Machine Learning-based Development and Validation of a Cell Senescence Predictive and Prognostic Signature in Intrahepatic Cholangiocarcinoma.

Background: Previous studies have shown that cellular senescence is strongly associated with tumorigenesis and the tumor microenvironment. Accordingly, we developed a novel prognostic signature for intrahepatic cholangiocarcinoma (ICCA) based on senescence-associated long non-coding RNAs (SR-lncRNAs) and identified a lncRNA-miRNA-mRNA axis involving in ICCA. Methods: Based on the 197 senescence-associated genes (SRGs) from Genacards and their expression in Fu-ICCA cohort, we identified 20 lncRNAs as senescence-associated lncRNAs (SR-lncRNAs) through co-expression and cox-regression analysis. According to 20 SR-lncRNAs, patients with ICCA were classified into 2 molecular subtypes using unsupervised clustering machine learning approach and to explore the prognostic and functional heterogeneity between these two subtypes. Subsequently, we integrated 113 machine learning algorithms to develop senescence-related lncRNA signature, ultimately identifying 11 lncRNAs and constructing prognostic models and risk stratification. The correlation between the signature and the immune landscape, immunotherapy response as well as drug sensitivity are explored too. Results: We developed a novel senescence related signature. The predictive model and risk score calculated by the signature exhibited favorable prognostic predictive performance, which is a suitable independent risk factor for the prognosis of patients with ICCA based on Kaplan-Meier plotter, nomogram and receiving operating characteristic (ROC) curves. The results were validated using external datasets. Estimate, ssGSEA (single sample gene set enrichment analysis), IPS (immunophenotype score) and TIDE (tumor immune dysfunction and exclusion) algorithms revealed higher immune infiltration, higher immune scores, lower immune escape potential and better response to immunotherapy in the high-risk group. In addition, signature identifies eight chemotherapeutic agents, including cisplatin for patients with different risk levels, providing guidance for clinical treatment. Finally, we identified a set of lncRNA-miRNA-mRNA axes involved in ICCA through regulation of senescence. Conclusion: SR-lncRNAs signature can favorably predict the prognosis, risk stratification, immune landscape and immunotherapy response of patients with ICCA and consequently guide individualized treatment.

Association between visceral adipose tissue and asthma based on the NHANES and Mendelian randomization study.

BACKGROUND: Obesity is a crucial risk factor for asthma. Observational studies have examined the association between abdominal obesity and asthma symptoms. This study aimed to investigate the causal relationship between visceral adipose tissue (VAT) and asthma and its potential as an independent indicator. METHODS: This study utilized data from the National Health and Nutrition Examination Survey spanning 2011-8. Multivariable logistic regression and stratified variable selection were employed to identify associations between asthma and VAT. Moreover, a two-sample Mendelian randomization analysis, using 221 genetic variants as instrumental variables, was conducted to assess this relationship further. RESULTS: Our findings indicated that individuals with higher VAT levels were more likely to develop asthma. Visceral obesity remained a significant risk factor for asthma after adjusting for demographic characteristics. Genetic predictions suggest a positive association between VAT and an elevated risk of asthma (odds ratio [OR] = 1.393, 95% confidence interval [CI]: 1.266-1.534, and P = 1.43E-11). No significant polymorphisms were detected using the Mendelian randomization-Egger intercept test. CONCLUSIONS: This study presents potential evidence supporting the causal role of VAT in asthma development. Furthermore, the findings from the Mendelian randomization analysis further reinforce the relationship between VAT and asthma risk.

The significance of m6A RNA methylation regulators in diagnosis and subtype classification of HBV-related hepatocellular carcinoma.

