ArticleBMC genomics2007
Temporal dynamics of gene expression in the lung in a baboon model of E. coli sepsis.
Article in BMC genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 28 citations in OpenAlex.
- Quantifying pathway perturbations based on gene network rewiring in sepsis progression toward death or survival.Frontiers in bioinformatics · 2026Article
- Sex-Specific Alterations of the Lung Transcriptome at Birth in Mouse Offspring Prenatally Exposed to Vanilla-Flavored E-Cigarette Aerosols and Enhanced Susceptibility to Asthma.International journal of environmental research and public health · 2023Article
- Laminar Inflammation Responses in the Oligofructose Overload Induced Model of Bovine Laminitis.Frontiers in veterinary science · 2020Article
- Extensive Changes in Transcriptomic "Fingerprints" and Immunological Cells in the Large Organs of Patients Dying of Acute Septic Shock and Multiple Organ Failure Caused byFrontiers in cellular and infection microbiology · 2020Article
- Dysregulated activities of proline-specific enzymes in septic shock patients (sepsis-2).PloS one · 2020Article
- In vivo-generated thrombin and plasmin do not activate the complement system in baboons.Blood · 2017Article
- Host responses to concurrent combined injuries in non-human primates.Journal of inflammation (London, England) · 2017Article
- Complement inhibition decreases early fibrogenic events in the lung of septic baboons.Journal of cellular and molecular medicine · 2015Article
- Article
- Acute lung injury and fibrosis in a baboon model of Escherichia coli sepsis.American journal of respiratory cell and molecular biology · 2014Article
- Pathophysiology, staging and therapy of severe sepsis in baboon models.Journal of cellular and molecular medicine · 2012Review
- Article
- Characterizing gene expressions based on their temporal observations.Journal of biomedicine & biotechnology · 2009Article
- Laudatio to professor Fletcher B. Taylor.Journal of cellular and molecular medicine · 2008Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundBacterial invasion during sepsis induces disregulated systemic responses that could lead to fatal lung failure. The purpose of this study was to relate the temporal dynamics of gene expression to the pathophysiological changes in the lung during the first and second stages of E. coli sepsis in baboons.
resultsUsing human oligonucleotide microarrays, we have explored the temporal changes of gene expression in the lung of baboons challenged with sublethal doses of E. coli. Temporal expression pattern and biological significance of the differentially expressed genes were explored using clustering and pathway analysis software. Expression of selected genes was validated by real-time PCR. Cytokine levels in tissue and plasma were assayed by multiplex ELISA. Changes in lung ultrastructure were visualized by electron microscopy. We found that genes involved in primary inflammation, innate immune response, and apoptosis peaked at 2 hrs. Inflammatory and immune response genes that function in the stimulation of monocytes, natural killer and T-cells, and in the modulation of cell adhesion peaked at 8 hrs, while genes involved in wound healing and functional recovery were upregulated at 24 hrs.
conclusionThe analysis of gene expression modulation in response to sepsis provides the baseline information that is crucial for the understanding of the pathophysiology of systemic inflammation and may facilitate the development of future approaches for sepsis therapy.
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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.