The DOI matches its Crossref record; 103 of the 107 references it cites were found in a registry or an index.
Markers of T Cell Senescence in Humans
Open accessAbstract
Many countries are facing the aging of their population, and many more will face a similar obstacle in the near future, which could be a burden to many healthcare systems. Increased susceptibility to infections, cardiovascular and neurodegenerative disease, cancer as well as reduced efficacy of vaccination are important matters for researchers in the field of aging. As older adults show higher prevalence for a variety of diseases, this also implies higher risk of complications, including nosocomial infections, slower recovery and sequels that may reduce the autonomy and overall quality of life of older adults. The age-related effects on the immune system termed as “immunosenescence” can be exemplified by the reported hypo-responsiveness to influenza vaccination of the elderly. T cells, which belong to the adaptive arm of the immune system, have been extensively studied and the knowledge gathered enables a better understanding of how the immune system may be affected after acute/chronic infections and how this matters in the long run. In this review, we will focus on T cells and discuss the surface and molecular markers that are associated with T cell senescence. We will also look at the implications that senescent T cells could have on human health and diseases. Finally, we will discuss the benefits of having these markers for investigators and the future work that is needed to advance the field of T cell senescence markers.
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“Some markers that are used to identify naïve and memory T cell subsets in humans such as CD45RA [352] (see section III.9 Immune senescence (aging) of human T cells) are not suitable for phenotyping murine T cell subsets, mainly because they do not allow reasonable separation in discrete positive and negative fractions.”
From Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition) (2021) · cites this paper as [352]
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“Phenotyping of naïve and memory T cell subsets by flow cytometry relies on a combination of markers that are acquired or lost during T cell differentiation, from naïve and memory to terminally differentiated T cells [352].”
From Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition) (2021) · cites this paper as [352]
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Additional file 6 of The effect of metformin on senescence of T lymphocytes
Yang, J., Liu, H.-C., Zhang, J.-Q., Zou, J.-Y., Zhang, X., Chen, W.-M., Gu, Y., & Hong, H. (2024) · Figshare · doi:10.6084/m9.figshare.26652471
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Additional file 2 of The effect of metformin on senescence of T lymphocytes
Yang, J., Liu, H.-C., Zhang, J.-Q., Zou, J.-Y., Zhang, X., Chen, W.-M., Gu, Y., & Hong, H. (2024) · Figshare · doi:10.6084/m9.figshare.24798069
Additional file 3 of The effect of metformin on senescence of T lymphocytes
Yang, J., Liu, H.-C., Zhang, J.-Q., Zou, J.-Y., Zhang, X., Chen, W.-M., Gu, Y., & Hong, H. (2024) · Figshare · doi:10.6084/m9.figshare.26652462
Tan, J. H. L., Hwang, Y. Y., Chin, H. X., Liu, M., Tan, S. Y., & Chen, Q. (2023) · Figshare · doi:10.6084/m9.figshare.24202743
Additional file 1 of The effect of metformin on senescence of T lymphocytes
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Additional file 5 of The effect of metformin on senescence of T lymphocytes
Yang, J., Liu, H.-C., Zhang, J.-Q., Zou, J.-Y., Zhang, X., Chen, W.-M., Gu, Y., & Hong, H. (2024) · Figshare · doi:10.6084/m9.figshare.26652468
Additional file 4 of The effect of metformin on senescence of T lymphocytes
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Metadata
- Authors
- Xu, W., & Larbi, A.
- Affiliations
- Agency for Science, Technology and Research (SG)
- Corresponding author
- Larbi, Anis
- ORCID
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2017-08-10
- Volume
- 18
- Issue
- 8
- Pages
- 1742
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC5578132
- OpenAlex
- W2744554795
- Cited by
- 261
- References
- 107
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 47 · 2023: 24 · 2022: 32 · 2021: 48 · 2020: 28 · 2019: 23 · 2018: 16 · 2017: 1
- FWCI
- 2.28
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- National University of Singapore (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DR-NTU (Nanyang Technological University) (submittedVersion, cc-by)
- Funders
- Graduiertenakademie, Technische Universität Dresden
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- T cell senescence, immunosenescence, T-cell markers, aging, older adults, influenza vaccination, age-related immune decline
- MeSH terms
- Immunosenescence, Aging, Cell Differentiation, Humans, T-Lymphocytes, Immunophenotyping, Cellular Senescence
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 ›
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