| Literature DB >> 23102269 |
Paul J Groot-Kormelink1, Lindsay Fawcett, Paul D Wright, Martin Gosling, Toby C Kent.
Abstract
BACKGROUND: Alveolar macrophages are one of the first lines of defence against invading pathogens and play a central role in modulating both the innate and acquired immune systems. By responding to endogenous stimuli within the lung, alveolar macrophages contribute towards the regulation of the local inflammatory microenvironment, the initiation of wound healing and the pathogenesis of viral and bacterial infections. Despite the availability of protocols for isolating primary alveolar macrophages from the lung these cells remain recalcitrant to expansion in-vitro and therefore surrogate cell types, such as monocyte derived macrophages and phorbol ester-differentiated cell lines (e.g. U937, THP-1, HL60) are frequently used to model macrophage function.Entities:
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Year: 2012 PMID: 23102269 PMCID: PMC3542584 DOI: 10.1186/1471-2172-13-57
Source DB: PubMed Journal: BMC Immunol ISSN: 1471-2172 Impact factor: 3.615
Figure 1Correlation of GPCR gene expression in alveolar macrophages in comparison to (A) PMA treated THP-1 cells (B) PMA treated HL60 cells (C) PMA treated U937 cells (D) peripheral blood monocytes and (E) monocyte derived macrophages. Expression is reported as ΔCT compared to the mean CT of the housekeeping genes and each value is the mean of ≥3 biological replicates.
Figure 2Correlation of ion channel gene expression in alveolar macrophages in comparison to (A) PMA treated THP-1 cells (B) PMA treated HL60 cells (C) PMA treated U937 cells (D) peripheral blood monocytes and (E) monocyte derived macrophages. Expression is reported as ΔCT compared to the mean CT of the housekeeping genes and each value is the mean of ≥3 biological replicates.
Figure 3Clustered heat map of ΔCvalues from GPCR arrays. Clustering of samples and of the genes to generate the heat maps was achieved using GeneSpring 11.5.1 software (Agilent Technologies Inc.). Unsupervised hierarchical clustering was carried out on genes using a Euclidean distance/similarity metric and a centroid linkage rule.
Figure 4Clustered heat map of ΔCvalues from ion channel arrays. Clustering of samples and of the genes to generate the heat maps was achieved using GeneSpring 11.5.1 software (Agilent Technologies Inc.). Unsupervised hierarchical clustering was carried out on genes using a Euclidean distance/similarity metric and a centroid linkage rule.