ArticleFrontiers in pharmacology2022
Integrated bioinformatical and
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Artificial intelligence-based evaluation of prognosis in cirrhosis.Journal of translational medicine · 2024Review
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver cirrhosis is one of the most common cause of death in the world. The progress of liver cirrhosis involves health, liver cirrhosis and liver cancer, leading to great challenges in the diagnosis of the disease. Drug targets, which could be obtained conveniently, can help clinicians improve prognosis and treatment. Liver cirrhosis is associated with serum calcium levels. And studies reported Tanshinone IIA plays a therapeutic role in liver injury through activating calcium-dependent apoptosis. In this study, we explored the diagnostic key targets of Tanshinone IIA in liver cirrhosis through exploration of comprehensive dataset including health, liver cirrhosis and liver cancer patients. The unsupervised consensus clustering algorithm identified 3 novel subtypes in which differentially expressed genes (DEGs) between both subtypes were found by pairwise comparison. Then, 4 key drug targets of Tanshinone IIA were determined through the intersection of these DEGs. The diagnostic performance of target genes was assessed and further verified in the external dataset. We found that the 4 key drug targets could be used as effective diagnostic biomarkers. Then the immune scores in the high and low expression groups of target genes were estimated to identify significantly expressed immune cells. In addition, the immune infiltration of high and low target gene expression groups in several immune cells were significantly different. The findings suggest that 4 key drug targets may be a simple and useful diagnostic tool for predicting patients with cirrhosis. We further studied the carcinogenesis role of AKR1C3 and TPX2
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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 OpenQuestion graph.