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Physical Activity and Diet Shape the Immune System during Aging
Abstract
With increasing age, the immune system undergoes a remodeling process, termed immunosenescence, which is accompanied by considerable shifts in leukocyte subpopulations and a decline in various immune cell functions. Clinically, immunosenescence is characterized by increased susceptibility to infections, a more frequent reactivation of latent viruses, decreased vaccine efficacy, and an increased prevalence of autoimmunity and cancer. Physiologically, the immune system has some adaptive strategies to cope with aging, while in some settings, maladaptive responses aggravate the speed of aging and morbidity. While a lack of physical activity, decreased muscle mass, and poor nutritional status facilitate immunosenescence and inflammaging, lifestyle factors such as exercise and dietary habits affect immune aging positively. This review will discuss the relevance and mechanisms of immunoprotection through physical activity and specific exercise interventions. In the second part, we will focus on the effect of dietary interventions through the supplementation of the essential amino acid tryptophan, n-3 polyunsaturated fatty acids, and probiotics (with a special focus on the kynurenine pathway).
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“moderate exercise training positively affects the composition of the T cell compartment, the function of various leukocyte subpopulations, and counteracts hallmarks of immunosenescence [250].”
From Nutrition for Older Athletes: Focus on Sex-Differences (2021) · cites this paper as [250]
In the citing paper
“While a lack of PA, decreased muscle mass, and poor nutritional status facilitate immunosenescence (namely, a decline of naïve T cells and the CD4/CD8 T-cell ratio, an increase in memory/effector T-cells and senescent/exhausted T-cells) and inflammaging (characterized by elevated levels of IL-6, TNF-α, and IL-1β)”
From Nutrition for Older Athletes: Focus on Sex-Differences (2021) · cites this paper as [250]
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Exercise sustains the hallmarks of health
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Nutrition for Older Athletes: Focus on Sex-Differences
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Self-citationKhoonin, W., Shantavasinkul, P. C., Santivarangkna, C., Praengam, K., & Trachootham, D. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1164469 · Cited by 7
Metadata
- Authors
- Weyh, C., Krüger, K., & Strasser, B.
- Venue
- Nutrients
- Publisher
- MDPI AG
- Published
- 2020-02-28
- Volume
- 12
- Issue
- 3
- Pages
- 622
- ISSN
- 2072-6643
- Cited by
- 175
- References
- 31
- Language
- en
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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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.