Evidence map›Paper›PMID 40471388›Full record

ArticleMolecular genetics and genomics : MGG2025

Transcriptional characterization of sepsis in a LPS porcine model.

Ryan Neill

RetractedAbstract readRetracted Publication
PubMed Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Ryan NeillMayo Clinic Graduate School of Biomedical Sciences, Scottsdale, AZ, USA. ryan.neill@gwmail.gwu.edu.ORCID http://orcid.org/0009-0001-9167-9367

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper identifies gene candidates differentially expressed in the porcine brain during sepsis, designed for eventual application in human clinical care for earlier detection of sepsis, as no known biomarkers currently exist. Sepsis associated encephalopathy (SAE) is characterized by dysregulated molecular pathways of the immune response impinging upon normal central nervous system (CNS) function and ultimately resulting in lasting cognitive and behavioral impairments. This study seeks to identify gene candidates that exhibit altered transcriptional expression during sepsis. Twelve Yorkshire pigs (n = 6 for saline control and lipopolysaccharide group) were utilized. LPS injection rate was 0.5-0.75 mL/kg resulting in death within 5-10 h. Brain tissue was collected and analyzed via bulk RNA-seq, and corresponding computational genomic analysis. Multiple genes demonstrated significant differential expression in the early septic brain, correlating with endothelial cell disruption, immune/inflammatory alterations, and potential alterations in microglia. Gene candidates downregulated include: OCLN, SLC19A3, and SLC52A3. Genes upregulated include: ICAM1, IRF1, CXCL10, and ZFP36. Specific gene candidates were identified as early changes in the septic brain that could be targets to prevent long-term cognitive and behavioral changes seen in sepsis survivors and establish a baseline diagnostic panel to interrogate in animal models with the goal of advancing treatments for human patients who experience sepsis.

Indexed as

SepsisSepsis-Associated EncephalopathyAnimalsBrainChemokine CXCL10Disease Models, AnimalGene Expression ProfilingGene Expression RegulationIntercellular Adhesion Molecule-1Interferon Regulatory Factor-1LipopolysaccharidesSwineTranscriptomeChemokine CXCL10Intercellular Adhesion Molecule-1Interferon Regulatory Factor-1LipopolysaccharidesComputational genomicsNeurodegenerationNeuroinflammationPig modelRNA sequencingSepsis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.