ArticleFrontiers in microbiology2012
Comparison of sepsis-induced transcriptomic changes in a murine model to clinical blood samples identifies common response patterns.
Article in Frontiers in microbiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Beneficial Effects of O-GlcNAc Stimulation in a Young Rat Model of Sepsis: Beyond Modulation of Gene Expression.International journal of molecular sciences · 2022Article
- Endoplasmic reticulum stress and the unfolded protein response in skeletal muscle of subjects suffering from peritoneal sepsis.Scientific reports · 2022Article
- Bioinformatics Analysis Identifies TNFRSF1A as a Biomarker of Liver Injury in Sepsis TNFRSF1A is a Biomarker for Septic Liver Injury.Genetics research · 2022Article
- Liver - guardian, modifier and target of sepsis.Nature reviews. Gastroenterology & hepatology · 2017Review
- Article
- Article
- An integrated transcriptome and expressed variant analysis of sepsis survival and death.Genome medicine · 2014Article
- Hyperresponsiveness of mice deficient in plasma-secreted sphingomyelinase reveals its pivotal role in early phase of host response.Journal of lipid research · 2013Article
- Systems biology of microbial infection.Frontiers in microbiology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Experimental models, mimicking physiology, and molecular dynamics of diseases in human, harbor the possibility to study the effect of interventions and transfer results from bench to bedside. Recent advances in high-throughput technologies, standardized protocols, and integration of knowledge from databases yielded rising consistency and usability of results for inter-species comparisons. Here, we explored similarities and dissimilarities in gene expression from blood samples of a murine sepsis model (peritoneal contamination and infection, PCI) and patients from the pediatric intensive care unit (PICU) measured by microarrays. Applying a consistent pre-processing and analysis workflow, differentially expressed genes (DEG) from PCI and PICU data significantly overlapped. A major fraction of DEG was commonly expressed and mapped to adaptive and innate immune response related pathways, whereas the minor fraction, including the chemokine (C-C motif) ligand 4, exhibited constant inter-species disparities. Reproducibility of transcriptomic observations was validated experimentally in PCI. These data underline, that inter-species comparison can obtain commonly expressed transcriptomic features despite missing homologs and different protocols. Our findings point toward a high suitability of an animal sepsis model and further experimental efforts in order to transfer results from animal experiments to the bedside.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.