The DOI matches its Crossref record; 151 of the 151 references it cites were found in a registry or an index.
How do Regulatory T Cells Work?
Open accessAbstract
CD4+ T cells are commonly divided into regulatory T (Treg) cells and conventional T helper (Th) cells. Th cells control adaptive immunity against pathogens and cancer by activating other effector immune cells. Treg cells are defined as CD4+ T cells in charge of suppressing potentially deleterious activities of Th cells. This review briefly summarizes the current knowledge in the Treg field and defines some key questions that remain to be answered. Suggested functions for Treg cells include: prevention of autoimmune diseases by maintaining self‐tolerance; suppression of allergy, asthma and pathogen‐induced immunopathology; feto‐maternal tolerance; and oral tolerance. Identification of Treg cells remains problematic, because accumulating evidence suggests that all the presently‐used Treg markers (CD25, CTLA‐4, GITR, LAG‐3, CD127 and Foxp3) represent general T‐cell activation markers, rather than being truly Treg‐specific. Treg‐cell activation is antigen‐specific, which implies that suppressive activities of Treg cells are antigen‐dependent. It has been proposed that Treg cells would be self‐reactive, but extensive TCR repertoire analysis suggests that self‐reactivity may be the exception rather than the rule. The classification of Treg cells as a separate lineage remains controversial because the ability to suppress is not an exclusive Treg property. Suppressive activities attributed to Treg cells may in reality, at least in some experimental settings, be exerted by conventional Th cell subsets, such as Th1, Th2, Th17 and T follicular (Tfh) cells. Recent reports have also demonstrated that Foxp3+ Treg cells may differentiate in vivo into conventional effector Th cells, with or without concomitant downregulation of Foxp3.
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
Control of Regulatory T Cell Development by the Transcription Factor Foxp3
Hori, S., Nomura, T., & Sakaguchi, S. (2003) · Science · doi:10.1126/science.1079490 · Cited by 8,187
Foxp3 programs the development and function of CD4+CD25+ regulatory T cells
Fontenot, J. D., Gavin, M. A., & Rudensky, A. Y. (2003) · Nature Immunology · doi:10.1038/ni904 · Cited by 7,745
Mosmann, T. R., Cherwinski, H., Bond, M. W., Giedlin, M. A., & Coffman, R. L. (1986) · The Journal of Immunology · doi:10.4049/jimmunol.136.7.2348 · Cited by 7,506
Park, J.-H., Adoro, S., Guinter, T., Erman, B., Alag, A. S., Catalfamo, M., Kimura, M. Y., Cui, Y., Lucas, P. J., Gress, R. E., et al. (2010) · Nature Immunology · doi:10.1038/ni.1840 · Cited by 5,835
Sakaguchi, S., Sakaguchi, N., Asano, M., Itoh, M., & Toda, M. (1995) · The Journal of Immunology · doi:10.4049/jimmunol.155.3.1151 · Cited by 5,608
Harrington, L. E., Hatton, R. D., Mangan, P. R., Turner, H., Murphy, T. L., Murphy, K. M., & Weaver, C. T. (2005) · Nature Immunology · doi:10.1038/ni1254 · Cited by 4,742
A distinct lineage of CD4 T cells regulates tissue inflammation by producing interleukin 17
Park, H., Li, Z., Yang, X. O., Chang, S. H., Nurieva, R., Wang, Y.-H., Wang, Y., Hood, L., Zhu, Z., Tian, Q., et al. (2005) · Nature Immunology · doi:10.1038/ni1261 · Cited by 4,265
A CD4+T-cell subset inhibits antigen-specific T-cell responses and prevents colitis
Groux, H., O'Garra, A., Bigler, M., Rouleau, M., Antonenko, S., de Vries, J. E., & Roncarolo, M. G. (1997) · Nature · doi:10.1038/39614 · Cited by 3,588
Bennett, C. L., Christie, J., Ramsdell, F., Brunkow, M. E., Ferguson, P. J., Whitesell, L., Kelly, T. E., Saulsbury, F. T., Chance, P. F., & Ochs, H. D. (2001) · Nature Genetics · doi:10.1038/83713 · Cited by 3,402
Shull, M. M., Ormsby, I., Kier, A. B., Pawlowski, S., Diebold, R. J., Yin, M., Allen, R., Sidman, C., Proetzel, G., Calvin, D., et al. (1992) · Nature · doi:10.1038/359693a0 · Cited by 2,985
Cited by
The Role of Macrophages in Cancer Development and Therapy
Cendrowicz, E., Sas, Z., Bremer, E., & Rygiel, T. P. (2021) · Cancers · doi:10.3390/cancers13081946 · Cited by 332
Genetics of Type 1 Diabetes: What's Next?
Pociot, F., Akolkar, B., Concannon, P., Erlich, H. A., Julier, C., Morahan, G., Nierras, C. R., Todd, J. A., Rich, S. S., & Nerup, J. (2010) · Diabetes · doi:10.2337/db10-0076 · Cited by 300
IL-17 and immunologically induced senescence regulate response to injury in osteoarthritis
Faust, H. J., Zhang, H., Han, J., Wolf, M. T., Jeon, O. H., Sadtler, K., Peña, A. N., Chung, L., Maestas, D. R., Tam, A. J., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci134091 · Cited by 260
HDAC inhibition potentiates immunotherapy in triple negative breast cancer
Terranova-Barberio, M., Thomas, S., Ali, N., Pawlowska, N., Park, J., Krings, G., Rosenblum, M. D., Budillon, A., & Munster, P. N. (2017) · Oncotarget · doi:10.18632/oncotarget.23169 · Cited by 182
Munshi, S., Loh, M. K., Ferrara, N., DeJoseph, M. R., Ritger, A., Padival, M., Record, M. J., Urban, J. H., & Rosenkranz, J. A. (2020) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2019.11.023 · Cited by 117
Metadata
- Authors
- Corthay, A.
- Venue
- Scandinavian Journal of Immunology
- Publisher
- Wiley
- Published
- 2009-09-08
- Volume
- 70
- Issue
- 4
- Pages
- 326-336
- ISSN
- 0300-9475 (ISSN-L)
- 1365-3083
- OpenAlex
- W2023214087
- Cited by
- 648
- References
- 151
- FWCI
- 12.98
- 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: How do Regulatory T Cells Work? https://app.cochat.ai/papers/10.1111/j.1365-3083.2009.02308.x
- The paper
- Corthay, A. (2009). How do Regulatory T Cells Work? Scandinavian Journal of Immunology. https://doi.org/10.1111/j.1365-3083.2009.02308.x
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.