Ethanol promoting the upregulation of C-X-C Motif Chemokine Ligand 1（CXCL1） and C-X-C Motif Chemokine Ligand 6（CXCL6） in models of early alcoholic liver disease.

Alcoholic liver disease (ALD) denotes a series of liver diseases caused by ethanol. Recently, immune-related genes (IRGs) play increasingly crucial role in diseases. However, it's unclear the role of IRGs in ALD. Bioinformatic analysis was used to discern the core immune-related differential genes (IRDGs) in the present study. Subsequently, Cell Counting Kit-8 say, oil red O staining, and triglyceride detection were employed to explore optimal experimental conditions of establishing hepatocellular models of early ALD. Ultimately, real-time reverse transcription-PCR and immunohistochemistry/immunocytochemistry methods were adopted to verify the expressions of mRNA and proteins of core IRDGs, respectively. C-X-C Motif Chemokine Ligand 1 (Cxcl1) and Cxcl6 were regarded as core IRDGs via integrated bioinformatics analysis. Besides, Lieber Decarli Ethanol feeding and 200 mM and 300 mM ethanol stimulating L02 cells for 36 h can both successfully hepatocellular model. In ethanol groups, the levels of CXCL1 and CXCL6 mRNA were significantly upregulated than pair-fed groups (P < 0.0001). Also, immunohistochemistry revealed that positive particles of CXCL1 and CXCL6 in mice model of early ALD were obviously more than control groups (P < 0.0001). Besides, in L02 hepatocytes stimulated by ethanol, CXCL1 and CXCL6 mRNA were over-expressed, compared with normal L02 cells (P < 0.0001). Meanwhile, immunocytochemistry indicated that CXCL1 and CXCL6 proteins in hepatocellular model of early ALD were higher than normal L02 hepatocytes stimulus (P < 0.0001). Ethanol promoted the upregulation of Cxcl1 and Cxcl6 mRNA and proteins in models of early ALD, denoting their potentiality of acting as biomarkers of ALD.

Long noncoding RNAs as biomarkers for the diagnosis of hepatocellular carcinoma: A meta-analysis.

BACKGROUND: Long non-coding RNAs (lncRNAs) are often aberrantly expressed in hepatocellular carcinoma (HCC). The role of lncRNAs in the diagnosis of HCC has attracted increasing attention. Hence, we performed a meta-analysis based on current studies to assess the diagnostic value of lncRNAs for HCC. METHODS: A systematic search was performed using PubMed, Web of Science, and Embase databases for relevant studies. The quality of the studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). A fixed-effect model was used if the value of I2 statistics < 50%; otherwise, a bivariate random effects model was applied (I2 ≥ 50%). In addition, subgroup analysis and meta-regression analysis were conducted to explore the sources of heterogeneity. Statistical analyses were based on Meta-Disc statistical software (Version 1.4) and STATA software (Version 15.1). RESULTS: A total of 52 studies in 20 related articles were selected for this meta-analysis, including 4930 patients and 4614 controls. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were 0.85 [95% confidence interval (CI) 0.82-0.88], 0.76 (95% CI 0.73-0.80), 3.6 (95% CI 3.1-4.2), 0.19 (95% CI 0.16-0.24), 19 (95% CI 14-26), and 0.88 (95% CI 0.85-0.91), respectively. The publication bias was evaluated by the Deek's funnel plot in our meta-analysis. CONCLUSIONS: LncRNAs can serve as feasible HCC diagnostic biomarkers. However, further studies are necessary to confirm its diagnostic and clinical value.

Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma.

Background: Cervical squamous cell carcinoma (CESC) is one of the most frequent malignancies in women worldwide. The level of immune cell infiltration and immune-related genes (IRGs) can significantly affect the prognosis and immunotherapy of CESC patients. Thus, this study aimed to identify an immune-related prognostic signature for CESC. Methods: TCGA-CESC cohorts, obtained from TCGA database, were divided into the training group and testing group; while GSE44001 dataset from GEO database was viewed as external validation group. ESTIMATE algorithm was applied to evaluate the infiltration levels of immune cells of CESC patients. IRGs were screened out through weighted gene co-expression network analysis (WGCNA). A multi-gene prognostic signature based on IRGs was constructed using LASSO penalized Cox proportional hazards regression, which was validated through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. The abundance of immune cells was calculated using ssGSEA algorithm in the ImmuCellAI database, and the response to immunotherapy was evaluated using immunophenoscore (IPS) analysis and the TIDE algorithm. Results: In TCGA-CESC cohorts, higher levels of immune cell infiltration were closely associated with better prognoses. Moreover, a prognostic signature was constructed using three IRGs. Based on this given signature, Kaplan-Meier analysis suggested the significant differences in overall survival (OS) and the ROC analysis demonstrated its robust predictive potential for CESC prognosis, further confirmed by internal and external validation. Additionally, multivariate Cox analysis revealed that the three IRGs signature served as an independent prognostic factor for CESC. In the three-IRGs signature low-risk group, the infiltrating immune cells (B cells, CD4/8 + T cells, cytotoxic T cells, macrophages and so on) were much more abundant than that in high-risk group. Ultimately, IPS and TIDE analyses showed that low-risk CESC patients appeared to present with a better response to immunotherapy and a better prognosis than high-risk patients. Conclusion: The present prognostic signature based on three IRGs (CD3E, CD3D, LCK) was not only reliable for survival prediction but efficient to predict the clinical response to immunotherapy for CESC patients, which might assist in guiding more precise individual treatment in the future.

