ArticleHeliyon2024
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 4 citations in OpenAlex.
- Targeting the Golgi apparatus enhances PD-L1 blockade and synergizes with oxaliplatin to improve immunotherapy efficacy.The Journal of biological chemistry · 2026Article
- CCL20-CCR6 axis mediates mucosal-associated invariant T-M2 macrophage crosstalk to drive immune dysregulation in liver cirrhosis.Frontiers in immunology · 2026Article
- Association between hepatitis B virus markers and liver fibrosis staging in patients with chronic hepatitis B.World journal of gastrointestinal surgery · 2025Article
- Association Between Serum HBV DNA Levels and CCL-20, CD8a, CXCL-16, and GDF-15 in Patients with Chronic Hepatitis B.Viruses · 2025Article
- Liver fibrosis and cirrhosis in the multi-omics era: mechanisms and therapeutic perspectives from human and animal models.Frontiers in cellular and infection microbiology · 2025Review
- Comprehensive immune modulation mechanisms of Angong Niuhuang Wan in ischemic stroke: Insights from mass cytometry analysis.CNS neuroscience & therapeutics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The main cause of the liver fibrosis (LF) remains hepatitis B virus (HBV) infection, especially in China. Histologically, liver fibrosis still occurs progressively in chronic hepatitis B (CHB) patients, even if HBV-DNA is negative or undetectable. The diagnosis of LF is beneficial to control the development of it, also it may promote the reversal of LF. Although liver biopsy is the gold standard of diagnosis in LF at present, it isa traumatic diagnosis. There are no diagnostic biomarkers as yet for the condition. It is badly in need of biomarkers clinically, which is simple to test, minimally invasive, highly specific, and sensitive. Early detection of HBV-LF development is crucial in the prevention, treatment, and prognosis prediction of HBV-LF. Cytokines are closely associated with both immune regulation and inflammation in the progression of hepatitis B virus associated-liver fibrosis (HBV-LF). In this bioinformatic study, we not only analyzed the relationship between HBV-LF and immune infiltration, but also identified key genes to uncover new therapeutic targets. Objectives: To find potential biomarkers for liver fibrosis in the development of chronic hepatic B patients. Materials and methods: We obtained two sets of data including CHB/healthy control and CHB/HBV-LF from the Integrated Gene Expression (GEO) database to select for differential expression analysis. Protein-protein interaction (PPI) network was also generated, while key genes and important gene modules involved in the occurrence and development of HBV-LF were identified. These key genes were analyzed by functional enrichment analysis, module analysis, and survival analysis. Furthermore, the relationship between these two diseases and immune infiltration was explored. Results: Among the identified genes, 150 were individually associated with CHB and healthy control in the differential gene expression (DGE) analysis. While 14 with CHB and HBV-LF. It was also analyzed in the Robust rank aggregation (RRA) analysis, 34 differential genes were further identified by Cytohubba. Among 34 differential genes, two core genes were determined: Conclusion:
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.