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Abstract Background Diabetic nephropathy (DN) is one of the serious microvascular complications of diabetes mellitus (DM). A growing body of research has demonstrated that the inflammatory state plays a critical role in the incidence and development of DN. Pyroptosis is a new way of programmed cell death, which has the particularity of natural immune inflammation. The inhibition of inflammatory cytokine expression and regulation of pathways related to pyroptosis may be a novel strategy for DN treatment. The aim of this study is to identify pyroptosis-related genes and potential drugs for DN. Methods DN differentially expressed pyroptosis-related genes were identified via bioinformatic analysis Gene Expression Omnibus (GEO) dataset GSE96804. Dataset GSE30528 and GSE142025 were downloaded to verify pyroptosis-related differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a pyroptosis-related gene predictive model. A consensus clustering analysis was performed to identify pyroptosis-related DN subtypes. Subsequently, Gene Set Variation Analysis (GSVA), Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the differences between DN clusters. A protein–protein interaction (PPI) network was used to select hub genes and DGIdb database was utilized to screen potential therapeutic drugs/compounds targeting hub genes. Results A total of 24 differentially expressed pyroptosis-related genes were identified in DN. A 16 gene predictive model was conducted via LASSO regression analysis. According to the expression level of these 16 genes, DN cases were divided into two subtypes, and the subtypes are mainly associated with inflammation, activation of immune response and cell metabolism. In addition, we identified 10 hub genes among these subtypes, and predicted 65 potential DN therapeutics that target key genes. Conclusion We identified two pyroptosis-related DN clusters and 65 potential therapeutical agents/compounds for DN, which might shed a light on the treatment of DN.

In this study, an exopolysaccharide (EPS)-producing strain of Lactiplantibacillus plantarum HDC-01 was isolated from sauerkraut, and the structure, properties and biological activity of the studied EPS were assessed. The molecular weight of the isolated EPS is 2.505 × 106 Da. Fourier transform infrared spectrometry (FT-IR) and nuclear magnetic resonance (NMR) results showed that the EPS was composed of glucose/glucopyranose subunits linked by an α-(1 → 6) glycosidic bond and contained an α-(1 → 3) branching structure. X-ray diffraction (XRD) analysis revealed the amorphous nature of the EPS. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) showed that the isolated EPS had a smooth and compact surface with several protrusions of varying lengths and irregularly shaped material. Moreover, the studied EPS showed good thermal stability, water holding capacity, and milk coagulation ability and promoted the growth of probiotics. L. plantarum EPS may be used as prebiotics in the fields of food and medicine.

A fundamental bottleneck in text-to-image synthesis is that there are rarely subjective quality evaluation metrics for a single generated image. To address this issue, this paper proposed a procedure to evaluate the single generated image, which includes a specific dataset named multiple metrics quality assessment for birds(MMQA Birds) and a learning model named blind generated image evaluator(BGIE). The motivation of our proposal is twofold. On the one hand, subjective image quality evaluation is a human perceptual task; Therefore, it tends to be a process of supervised learning. To the best of our knowledge, there are not any datasets for this study. Thus, we handle this problem via designing a specific dataset. On the other hand, we observed that the spatial content of generated image attracts more attention when humans judge its quality; According to this finding, an efficient machine-learning model that combines both pixel-level features and spatial features is proposed. Extensive experiments manifest our method can solve this problem to some extent. In the generated image dataset, BGIE surpasses the state-of-art NSS-based method by 6.3% in PLCC and SRCC. In practice, we further discuss the rationality of the MMQA Birds dataset and the application of BGIE. It proves that both in subjective and objective aspects, our method achieves convincing results.

Abstract Background ω-3 polyunsaturated fatty acids (PUFAs) are synthesized from α-Linolenic acid (ALA, C18:3ω3) and play important roles in anti-inflammatory and antioxidant responses in mammal cells. ALA is an essential fatty acid which cannot be produced within the human body and must be acquired through diet. The purpose of this study was to evaluate the potential of a novel microalgal strain (HDMA-20) as a source of ω-3 PUFAs including ALA and eicosatetraenoic acid (ETA, C20:4ω3). Method Phylogenetic Neighbor-Joining analysis based on 18S ribosomal DNA sequence was used to identify the microalga strain HDMA-20. Autotrophic condition was chosen to cultivate HDMA-20 to reduce the cultivation cost. GC-MS was used to determine the fatty acid composition of HDMA-20 lipid. Results A microalgal strain (HDMA-20) from Lake Chengfeng (Daqing, Heilongjiang province, China) was found to accumulate high content of ω-3 PUFAs (63.4% of total lipid), with ALA and eicosatetraenoic acid (ETA, C20:4ω3) accounting for 35.4 and 9.6% of total lipid, respectively. Phylogenetic analysis based on 18S ribosomal DNA sequences suggested that the HDMA-20 belonged to genus Monoraphidium (Selenastraceae, Sphaeropleales) and its 18S rDNA sequence information turned out to be new molecular record of Monoraphidium species. The biomass productivity and lipid content of HDMA-20 were also investigated under autotrophic condition. The biomass productivity of HDMA-20 reached 36.3 mg L− 1 day− 1, and the lipid contents was 22.6% of dry weight. Conclusion HDMA-20 not only represent an additional source of ALA, but also a totally new source of ETA. The high content of ω-3 PUFAs, especially ALA, of HDMA-20, makes it suitable as a source of nutrition supplements for human health. In addition, HDMA-20 exhibited good properties in growth and lipid accumulation, implying its potential for cost-effective ω-3 PUFAs production in future.