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Abstract The heterogeneity of hepatocellular carcinoma (HCC) poses a challenge for accurate prognosis prediction. DNA damage repair genes (DDRGs) have an impact on a wide range of malignancies. However, the relevance of these genes in HCC prognosis has received little attention. In this study, we aimed to develop a prognostic signature to identify novel therapy options for HCC. We acquired mRNA expression profiles and clinical data for HCC patients from The Cancer Genome Atlas (TCGA) database. A polygenic prognostic model for HCC was constructed using selection operator Cox analysis and least absolute shrinkage. The model was validated using International Cancer Genome Consortium (ICGC) data. Overall survival (OS) between the high-risk and low-risk groups was compared using Kaplan‒Meier analysis. Independent predictors of OS were identified through both univariate and multivariate Cox analyses. To determine immune cell infiltration scores and activity in immune-related pathways, a single-sample gene set enrichment analysis was performed. The protein and mRNA expression levels of the prognostic genes between HCC and normal liver tissues were also examined by immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real-time PCR (qRT-PCR). A novel ten-gene signature (CHD1L, HDAC1, KPNA2, MUTYH, PPP2R5B, NEIL3, POLR2L, RAD54B, RUVBL1 and SPP1) was established for HCC prognosis prediction. Patients in the high-risk group had worse OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the predictive ability of this prognostic gene signature. Multivariate Cox analysis showed that the risk score was an independent predictor of OS. Functional analysis revealed a strong association with cell cycle and antigen binding pathways, and the risk score was highly correlated with tumor grade, tumor stage, and types of immune infiltrate. High expression levels of the prognostic genes were significantly correlated with increased sensitivity of cancer cells to antitumor drugs. IHC, IF and qRT-PCR all indicated that the prognostic genes were highly expressed in HCC relative to normal liver tissue, consistent with the results of bioinformatics analysis. Ten DDRGs were utilized to create a new signature for identifying the immunological state of HCC and predicting prognosis. In addition, blocking these genes could represent a promising treatment.

Abstract Background Type 2 diabetes mellitus (T2DM), which has a high incidence and several harmful consequences, poses a severe danger to human health. Research on the function of ferroptosis in T2DM is increasing. This study uses bioinformatics techniques identify new diagnostic T2DM biomarkers associated with ferroptosis. Methods To identify ferroptosis‐related genes (FRGs) that are differentially expressed between T2DM patients and healthy individuals, we first obtained T2DM sequencing data and FRGs from the Gene Expression Omnibus (GEO) database and FerrDb database. Then, drug‐gene interaction networks and competitive endogenous RNA (ceRNA) networks linked to the marker genes were built after marker genes were filtered by two machine learning algorithms (LASSO and SVM‐RFE algorithms). Finally, to confirm the expression of marker genes, the GSE76895 dataset was utilized. The protein and RNA expression of some marker genes in T2DM and nondiabetic tissues was also examined by Western blotting, immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real‐time PCR (qRT‐PCR). Results We obtained 58 differentially expressed genes (DEGs) associated with ferroptosis. GO and KEGG enrichment analyses showed that these DEGs were significantly enriched in hypoxia and ferroptosis. Subsequently, eight marker genes (SCD, CD44, HIF1A, BCAT2, MTF1, HILPDA, NR1D2, and MYCN) were screened by LASSO and SVM‐RFE machine learning algorithms, and a model was constructed based on these eight genes. This model also has high diagnostic power. In addition, based on these eight genes, we obtained 48 drugs and constructed a complex ceRNA network map. Finally, Western blotting, IHC, IF, and qRT‐PCR results of clinical samples further confirmed the results of public databases. Conclusions The diagnosis and aetiology of T2DM can be greatly aided by eight FRGs, providing novel therapeutic avenues.

