| Title |
Genetic programs expressed in resting and IL-4 alternatively activated mouse and human macrophages: similarities and differences
|
|---|---|
| Published in |
Blood, January 2013
|
| DOI | 10.1182/blood-2012-06-436212 |
| Pubmed ID | |
| Authors |
Fernando O. Martinez, Laura Helming, Ronny Milde, Audrey Varin, Barbro N. Melgert, Christina Draijer, Benjamin Thomas, Marco Fabbri, Anjali Crawshaw, Ling Pei Ho, Nick H. Ten Hacken, Viviana Cobos Jiménez, Neeltje A. Kootstra, Jörg Hamann, David R. Greaves, Massimo Locati, Alberto Mantovani, Siamon Gordon |
| Abstract |
The molecular repertoire of macrophages in health and disease can provide novel biomarkers for diagnosis, prognosis, and treatment. Th2-IL-4–activated macrophages (M2) have been associated with important diseases in mice, yet no specific markers are available for their detection in human tissues. Although mouse models are widely used for macrophage research, translation to the human can be problematic and the human macrophage system remains poorly described. In the present study, we analyzed and compared the transcriptome and proteome of human and murine macrophages under resting conditions (M0) and after IL-4 activation (M2). We provide a resource for tools enabling macrophage detection in human tissues by identifying a set of 87 macrophage-related genes. Furthermore, we extend current understanding of M2 activation in different species and identify Transglutaminase 2 as a conserved M2 marker that is highly expressed by human macrophages and monocytes in the prototypic Th2 pathology asthma. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | <1% |
| Spain | 4 | <1% |
| Germany | 3 | <1% |
| United States | 2 | <1% |
| Netherlands | 2 | <1% |
| Singapore | 1 | <1% |
| New Zealand | 1 | <1% |
| India | 1 | <1% |
| Australia | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 507 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 126 | 24% |
| Researcher | 109 | 21% |
| Student > Master | 53 | 10% |
| Student > Bachelor | 39 | 7% |
| Student > Doctoral Student | 30 | 6% |
| Other | 66 | 13% |
| Unknown | 103 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 133 | 25% |
| Medicine and Dentistry | 71 | 13% |
| Immunology and Microbiology | 70 | 13% |
| Biochemistry, Genetics and Molecular Biology | 66 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 19 | 4% |
| Other | 47 | 9% |
| Unknown | 120 | 23% |