In recent years, abnormal m6A alteration in hepatocellular carcinoma (HCC) has been a focus on investigating the biological implications. In this study, our objective is to determine whether m6A modification contributes to the progression of HBV-related HCC. To achieve this, we employed a random forest model to screen top 8 characteristic m6A regulators from 19 candidate genes. Subsequently, we developed a nomogram model that utilizes these 8 characteristic m6A regulators to predict the prevalence of HBV-related HCC. According to decision curve analysis, patients may benefit from the nomogram model. The clinical impact curves exhibited a robust predictive capability of the nomogram models. Additionally, consensus molecular subtyping was employed to identify m6A modification patterns and m6A-related gene signature. The quantification of immune cell subsets was accomplished through the implementation of ssGSEA algorithms. PCA algorithms were developed to compute the m6A score for individual tumors. Two distinct m6A modification patterns, namely cluster A and cluster B, exhibited significant correlations with distinct immune infiltration patterns and biological pathways. Notably, patients belonging to cluster B demonstrated higher m6A scores compared to those in cluster A, as determined by the m6A score metric. Furthermore, the expression of IGFBP3 proteins was validated through immunofluorescence, revealing their pronounced lower expression in tumor tissues. In summary, our study underscores the importance of m6A modification in the advancement of HBV-related HCC. This research has the potential to yield novel prognostic biomarkers and therapeutic targets for the identification of HBV-related HCC.

PCDH8 is a novel prognostic biomarker in thyroid cancer and promotes cell proliferation and viability.

Protocadherin 8 (PCDH8), a calcium-dependent transmembrane protein in the protocadherin family, regulates cell adhesion and signal transduction. While some studies have provided indirect evidence that PCDH8 has cancer-promoting properties, this association is controversial. In particular, its involvement in thyroid cancer (THCA) remains unclear. We aimed to elucidate the role of PCDH8 in THCA using bioinformatic analysis. Subsequently, the results were experimentally validated. The analysis conducted using the R programming language and online web tools explored PCDH8 expression levels, prognostic, and clinical implications, and its relationship with the tumor immune microenvironment in THCA. Furthermore, we examined the association between PCDH8 and co-expressed genes, highlighting their involvement in several biological processes relevant to THCA. The potential of PCDH8 as a therapeutic target for this pathology was also explored. Immunohistochemical (IHC) staining was performed on samples from 98 patients with THCA, and experimental validation was carried out. PCDH8 was significantly elevated in cancer tissues and associated with poor prognosis, several clinical factors, and immune cell and checkpoint abundance. Cox regression and survival analyses, together with Receiver Operating Curves (ROC) indicated that PCDH8 was an independent prognostic factor for THCA. Furthermore, PCDH8 impacts cell viability and proliferation, promoting tumorigenesis. Also, it influences tumor cell sensitivity to various drugs. Thus, PCDH8 might be a potential therapeutic target for THCA. IHC, cell culture, MTT, and colony formation experiments further confirmed our findings. This analysis provided insights into the potential carcinogenic role of PCDH8 in THCA, as it impacts cell viability and proliferation. Thus, PCDH8 might play an important role in its prognosis, immune infiltration, and diagnosis.

Colonic microflora and plasma metabolite-based comparative analysis of unilateral ureteral obstruction-induced chronic kidney disease after treatment with the Chinese medicine FuZhengHuaYuJiangZhuTongLuo and AST-120.

