The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Combinatorial Single-Cell Analyses of Granulocyte-Monocyte Progenitor Heterogeneity Reveals an Early Uni-potent Neutrophil Progenitor
Open accessAbstract
Granulocyte-monocyte progenitors (GMPs) have been previously defined for their potential to generate various myeloid progenies such as neutrophils and monocytes. Although studies have proposed lineage heterogeneity within GMPs, it is unclear if committed progenitors already exist among these progenitors and how they may behave differently during inflammation. By combining single-cell transcriptomic and proteomic analyses, we identified the early committed progenitor within the GMPs responsible for the strict production of neutrophils, which we designate as proNeu1. Our dissection of the GMP hierarchy led us to further identify a previously unknown intermediate proNeu2 population. Similar populations could be detected in human samples. proNeu1s, but not proNeu2s, selectively expanded during the early phase of sepsis at the expense of monocytes. Collectively, our findings help shape the neutrophil maturation trajectory roadmap and challenge the current definition of GMPs.
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
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
(2008) · Journal of Machine Learning Research · Cited by 33,051
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
Dimensionality reduction for visualizing single-cell data using UMAP
Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358
Self-citationReversed graph embedding resolves complex single-cell trajectories
Qiu, X., Mao, Q., Tang, Y., Wang, L., Chawla, R., Pliner, H. A., & Trapnell, C. (2017) · Nature Methods · doi:10.1038/nmeth.4402 · Cited by 5,070
Full-length RNA-seq from single cells using Smart-seq2
Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137
Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
The Tabula Muris Consortium, coordination, O., coordination, L., processing, O. C. A., sequencing, L. P. A., analysis, C. D., annotation, C. T., Writing group, Supplemental text writing group, & Principal investigators (2018) · Nature · doi:10.1038/s41586-018-0590-4 · Cited by 2,842
Cited by
Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment
Schulte-Schrepping, J., Reusch, N., Paclik, D., Baßler, K., Schlickeiser, S., Zhang, B., Krämer, B., Krammer, T., Brumhard, S., Bonaguro, L., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.001 · Cited by 1,461
Neutrophils in cancer: heterogeneous and multifaceted
Hedrick, C. C., & Malanchi, I. (2022) · Nature Reviews Immunology · doi:10.1038/s41577-021-00571-6 · Cited by 768
Burn, G. L., Foti, A., Marsman, G., Patel, D. F., & Zychlinsky, A. (2021) · Immunity · doi:10.1016/j.immuni.2021.06.006 · Cited by 729
Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)
Cossarizza, A., Chang, H., Radbruch, A., Abrignani, S., Addo, R., Akdis, M., Andrä, I., Andreata, F., Annunziato, F., Arranz, E., et al. (2021) · European Journal of Immunology · doi:10.1002/eji.202170126 · Cited by 531
Self-citationA neutrophil response linked to tumor control in immunotherapy
Gungabeesoon, J., Gort-Freitas, N. A., Kiss, M., Bolli, E., Messemaker, M., Siwicki, M., Hicham, M., Bill, R., Koch, P., Cianciaruso, C., et al. (2023) · Cell · doi:10.1016/j.cell.2023.02.032 · Cited by 412
Metadata
- Authors
- Kwok, I., Becht, E., Xia, Y., Ng, M., Teh, Y. C., Tan, L., Evrard, M., Li, J. L. Y., Tran, H. T. N., Tan, Y., Liu, D., Mishra, A., Liong, K. H., Leong, K., Zhang, Y., Olsson, A., Mantri, C. K., Shyamsunder, P., Liu, Z., Piot, C., Dutertre, C.-A., Cheng, H., Bari, S., Ang, N., Biswas, S. K., Koeffler, H. P., Tey, H. L., Larbi, A., Su, I.-H., Lee, B., St. John, A., Chan, J. K. Y., Hwang, W. Y. K., Chen, J., Salomonis, N., Chong, S. Z., Grimes, H. L., Liu, B., Hidalgo, A., Newell, E. W., Cheng, T., Ginhoux, F., & Ng, L. G.
- Venue
- Immunity
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 53
- Issue
- 2
- Pages
- 303-318.e5
- ISSN
- 1074-7613 (ISSN-L)
- OpenAlex
- W3035965283
- Cited by
- 264
- References
- 45
- FWCI
- 9.89
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Combinatorial Single-Cell Analyses of Granulocyte-Monocyte Progenitor Heterogeneity Reveals an Early Uni-potent Neutrophil Progenitor. https://app.cochat.ai/papers/10.1016/j.immuni.2020.06.005
- The paper
- Kwok, I., Becht, E., Xia, Y., Ng, M., Teh, Y. C., Tan, L., Evrard, M., Li, J. L. Y., Tran, H. T. N., Tan, Y., Liu, D., Mishra, A., Liong, K. H., Leong, K., Zhang, Y., Olsson, A., Mantri, C. K., Shyamsunder, P., Liu, Z., . . . Ng, L. G. (2020). Combinatorial Single-Cell Analyses of Granulocyte-Monocyte Progenitor Heterogeneity Reveals an Early Uni-potent Neutrophil Progenitor. Immunity. https://doi.org/10.1016/j.immuni.2020.06.005
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.