Publications by authors named "Chong-ge You"

Article Synopsis
  • Liver cancer is a common and serious health issue, with early detection being vital for improving survival rates, but symptoms often go unnoticed until later stages.
  • The study aims to create a machine learning-based risk prediction model to help identify liver cancer early, using data from 550 patients including those with hepatocellular carcinoma and cirrhosis.
  • Among four models tested (Logistic Regression, SVM, Random Forest, and LASSO), the Random Forest model outperformed others, achieving high accuracy metrics in predicting liver cancer risk, which could aid in better early diagnosis.
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Background: Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated.

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Gout is a common inflammatory disease. The activation of NLRP3 inflammasome induced by monosodium urate (MSU) crystals has a critical role in gout, and its prevention is beneficial for patients. Lipoxin A4 (LXA4) is an endogenous lipoxygenase-derived eicosanoid mediator with powerful anti-inflammatory properties.

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Background: The incidence, prevalence, and mortality of ischemic stroke (IS) continue to rise, resulting in a serious global disease burden. The prediction models have a great value in the early prediction and diagnosis of IS.

Methods: The R software was used to screen the differentially expressed genes (DEGs) of IS and control samples in the datasets GSE16561, GSE58294, and GSE37587 and analyze DEGs for enrichment analysis.

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Objective: This review aims to summarize the capability of lipoxin in regulating oxidative stress.

Background: Oxidative stress is defined as an imbalance between the production of free radicals and the antioxidant system, and it is associated with the existence of a large number of oxidation products, such as reactive oxygen species (ROS) and reaction nitrogen species (RNS), causing damage to human tissues through immunoinflammatory responses. Therefore, reducing oxidative stress is vital to alleviate pathological damage.

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Gout is a chronic metabolic disease that seriously affects human health. It is also a major challenge facing the world, which has brought a heavy burden to patients and society. Hyperuricemia (HUA) is the most important risk factor for gout.

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Purpose: To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE.

Methods: The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database.

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Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex-specific outcome, and revealing potential treatment targets.

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Due to changes in lifestyle, diet structure, and aging worldwide, the incidence of metabolic syndromes such as hyperlipidemia, hypertension, diabetes, and obesity is increasing. Metabolic syndrome is considered to be closely related to cardiovascular disease and severely affects human health. In recent years, researchers have revealed that the gut microbiota, through its own or interacting metabolites, has a positive role in regulating metabolic syndrome.

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Background: As the mechanism of systemic inflammatory response in the course of cancer progression is gradually revealed, research has begun to focus on the two indictors of neutrophil to lymphocyte ratio (NLR) and the platelet to lymphocyte ratio (PLR) which may be associated with clinical disease development, treatment, and prognosis in patients who are undergoing surgery, chemotherapy, targeted therapy, and immunotherapy. We aim to define the clinical application values of those two biomarkers in multiple cancers.

Methods: PubMed and Web of Science are used to perform the systematic literature research.

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Lung cancer is the leading cause of cancer-related deaths worldwide. Dysregulation of RNA binding proteins (RBPs) has been found in a variety of cancers and is related to oncogenesis and progression. However, the functions of RBPs in lung squamous cell carcinoma (LUSC) remain unclear.

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RNA binding proteins (RBPs) dysregulation have been reported in various malignant tumors and associated with the occurrence and development of cancer. However, the role of RBPs in lung adenocarcinoma (LUAD) is poorly understood. We downloaded the RNA sequencing data of LUAD from the Cancer Genome Atlas (TCGA) database and determined the differently expressed RBPs between normal and cancer tissues.

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Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC.

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Although immunotherapy has progressed in the treatment of bladder cancer, some patients still have poor prognosis. New therapeutic targets are eager to be discovered to improve the outcomes of bladder cancer. With the development of high-throughput sequencing and tumor profiling, potential tumor biomarkers were identified.

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Background: Hyperuricemia (HUA) is a metabolic disease caused by a disorder of purine metabolism, which increases the risk of cardio-cerebrovascular disease. Serum lipids and blood glucose are risk factors for metabolic syndrome. Thus, this study aimed to assess the prevalence of HUA and its relationship with serum lipids and blood glucose.

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Background: The aim of this study was to determine the association between hypertriglyceridemia and hyperuricemia (HUA).

Methods: The study was conducted in 3884 subjects who had not received medication enrolled as a baseline. Each participant received at least three annual health check-ups between 2011 and 2017.

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Background Clinical evidence indicates that genetic variations may interfere with the mechanism of drug action. Recently, it has been reported that the single nucleotide polymorphisms (SNPs) of STAT4, PTPN2, PSORS1C1 and TRAF3IP2RA genes are associated with the clinical efficacy of tumor necrosis factor (TNF) inhibitors in the treatment of rheumatoid arthritis (RA) patients. Therefore, the detection of the SNPs linked with TNF inhibitor efficacy may provide an important basis for the treatment of RA.

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Background: High-resolution melting curve analysis has been widely applied as one of the mainstream technologies used for scanning and detecting genetic mutations. After having realized the integration of PCR amplification and HRM detection on the same instrument, researchers have begun to focus on the throughput and speed of PCR-HRM detection.

Methods: A systematic literature search was conducted with the use of PubMed and ScienceDirect for articles on high resolution melting curve and microfluidic technologies.

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A total of 64 patients with β-lactam allergy and 30 control subjects were enrolled in a case-control study. This study is aimed to analyze the relationship between β-lactam allergy and 10 single nucleotide polymorphisms (SNPs) in interleukin-10 (IL-10), IL-13, IL-4Rα, high-affinity immunoglobulin E-receptor β chain (FcεRIβ), interferon γ receptor 2 (IFNGR2), and CYP3A4, and within the Han Chinese population of Northwest China. Genotyping for the SNPs was conducted using the Sequenom MassARRAY(®) platform.

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Objective: To analyze the relationship of genetic polymorphisms in IL1β, IL6, TNF-α genes and their receptors genes with rheumatoid arthritis (RA) for northwest Han Chinese. This study also explores whether there are gene-gene interactions among these genetic polymorphisms.

Methods: A total of 452 patients with RA and 373 matched healthy controls were enrolled to carry out a case-control study for 16 SNPs of IL1B-511 C>T, IL1B-31 T>C, IL1B+3954 C>T, IL1RN T>C, IL6-597 G>A, IL6-572 G>C, IL6-174 G>C, IL6R-183 G>A, IL6R exon2 T>A, IL6R exon1 A>C, TNFA-863 C>A, TNFA-857 C>T, TNFA-308 G>A, TNFA-238 G>A, TNFR1-383 A>C and TNFR2 T676G T>G from seven genes.

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Background: Previous studies suggest that a variable number of tandem repeats polymorphism in the second intron of the interleukin-1 receptor antagonist gene and two single nucleotide polymorphisms at positions -511 and +3954 of the interleukin-1beta (IL-1B) gene are associated with an increased risk of autoimmune diseases. In the present study, we evaluated associations between these genetic factors and an increased risk of rheumatoid arthritis (RA) in a population from Northwest China.

Methods: A total of 240 patients with RA and 227 healthy controls from Northwest China were investigated using PCR and PCR-restriction fragment length polymorphism.

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