Background: Many researchers have investigated the use of Chinese herbs to delay the progression of chronic kidney disease (CKD) through their effects on colonic microflora and microbiota-derived metabolites. However, whether FuZhengHuaYuJiangZhuTongLuo (FZHY) has effects that are similar to those of AST-120 on CKD needs to be elucidated. Methods: In this study, we compared the effects of FZHY and AST-120 on the colonic microbiota and plasma metabolites in the CKD rat model. We developed a unilateral ureteral obstruction (UUO)-induced CKD rat model and then administered FZHY and AST-120 to these model rats. Non-targeted metabolomic LC-MS analysis, 16S rRNA sequencing, and histopathological staining were performed on plasma, stool, and kidney tissues, respectively, and the joint correlation between biomarkers and metabolites of candidate bacteria was analyzed. Results: Our results showed that administering FZHY and AST-120 effectively ameliorated UUO-induced abnormal renal function and renal fibrosis and regulated the composition of microbiota and metabolites. Compared to the UUO model group, the p_Firmicutes and o_Peptostreptococcales_Tissierellales were increased, while 14 negative ion metabolites were upregulated and 21 were downregulated after FZHY treatment. Additionally, 40 positive ion metabolites were upregulated and 63 were downregulated. On the other hand, AST-120 treatment resulted in an increase in the levels of g_Prevotellaceae_NK3B31_group and f_Prevotellaceae, as well as 12 upregulated and 23 downregulated negative ion metabolites and 56 upregulated and 63 downregulated positive ion metabolites. Besides, FZHY increased the levels of candidate bacterial biomarkers that were found to be negatively correlated with some poisonous metabolites, such as 4-hydroxyretinoic acid, and positively correlated with beneficial metabolites, such as l-arginine. AST-120 increased the levels of candidate bacterial biomarkers that were negatively correlated with some toxic metabolites, such as glycoursodeoxycholic acid, 4-ethylphenol, and indole-3-acetic acid. Conclusion: FZHY and AST-120 effectively reduced kidney damage, in which, the recovery of some dysregulated bacteria and metabolites are probably involved. As their mechanisms of regulation were different, FZHY might play a complementary role to AST-120 in treating CKD.

Is Kidney Stone Associated with Thyroid Disease? The United States National Health and Nutrition Examination Survey 2007­2018

BACKGROUND: Kidney stones and thyroid disease are two common diseases in the general population, with multiple common risk factors. The associations between kidney stones and thyroid disease are unclear. AIM: This study aims to assess the association between 'once had a thyroid disease' and the odds of kidney stones. METHODS: Adult participants from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 with reliable kidney stone and thyroid disease data were included. Adjusting for age, gender, race, education level, and marital status, diabetes, hypertension, gout, angina pectoris, stroke, and asthma, logistic regression was used to examine the relationship between kidney stones and thyroid illness. RESULTS: Using stratified analysis, the association between thyroid illness and kidney stones was investigated further. Among the participants, 4.9% had kidney stones, and 10.1% had thyroid disease. Kidney stone was associated with thyroid disease (OR=1.441, (95% CI:1.294-1.604), p <0.01), which remained significant (OR=1.166, (95% CI:1.041-1.305), p <0.01) after adjustments with age, gender, race, education level and marital status, diabetes, hypertension, gout, angina pectoris, stroke, and asthma. Stratified by blood lead, blood cadmium, and blood urea nitrogen levels in the human body, the odds of kidney stones still increased with once having a previous thyroid disease. CONCLUSIONS: In this large nationally representative survey over 10 years, kidney stone was strongly associated with thyroid disease. In this cross-sectional study, we explored the association between thyroid disease and kidney stones, which may help clinicians intervene in them early.

Enhanced catalytic performance of penicillin G acylase by covalent immobilization onto functionally-modified magnetic Ni0.4Cu0.5Zn0.1Fe2O4 nanoparticles.

With the emergence of penicillin resistance, the development of novel antibiotics has become an urgent necessity. Semi-synthetic penicillin has emerged as a promising alternative to traditional penicillin. The demand for the crucial intermediate, 6-aminopicillanic acid (6-APA), is on the rise. Enzyme catalysis is the primary method employed for its production. However, due to certain limitations, the strategy of enzyme immobilization has also gained prominence. The magnetic Ni0.4Cu0.5Zn0.1Fe2O4 nanoparticles were successfully prepared by a rapid-combustion method. Sodium silicate was used to modify the surface of the Ni0.4Cu0.5Zn0.1Fe2O4 nanoparticles to obtain silica-coated nanoparticles (Ni0.4Cu0.5Zn0.1Fe2O4-SiO2). Subsequently, in order to better crosslink PGA, the nanoparticles were modified again with glutaraldehyde to obtain glutaraldehyde crosslinked Ni0.4Cu0.5Zn0.1Fe2O4-SiO2-GA nanoparticles which could immobilize the PGA. The structure of the PGA protein was analyzed by the PyMol program and the immobilization strategy was determined. The conditions of PGA immobilization were investigated, including immobilization time and PGA concentration. Finally, the enzymological properties of the immobilized and free PGA were compared. The optimum catalytic pH of immobilized and free PGA was 8.0, and the optimum catalytic temperature of immobilized PGA was 50°C, 5°C higher than that of free PGA. Immobilized PGA in a certain pH and temperature range showed better catalytic stability. Vmax and Km of immobilized PGA were 0.3727 µmol·min-1 and 0.0436 mol·L-1, and the corresponding free PGA were 0.7325 µmol·min-1 and 0.0227 mol·L-1. After five cycles, the immobilized enzyme activity was still higher than 25%.

