The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset
Abstract
Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16−, intermediate CD14++CD16+, and nonclassical CD14+CD16++ monocytes. Current knowledge on human monocyte heterogeneity is still incomplete: while it is increasingly acknowledged that CD14++CD16+ monocytes are of outstanding significance in 2 global health issues, namely HIV-1 infection and atherosclerosis, CD14++CD16+ monocytes remain the most poorly characterized subset so far. We therefore developed a method to purify the 3 monocyte subsets from human blood and analyzed their transcriptomes using SuperSAGE in combination with high-throughput sequencing. Analysis of 5 487 603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the 2 other monocyte subsets. Gene Ontology (GO) enrichment analysis suggests diverse immunologic functions, linking CD14++CD16+ monocytes to Ag processing and presentation (eg, CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (eg, TGFB1, AIF1, PTPN6), and to angiogenesis (eg, TIE2, CD105). In conclusion, we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity. After CD14++CD16+ monocytes have earlier been discussed as a potential therapeutic target in inflammatory diseases, we are hopeful that our data will spur further research in the field of monocyte heterogeneity.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Expression of Tie-2 by Human Monocytes and Their Responses to Angiopoietin-2
Murdoch, C., Tazzyman, S., Webster, S., & Lewis, C. E. (2007) · The Journal of Immunology · doi:10.4049/jimmunol.178.11.7405 · Cited by 318
Cited by
From Monocytes to M1/M2 Macrophages: Phenotypical vs. Functional Differentiation
Italiani, P., & Boraschi, D. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00514 · Cited by 2,067
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells
Ramsköld, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O. R., Daniels, G. A., Khrebtukova, I., Loring, J. F., Laurent, L. C., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2282 · Cited by 1,609
Developmental and Functional Heterogeneity of Monocytes
Guilliams, M., Mildner, A., & Yona, S. (2018) · Immunity · doi:10.1016/j.immuni.2018.10.005 · Cited by 973
Mildner, A., Schönheit, J., Giladi, A., David, E., Lara-Astiaso, D., Lorenzo-Vivas, E., Paul, F., Chappell-Maor, L., Priller, J., Leutz, A., et al. (2017) · Immunity · doi:10.1016/j.immuni.2017.04.018 · Cited by 317
Metcalf, T. U., Wilkinson, P. A., Cameron, M. J., Ghneim, K., Chiang, C., Wertheimer, A. M., Hiscott, J. B., Nikolich-Zugich, J., & Haddad, E. K. (2017) · The Journal of Immunology · doi:10.4049/jimmunol.1700148 · Cited by 166
Metadata
- Authors
- Zawada, A. M., Rogacev, K. S., Rotter, B., Winter, P., Marell, R.-R., Fliser, D., & Heine, G. H.
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2011-09-22
- Volume
- 118
- Issue
- 12
- Pages
- e50-e61
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- OpenAlex
- W2013873031
- Cited by
- 560
- References
- 1
- FWCI
- 15.22
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset. https://app.cochat.ai/papers/10.1182/blood-2011-01-326827
- The paper
- Zawada, A. M., Rogacev, K. S., Rotter, B., Winter, P., Marell, R.-R., Fliser, D., & Heine, G. H. (2011). SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset. Blood. https://doi.org/10.1182/blood-2011-01-326827
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.