Integration of Vitreous Lipidomics and Metabolomics for Comprehensive Understanding of the Pathogenesis of Proliferative Diabetic Retinopathy.

As a vision-threatening complication of diabetes mellitus (DM), proliferative diabetic retinopathy (PDR) is associated with sustained metabolic disorders. Herein, we collected the vitreous cavity fluid of 49 patients with PDR and 23 control subjects without DM for metabolomics and lipidomics analyses. Multivariate statistical methods were performed to explore relationships between samples. For each group of metabolites, gene set variation analysis scores were generated, and we constructed a lipid network by using weighted gene co-expression network analysis. The association between lipid co-expression modules and metabolite set scores was investigated using the two-way orthogonal partial least squares (O2PLS) model. A total of 390 lipids and 314 metabolites were identified. Multivariate statistical analysis revealed significant vitreous metabolic and lipid differences between PDR and controls. Pathway analysis showed that 8 metabolic processes might be associated with the development of PDR, and 14 lipid species were found to be altered in PDR patients. Combining metabolomics and lipidomics, we identified fatty acid desaturase 2 (FADS2) as an important potential contributor to the pathogenesis of PDR. Collectively, this study integrates vitreous metabolomics and lipidomics to comprehensively unravel metabolic dysregulation and identifies genetic variants associated with altered lipid species in the mechanistic pathways for PDR.

Rapid Detection and Differentiation of Legionella pneumophila and Non-Legionella pneumophila Species by Using Recombinase Polymerase Amplification Combined With EuNPs-Based Lateral Flow Immunochromatography.

Legionella, a waterborne pathogen, is the main cause of Legionnaires' disease. Therefore, timely and accurate detection and differentiation of Legionella pneumophila and non-Legionella pneumophila species is crucial. In this study, we develop an easy and rapid recombinase polymerase amplification assay combined with EuNPs-based lateral flow immunochromatography (EuNPs-LFIC-RPA) to specifically distinguish Legionella pneumophila and non-Legionella pneumophila. We designed primers based on the mip gene of Legionella pneumophila and the 5S rRNA gene of non-Legionella pneumophila. The recombinase polymerase amplification reaction could go to completion in 10 min at 37°C, and the amplification products could be detected within 5 min with EuNPs-LFIC strips. Using a florescent test strip reader, the quantitative results were achieved by reading the colored signal intensities on the strips. The sensitivity was 1.6 × 101 CFU/ml, and a linear standard linear curve plotted from the test strip reader had a correlation coefficient for the determination of Legionella pneumophila (R 2 = 0.9516). Completed concordance for the presence or absence of Legionella pneumophila by EuNPs-LFIC-RPA and qPCR was 97.32% (κ = 0.79, 95% CI), according to an analysis of practical water samples (n = 112). In short, this work shows the feasibility of EuNPs-LFIC-RPA for efficient and rapid monitoring of Legionella pneumophila and non-Legionella pneumophila in water samples.