SynthesisMolecular medicine reports2017
Personalized identification of differentially expressed pathways in pediatric sepsis.
Synthesis in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Pediatric Sepsis.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Precision medicine in pediatric sepsis.Current opinion in pediatrics · 2019Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis is a leading killer of children worldwide with numerous differentially expressed genes reported to be associated with sepsis. Identifying core pathways in an individual is important for understanding septic mechanisms and for the future application of custom therapeutic decisions. Samples used in the study were from a control group (n=18) and pediatric sepsis group (n=52). Based on Kauffman's attractor theory, differentially expressed pathways associated with pediatric sepsis were detected as attractors. When the distribution results of attractors are consistent with the distribution of total data assessed using support vector machine, the individualized pathway aberrance score (iPAS) was calculated to distinguish differences. Through attractor and Kyoto Encyclopedia of Genes and Genomes functional analysis, 277 enriched pathways were identified as attractors. There were 81 pathways with P<0.05 and 59 pathways with P<0.01. Distribution outcomes of screened attractors were mostly consistent with the total data demonstrated by the six classifying parameters, which suggested the efficiency of attractors. Cluster analysis of pediatric sepsis using the iPAS method identified seven pathway clusters and four sample clusters. Thus, in the majority pediatric sepsis samples, core pathways can be detected as different from accumulated normal samples. In conclusion, a novel procedure that identified the dysregulated attractors in individuals with pediatric sepsis was constructed. Attractors can be markers to identify pathways involved in pediatric sepsis. iPAS may provide a correlation score for each of the signaling pathways present in an individual patient. This process may improve the personalized interpretation of disease mechanisms and may be useful in the forthcoming era of personalized medicine.
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