based Interpretable Machine Learning Prediction Model for Diabetic Retinopathy Risk: A Cross-Sectional Study in Chinese Patients with Type 2 Diabetes.

The burden of diabetic retinopathy (DR) is increasing, and the sensitive biomarkers of the disease were not enough. Studies have found that the metabolic profile, such as amino acid (AA) and acylcarnitine (AcylCN), in the early stages of DR patients might have changed, indicating the potential of metabolites to become new biomarkers. We are amid to construct a metabolite-based prediction model for DR risk.

The Association of Homocysteine and Diabetic Retinopathy in Homocysteine Cycle in Chinese Patients With Type 2 Diabetes.

Objective: This study aimed to explore the relationship between homocysteine (Hcy) and diabetic retinopathy (DR) and the impacts of the Hcy pathway on this relationship against this background.

Methods: This study retrieved 1979 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University in Jinzhou, Liaoning Province, China. Multiple logistic regression was used to analyze the effects of Hcy cycle on the relationship between Hcy and DR.

Identification of four differentially methylated genes as prognostic signatures for stage I lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the main subtype of non-small cell lung cancer with a low survival prognosis. We aimed to generate a prognostic model for the postoperative recurrence of LUAD.

Methods: The methylated DNA data of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA).

Association between XRCC1 polymorphisms and glioma risk among Chinese population.

The pathogenesis of glioma remains largely unknown now. It has been suggested that the X-ray cross-complementing group 1 (XRCC1) gene may influence the capacity to repair DNA damage leading to an increased gliomas susceptibility. This study aimed to evaluate the relationship between XRCC1 polymorphisms and glioma risk.

Use of a transanal drainage tube for prevention of anastomotic leakage and bleeding after anterior resection for rectal cancer.

Background: The aim of the present study was to investigate the usefulness of the transanal drainage tube for prevention of anastomotic leakage and bleeding after anterior resection for rectal cancer.

Methods: Between January 2007 and May 2011 a nonrandomized prospective study of patients undergoing anterior resection for rectal cancer was done. The patients were divided into the transanal drainage tube (TDT) and non-transanal drainage tube (NTDT) groups according to whether the transanal drainage tube was used in the operation.