Integrated Multi-omics Analyses Identify CDCA5 as a Novel Biomarker Associated with Alternative Splicing, Tumor Microenvironment, and Cell Proliferation in Colon Cancer Via Pan-cancer Analysis.

Background: CDCA5 has been reported as a gene involved in the cell cycle, however current research provides little details. Our goal was to figure out its functions and probable mechanisms in pan-cancer. Methods: Pan-cancer bulk sequencing data and web-based analysis tools were applied to analyze CDCA5's correlations with the gene expression, clinical prognosis, genetic alterations, promoter methylation, alternative splicing, immune checkpoints, tumor microenvironment and enrichment. Real­time PCR, cell clone formation assay, CCK-8 assay, cell proliferation assay, migration assay, invasion assay and apoptosis assay were used to evaluate the effect of CDCA5 silencing on colon cancer cell lines. Results: CDCA5 is highly expressed in most tumors, which has been linked to a poor prognosis. Immune checkpoints analysis revealed that CDCA5 was associated with the immune gene CD276 in various tumors. Single-cell analysis showed that CDCA5 correlated with proliferating T cell infiltration in COAD. Enrichment analysis demonstrated that CDCA5 may modify cell cycle genes to influence p53 signaling. The examination of DLD1 cells revealed that CDCA5 increased the proliferation and blocked cell apoptosis. Conclusion: This study contributes to the knowledge of the role of CDCA5 in carcinogenesis, highlighting the prognostic potential and carcinogenic involvement of CDCA5 in pan-cancer.

Changes in Blood Pressure is Associated with Bone Loss in US Adults: A Cross-Sectional Study from NHANES 2005-2018.

Hypertension and osteoporosis are common geriatric diseases, sharing similar risk factors. This study aims to investigate this association and explore relatively mixed variables. Our study included 12,787 eligible participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Included participants had valid data on hypertension and osteoporosis, without tumors, liver diseases, gout or thyroid diseases. We explored the association between hypertension and osteoporosis by logistic regression and examined blood pressure and BMD/BMC by linear and non-linear regression. Moreover, we used machine learning models to predict the importance of various factors in the occurrence of osteoporosis and evaluated causality by mendelian randomization. Our study found that osteoporosis is significantly associated with hypertension [OR 2.072 (95% CI 2.067-2.077), p < 0.001]. After adjusting for co-variances, the association remained significant [OR 1.223 (95% CI 1.220-1.227), p < 0.001]. Our study showed that osteoporosis is positively associated with hypertension in the US population. A variety of factors influence this relationship. Specific regulatory mechanisms and confounding factors need to be further investigated.

Investigation of GPR143 as a promising novel marker for the progression of skin cutaneous melanoma through bioinformatic analyses and cell experiments.