Integrated Analyses Identify Key Molecules and Reveal the Potential Mechanism of miR-182-5p/FOXO1 Axis in Alcoholic Liver Disease.

Background: Alcoholic liver disease (ALD) is one of the most common chronic liver diseases worldwide. However, the potential molecular mechanism in ALD development remains unclear. The objective of this work was to identify key molecules and demonstrate the underlying regulatory mechanisms. Methods: RNA-seq datasets were obtained from Gene Expression Omnibus (GEO), and key molecules in ALD development were identified with bioinformatics analysis. Alcoholic liver disease mouse and cell models were constructed using Lieber-DeCarli diets and alcohol medium, respectively. Quantitative real-time PCR and Western blotting were conducted to confirm the differential expression level. Dual-luciferase reporter assays were performed to explore the targeting regulatory relationship. Overexpression and knockdown experiments were applied to reveal the potential molecular mechanism in ALD development. Results: Between ALD patients and healthy controls, a total of 416 genes and 21 microRNAs (miRNAs) with significantly differential expression were screened. A comprehensive miRNA-mRNA network was established; within this network, the miR-182-5p/FOXO1 axis was considered a significant pathway in ALD lipid metabolism. Mouse and cell experiments validated that miR-182-5p was substantially higher in ALD than in normal livers, whereas the expression of FOXO1 was dramatically decreased by alcohol consumption (P < 0.05). Next, dual-luciferase reporter assays demonstrated that miR-182-5p directly targets the binding site of the FOXO1 3'UTR and inhibits its mRNA and protein expression. In addition, miR-182-5p was found to promote hepatic lipid accumulation via targeting the FOXO1 signaling pathway, and inhibition of the miR-182-5p/FOXO1 axis improved hepatic triglyceride (TG) deposition in ALD by regulating downstream genes involved in lipid metabolism. Conclusion: In summary, key molecules were identified in ALD development and a comprehensive miRNA-mRNA network was established. Meanwhile, our results suggested that miR-182-5p significantly increases lipid accumulation in ALD by targeting FOXO1, thereby providing novel scientific insights and potential therapeutic targets for ALD.

Response mechanism of the phase transitions of poly(n-isopropylacrylamide-co-benzo-18-crown-6-acrylamide) using infrared spectroscopy.

The thermal and ionic effects on the phase transitions of poly(N-isopropylacrylamide) (PNIPAAm) and its copolymer with benzo-18-crown-6-acrylamide, poly(N-isopropylacrylamide-co-benzo-18-crown-6-acrylamide) (PNIPAAm-co-BCAm), were investigated using infrared (IR) spectral variations of methyl (CH3), C=O, and amine (NH) groups. Subsequently, perturbation correlation moving-window two-dimensional correlation infrared spectroscopy (PCMW 2D-IR) was applied to clarify the differences in the phase-transition mechanisms of the polymers. The dominant influence on the phase-transition mechanism of PNIPAAm is whether the anion is evenly distributed in the bulk solution. The results show that the phase transition shifts to a lower temperature with increasing barium chloride (BaCl2) concentrations. In addition, the effect of the anion on the chemical group is homogeneous upon heating. As a result, the relevant transition temperature ranges have remain approximately constant. In contrast, the dominant influence on the phase-transition mechanism of PNIPAAm-co-BCAm is the interactions of the polymer chains with barium ions (Ba(2+)). The hydrophilic BCAm-Ba(2+) complexes distributed in the PNIPAAm-co-BCAm chain prevent the water molecules from leaving the polymer chains, which leads to an increase in the transition temperature and the complicated variation of the transition temperature range, as environmental stimuli-response behavior, with increasing BaCl2 concentrations.