Objective This study aimed to investigate whether luteolin delays the progress of diabetic nephropathy (DN) induced by streptozotocin. Methods Fifty-three healthy, 8-week-old, male Sprague–Dawley rats were randomly divided into the control (n = 6), model (n = 23), and experimental groups (n = 24). The rat model of diabetic nephropathy was established by intraperitoneal injection of streptozotocin. Rats in the experimental group were administered luteolin suspension of 80 mg/kg daily for 8 weeks. Blood glucose levels and body weight were recorded until the fourth week. After intragastric administration, blood flow and the protective effect of luteolin on diabetic nephropathy were evaluated. Results The degree of renal apoptosis and fibrosis in the experimental group was milder, and glomerular structure was more complete compared with the model group. Nphs2 staining suggested that luteolin delayed apoptosis and deletion and fusion of podocytes under high glucose levels, and protected the filtration function of the basement membrane by upregulating Nphs2 protein expression. Time intensity curve results suggested that luteolin delayed deterioration of renal haemodynamics under hyperglycaemia. Conclusions This study shows that luteolin delays progression of diabetic nephropathy. This drug has potential wide applicability in future clinical application.

Background The hemolytic activity of skin secretions obtained by stimulating the frog Kaloula pulchra hainana with diethyl ether was tested using human, cattle, rabbit, and chicken erythrocytes. The skin secretions had a significant concentration-dependent hemolytic effect on erythrocytes. The hemolytic activity of the skin secretions was studied in the presence of osmotic protectants (polyethylene glycols and carbohydrates), cations (Mg2+, Ca2+, Ba2+, Cu2+, and K+), or antioxidants (ascorbic acid, reduced glutathione, and cysteine). Results Depending on their molecular mass, osmotic protectants effectively inhibited hemolysis. The inhibition of skin hemolysis was observed after treatment with polyethylene glycols (1000, 3400, and 6000 Da). Among divalent cations, only 1 mM Cu2+ markedly inhibited hemolytic activity. Antioxidant compounds slightly reduced the hemolytic activity. Conclusions The results suggested that skin secretions of K. pulchra hainana induce a pore-forming mechanism to form pores with a diameter of 1.36-2.0 nm rather than causing oxidative damage to the erythrocyte membrane.

Background. Resveratrol (RES) is a polyphenolic compound and natural phytoalexin that plays a potential role in various human diseases. Studies have confirmed that RES has an important function in cardioprotection. Objectives. To investigate the effect of RES on HO-1 protein expression in rat heart after different duration of hypothermic preservation. Material and methods. The Langendorff model of isolated rat heart was used. After being stored in 4°C different Celsior solution for 9 h, Sprague-Dawley rats hearts were divided into 6 groups randomly: control group, 9 h group, 3 μM RES group, 10 μM RES group, 30 μM RES group, and 100 μM RES group. The morphological changes of cardiomyocytes were detected with the hematoxylin & eosin (H&E) staining using a light microscope. The mRNA and protein expression of HO-1 were detected using reverse-transcription polymerase chain reaction (RT-PCR) and western blotting. Results. Compared with the control group, cardiomyocytes were obviously injured in the 9 h group and the protein and mRNA expression of HO-1 were obviously decreased. Compared with the 9 h group, the mRNA and protein expression of HO-1 were increased in dose-dependent manner in the 3 μM RES, 10 μM RES and 30 μM RES group. Compared with the 9 h group, rat myocardial injury was gradually alleviated in 3 μM RES, 10 μM RES and 30 μM RES groups. However, the rat myocardial injury in the 100 μM RES group showed no more obvious improvement than in the 30 μM RES group. Conclusions. In the isolated rat heart, RES protects cardiomyocytes against hypothermic preservation injury through increasing HO-1 protein expression. [ABSTRACT FROM AUTHOR]

The rapid development of artificial intelligence technology has influenced, constrained, guided, and even dominated modern combat methods. Especially in the field of command and control(C2), artificial intelligence technology deeply influences various elements and links of C2 activities through C2 systems and equipment. However, due to the novelty of artificial intelligence technology and the specificity of military systems, the impact of artificial intelligence on C2 is difficult to explicitly capture and measure during non war periods. This article systematically explores the mechanism of the role of artificial intelligence in the field of C2 from four aspects: the relationship between artificial intelligence and C2, the ways in which artificial intelligence affects the elements of C2, the trends in the impact of artificial intelligence on C2, and the risks and challenges faced by the co-evolution of artificial intelligence and C2. The conclusion drawn can assist military personnel in better controlling the battlefield, controlling war, and facing the challenges of war in the intelligent era.