BACKGROUND: Skin cutaneous melanoma (SKCM) is an aggressive and life-threatening skin cancer. G-protein coupled receptor 143 (GPR143) belongs to the superfamily of G protein-coupled receptors. METHODS: We used the TCGA, GTEx, CCLE, and the Human Protein Atlas databases to examine the mRNA and protein expression of GPR143. In addition, we performed a survival analysis and evaluated the diagnostic efficacy using the Receiver-Operating Characteristic (ROC) curve. Through CIBERSORT, R programming, TIMER, Gene Expression Profiling Interactive Analysis, Sangerbox, and Kaplan-Meier plotter database analyses, we explored the relationships between GPR143, immune infiltration, and gene marker expression of immune infiltrated cells. Furthermore, we investigated the proteins that potentially interact with GPR143 and their functions using R programming and databases including STRING, GeneMANIA, and GSEA. Meanwhile, the cBioPortal, UALCNA, and the MethSurv databases were used to examine the genomic alteration and methylation of GPR143 in SKCM. The Connectivity Map database was used to discover potentially effective therapeutic molecules against SKCM. Finally, we conducted cell experiments to investigate the potential role of GPR143 in SKCM. RESULTS: We demonstrated a significantly high expression level of GPR143 in SKCM compared with normal tissues. High GPR143 expression and hypomethylation status of GPR143 were associated with a poorer prognosis. ROC analysis showed that the diagnostic efficacy of the GPR143 was 0.900. Furthermore, GPR143 expression was significantly correlated with immune infiltration in SKCM. We identified 20 neighbor genes and the pathways they enriched were anabolic process of pigmentation, immune regulation, and so on. Genomic alteration analysis revealed significantly different copy number variations related to GPR143 expression in SKCM, and shallow deletion could lead to high expression of GPR143. Ten potential therapeutic drugs against SKCM were identified. GPR143 knockdown inhibited melanoma cell proliferation, migration, and colony formation while promoting apoptosis. CONCLUSIONS: Our findings suggest that GPR143 serves as a novel diagnostic and prognostic biomarker and is associated with the progression of SKCM.

Surpassing the limitation of a coherence length in lidar by digital coherence.

In this manuscript, we propose a digital coherent detection method to surpass the limitation of a coherent length on the detection range of a coherent lidar. This method rapidly reconstructs the laser phase noise utilizing the multi-channel delay self-homodyne and the generalized inverse of the system observation matrix. Subsequently, the reconstructed phase noise is utilized to expunge its perturbation onto the target information in the digital domain, thereby effectively surmounting the coherence length limitation. Through experimentation, the proposed method is verified to produce stable and high-quality interference even when the optical path difference between two beams exceeds 1000 times the coherence length. Additionally, the equivalent laser linewidth is compressed by 105 times.

Mediating oxidative stress through the Palbociclib/miR-141-3p/STAT4 axis in osteoporosis: a bioinformatics and experimental validation study.

Osteoporosis is a common bone disease characterized by loss of bone mass, reduced bone strength, and deterioration of bone microstructure. ROS-induced oxidative stress plays an important role in osteoporosis. However, the biomarkers and molecular mechanisms of oxidative stress are still unclear. We obtained the datasets from the Gene Expression Omnibus (GEO) database, and performed differential analysis, Venn analysis, and weighted correlation network analysis (WGCNA) analysis out the hub genes. Then, the correlation between inflammatory factors and hub genes was analyzed, and a Mendelian randomization (MR) analysis was performed on cytokines and osteoporosis outcomes. In addition, "CIBERSORT" was used to analyze the infiltration of immune cells and single-cell RNA-seq data was used to analyze the expression distribution of hub genes and cell-cell communications. Finally, we collected human blood samples for RT-qPCR and Elisa experiments, the miRNA-mRNA network was constructed using the miRBase database, the 3D structure was predicted using the RNAfold, Vfold3D database, and the drug sensitivity analysis was performed using the RNAactDrug database. We obtained three differentially expressed genes associated with oxidative stress: DBH, TAF15, and STAT4 by differential, WGCNA clustering, and Venn screening analyses, and further analyzed the correlation of these 3 genes with inflammatory factors and immune cell infiltration and found that STAT4 was significantly and positively correlated with IL-2. Single-cell data analysis showed that the STAT4 gene was highly expressed mainly in dendritic cells and monocytes. In addition, the results of RT-qPCR and Elisa experiments verified that the expression of STAT4 was consistent with the previous analysis, and a significant causal relationship between IL-2 and STAT4 SNPs and osteoporosis was found by Mendelian randomization. Finally, through miRNA-mRNA network and drug sensitivity analysis, we analyzed to get Palbociclib/miR-141-3p/STAT4 axis, which can be used for the prevention and treatment of osteoporosis. In this study, we proposed the Palbociclib/miR-141-3p/STAT4 axis for the first time and provided new insights into the mechanism of oxidative stress in osteoporosis.

