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Background Diabetic nephropathy (DN) and diabetic retinopathy (DR) are common microvascular complications of diabetes. The purpose of this study was to investigate the correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 DN and to determine the capacity of retinal vascular geometric parameters in differentiating DN from non-diabetic renal disease (NDRD). Methods The study participants were adult patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease who underwent a renal biopsy. Univariate and multivariable regression analyses were performed to evaluate associations between retinal vessel geometry parameters and pathologically diagnosed DN. Multivariate binary logistic regression analyses were performed to establish a differential diagnostic model for DN. Results In total, 403 patients were examined in this cross-sectional study, including 152 (37.7%) with DN, 157 (39.0%) with NDRD and 94 (23.3%) with DN combined with NDRD. After univariate logistic regression, total vessel fractal dimension, arteriolar fractal dimension and venular fractal dimension were all found to be associated with DN. In multivariate analyses adjusting for age, sex, blood pressure, diabetes, DR and other factors, smaller retinal vascular fractal dimensions were significantly associated with DN (P  < .05). We developed a differential diagnostic model for DN combining traditional clinical indicators and retinal vascular geometric parameters. The area under the curve of the model established by multivariate logistic regression was 0.930. Conclusions Retinal vessel fractal dimension is of great significance for the rapid and non-invasive differentiation of DN. Incorporating retinal vessel fractal dimension into the diagnostic model for DN and NDRD can improve the diagnostic efficiency. [ABSTRACT FROM AUTHOR]

The total area of the Earth's oceans is 360 million square kilometers, accounting for approximately 71% of the Earth's surface area. It is a huge treasure trove of resources, containing abundant mineral resources, oil and gas resources, microbial resources, etc. The production of marine biomass is enormous, and as a third-generation renewable energy source, it has more sustainable development potential than terrestrial biomass. The main source of marine biomass is marine algae, so the development and excavation of marine algae resources is imperative. At present, alginate has become the second largest sustainable development resource in terms of production, second only to cellulose, and has enormous application value. The biological enzyme method for degrading alginate utilizes alginate lyase to β The elimination mechanism breaks the glycosidic bond, which has more degradation advantages than physical and chemical methods.

The hyperdispersant SSS-MPEGA-MA (SMM) is prepared through aqueous polymerization using sodium p-styrenesulfonate (SSS), polyethylene glycol monomethyl ether acrylate (MPEGA) and maleic anhydride (MA) as monomers for dispersing phase change microcapsules (PCM). It is also concluded that the best dispersion effect is achieved when the starting concentration of SMM dispersant in aqueous solution with a solid content of phase change microcapsules of 20% occupies 2% of PCM content. The phase change microcapsules are added to a waterborne varnish with a solid content of 20%, and after adding a certain mass of SMM dispersant dropwise, phase change performance is still found on the film, which is the best with a dispersant concentration of 2%. At the same time, the hyperdispersant SMM can make the phase change microcapsules evenly distributed on the water-based varnish, and the dispersion effect is good without affecting the properties of the paint film itself. [ABSTRACT FROM AUTHOR]