Bioinformatic Analysis to Identify and Cellular Experiments to Validate Autophagy-related Genes in Psoriasis.

PURPOSE: To explore differentially expressed genes (DEGs) associated with autophagy in psoriasis using bioinformatics analysis and verify them in an M5-induced psoriatic cell model. METHODS: We obtained gene expression microarray data from patients with psoriasis and normal skin tissues from the dataset GSE78097 of the NCBI Gene Expression Omnibus (GEO) database. R software was used to identify DEGs associated with autophagy in psoriasis. Proteinprotein interaction (PPI) and correlation analyses were used to show interactions between certain genes. Their potential biological roles were determined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, all the DEGs associated with autophagy in psoriasis were validated in a psoriatic cell model by RT-qPCR. RESULTS: 28 DEGs associated with autophagy were identified. These genes were linked to one another, and the most connected hub gene was VEGFA, according to PPI analysis. GO and KEGG enrichment analyses revealed various biological pathways associated with autophagy. The RT-qPCR findings of the expression of 18 genes in the psoriatic cell model confirmed the bioinformatics analysis results. The five genes with the most significant differences were IL24, CCL2, NAMPT, PPP1R15A, and SPHK1. CONCLUSION: We identified DEGs associated with autophagy in patients with psoriasis. IL24, CCL2, NAMPT, PPP1R15A, and SPHK1 were identified as important genes that may influence psoriasis development through the regulation of autophagy.

Prediction of gaseous medium insulation strength based on electrostatic potential on real space function isosurface.

CONTEXT: SF6 is widely used in electrical equipment due to its chemical stability and insulation strength, but it is a strong greenhouse gas and its use has been restricted internationally. In order to reduce the SF6 usage, it is needed to find a replacement gas for SF6. Electrical breakdown test is always adopted to select potential substitutes, but it is resource and time intensive. Thus, a structure-activity relationship model is needed to effectively predict the gas insulation strength. In this work, we calculated the isosurface electrostatic potential of 68 gas molecules in case of electron probability density, Laplacian of electron density, electron localization function, and localized orbital function. The distribution characteristics of these four real space functions were analyzed. Furthermore, correlation between the electrostatic potential parameters and insulation strength was presented. Finally, a prediction model for insulation strength of gaseous medium was established. Using the electrostatic potential parameter on the localized orbital locator function with a threshold of 0.05 a.u., the prediction model achieved the best performance with a coefficient of determination of 0.860 and a mean squared error of 0.0663. METHODS: The quantization calculation tool used in this work is the GAUSSIAN 16 software. The M06-2X method with the 6-311G++(d, p) basis set is used to optimize the molecular structure and output stable wavefunction files. Then the wavefunction analysis software Multiwfn is used to plot the contour map of the gas molecules and calculate the radial distribution patterns.

Electrochemical sensor based on Fe3O4/α-Fe2O3@Au magnetic nanocomposites for sensitive determination of the TP53 gene.

Considering the high cost and tedious process of gene sequencing, there is an urgent need to develop portable and efficient sensors for the TP53 gene. Here, we developed a novel electrochemical sensor that detected the TP53 gene using magnetic peptide nucleic acid (PNA)-modified Fe3O4/α-Fe2O3@Au nanocomposites. Cyclic voltammetry and electrochemical impedance spectroscopy confirmed the successful stepwise construction of the sensor, especially the high-affinity binding of PNA to DNA strands, which induced different electron transfer rates and resulted in current changes. Variations in the differential pulse voltammetry current observed during hybridization at different surface PNA probe densities, hybridization times, and hybridization temperatures were explored. The biosensing strategy obtained a limit of detection of 0.26 pM, a limit of quantification of 0.85 pM, and a wide linear range (1 pM-1 µM), confirming that the Fe3O4/α-Fe2O3@Au nanocomposites and the strategy based on magnetic separation and magnetically induced self-assembly improved the binding efficiency of nucleic acid molecules. The biosensor was a label-free and enzyme-free device with excellent reproducibility and stability that could identify single-base mismatched DNA without additional DNA amplification procedures, and the serum spiked experiments revealed the feasibility of the detection approach.

Association between serum S100A11 levels and glucose metabolism in diabetic process.

BACKGROUND: Diabetes mellitus (DM) is a prevalent non-communicable metabolic disease, and S100A11 is a newly identified gene closely related to metabolism. The association of S100A11 with diabetes is unclear. This study aimed to assess the relationship between S100A11 and markers of glucose metabolism in patients with different glucose tolerance and gender. METHODS: This study included 97 participants. Baseline data were obtained, and the serum levels of S100A11 and metabolic markers (glycated hemoglobin [HbA1c], insulin release test, and oral glucose tolerance test) were measured. Linear and nonlinear correlations between serum S100A11 levels and HOMA-IR, HOMA of ß, HbA1c, insulin sensitivity index (ISI), corrected insulin response (CIR), and oral disposition index (DIo) were analyzed. The expression of S100A11 was also detected in mice. RESULTS: Serum S100A11 levels increased in patients with impaired glucose tolerance (IGT) of both genders. S100A11 mRNA and protein expression increased in obese mice. There were nonlinear correlations between S10011 levels and CIR, FPI, HOMA-IR, whole-body ISI in the IGT group. S100A11 was nonlinearly correlated with HOMA-IR, hepatic ISI, FPG, FPI, and HbA1c in the DM group. In the male group, S100A11 was linearly correlated with HOMA-IR and nonlinearly correlated with DIo (derived from hepatic ISI) and HbA1c. In the female population, S100A11 was nonlinearly correlated with CIR. CONCLUSIONS: Serum S100A11 levels were highly expressed in patients with IGT and in the liver of obese mice. In addition, there were linear and nonlinear correlations between S100A11 and markers of glucose metabolism, demonstrating that S100A11 has a role in diabetes. Trial registration ChiCTR1900026990.

Osteoprotegerin deficiency aggravates methionine-choline-deficient diet-induced nonalcoholic steatohepatitis in mice.

Clinical studies have shown that osteoprotegerin (OPG) is reduced in patients with nonalcoholic steatohepatitis (NASH), but the underlying mechanisms are unclear. The current study focuses on the role of OPG in the NASH pathogenesis. OPG knockout mice and wild-type control mice fed a methionine choline-deficient diet (MCD) for 4 weeks resulted in an animal model of NASH. Measurement of triglycerides (TG) in serum and liver to assess steatosis. Hematoxylin eosin (HE), Sirius Red and Masson staining were used to assess the liver damage. Transcriptome sequencing analysis, qPCR and western blot were to analyze changes in lipid metabolism and inflammation-related indicators in the liver. In vivo knockout of OPG resulted in a reduction of TG levels in the liver and a significant increase in serum ALT and AST. The expression of inflammatory factors and fibrosis genes was significantly upregulated in the livers of OPG knockout mice. Transcriptome sequencing analysis showed that OPG knockout significantly enhanced MCD diet-induced activation of the mitogen-activated protein kinase (MAPK) signaling pathway. Mechanistically, OPG may inhibit MAPK signaling pathway activity by upregulating the expression of dual specificity phosphatase 14 (DUSP14), thereby reducing inflammatory injury. OPG could regulate the activity of the MAPK signaling pathway via DUSP14, thus regulating the expression of some inflammatory factors in NASH, it may be a promising target for the treatment of NASH.

Assessment of Diagnosis, Prognosis and Immune Infiltration Response to the Expression of the Ferroptosis-Related Molecule HAMP in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Hepcidin antimicrobial peptide (HAMP) is a key factor in maintaining iron metabolism, which may induce ferroptosis when upregulated. However, its prognostic value and relation to immune infiltrating cells remains unclear. METHODS: This study analyzed the expression levels of HAMP in the Oncomine, Timer and Ualcan databases, and examined its prognostic potential in KIRC with R programming. The Timer and GEPIA databases were used to estimate the correlations between HAMP and immune infiltration and the markers of immune cells. The intersection genes and the co-expression PPI network were constructed via STRING, R programming and GeneMANIA, and the hub genes were selected with Cytoscape. In addition, we analyzed the gene set enrichment and GO/KEGG pathways by GSEA. RESULTS: Our study revealed higher HAMP expression levels in tumor tissues including KIRC, which were related to poor prognosis in terms of OS, DSS and PFI. The expression of HAMP was positively related to the immune infiltration level of macrophages, Tregs, etc., corresponding with the immune biomarkers. Based on the intersection genes, we constructed the PPI network and used the 10 top hub genes. Further, we performed a pathway enrichment analysis of the gene sets, including Huntington's disease, the JAK-STAT signaling pathway, ammonium ion metabolic process, and so on. CONCLUSION: In summary, our study gave an insight into the potential prognosis of HAMP, which may act as a diagnostic biomarker and therapeutic target related to immune infiltration in KIRC.

The antifibrotic and anti-inflammatory effects of FZHY prescription on the kidney in rats after unilateral ureteral obstruction.

PURPOSE: To explore the potential impact of traditional Chinese herb FuZhengHuaYuJiangZhuTongLuo recipe (FZHY) on renal interstitial fibrosis (RIF) in chronic kidney disease (CKD) at cellular and molecular levels. METHODS: Unilateral ureteral obstruction (UUO) rats were established as the RIF model in vivo. The rats were given intragastric administration with FZHY once a day for consecutive 7, 14 and 21 days, respectively. The renal function parameters and inflammation indicators in kidney tissues were measured using enzyme-linked immunosorbent assay, the CD4+/CD8+ T cells in peripheral blood was detected using flow cytometry, the renal fibrosis degree was estimated using Masson's staining, and the fibrosis-related genes' expression was detected using quantitative polymerase chain reaction, western blotting, and immunohistochemistry analyses. RESULTS: FZHY prescription reduced the serum creatinine and blood urea nitrogen, decreased the levels of c-reactive protein, interleukin-1, interleukin-6 and tumor necrosis factor-α in kidney tissues, and increased the ratio of CD4+/CD8+ T cells in peripheral blood. FZHY prescription suppressed the renal tissue fibrosis and reduced the levels of laminin, fibronectin, collagen I and collagen III. CONCLUSIONS: FZHY prescription suppressed the renal fibrosis and improved the condition of "Healthy Qi Deficiency and Evil Qi Excess" in rats with UUO, which may provide an effective method for CKD treatment.

GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas.

Gliomas are the most frequent malignant and aggressive tumors in the central nervous system. Early and effective diagnosis of glioma using diagnostic biomarkers can prolong patients' lives and aid in the development of new personalized treatments. Therefore, a thorough and comprehensive understanding of the diagnostic biomarkers in gliomas is of great significance. To this end, we developed the integrated and web-based database GlioMarker (http://gliomarker.prophetdb.org/), the first comprehensive database for knowledge exploration of glioma diagnostic biomarkers. In GlioMarker, accurate information on 406 glioma diagnostic biomarkers from 1559 publications was manually extracted, including biomarker descriptions, clinical information, associated literature, experimental records, associated diseases, statistical indicators, etc. Importantly, we integrated many external resources to provide clinicians and researchers with the capability to further explore knowledge on these diagnostic biomarkers based on three aspects. (1) Obtain more ontology annotations of the biomarker. (2) Identify the relationship between any two or more components of diseases, drugs, genes, and variants to explore the knowledge related to precision medicine. (3) Explore the clinical application value of a specific diagnostic biomarker through online analysis of genomic and expression data from glioma cohort studies. GlioMarker provides a powerful, practical, and user-friendly web-based tool that may serve as a specialized platform for clinicians and researchers by providing rapid and comprehensive knowledge of glioma diagnostic biomarkers to subsequently facilitates high-quality research and applications.