Evidence map›Paper›PMID 39583307›Full record

ArticlePhenomics (Cham, Switzerland)2024

True Ageing: An Up-to-date Model for Evaluating the Immune Age of the Chinese Population.

Hao Cheng, Bin Li

Abstract read
In one paragraph

Article in Phenomics (Cham, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hao ChengDepartment of Rheumatism and Immunology, Peking University Shenzhen Hospital, Guangdong, 518036 China.ORCID 0000-0002-5091-3874
Bin LiCenter for Immune-Related Diseases, Shanghai Institute of Immunology, Department of Respiratory and Critical Care Medicine of Ruijin Hospital, Department of Thoracic Surgery of Ruijin Hospital, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025 China.ORCID 0000-0002-7640-8884

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pursuit of immortality has always been a long-standing aspiration of humanity. However, with increasing age comes the unexpected onset of aging. Although time is impartial, the process of ageing lacks uniformity. The human immune system changes with age and immune ageing significantly weakens an individual's resistance against various pathogens and cancer cells while simultaneously elevating the risk of immune disorders and chronic inflammation. Consequently, individuals who share the same chronological age may exhibit varying disease-fighting abilities. The substantial inter-individual variability underscores the imperative of precise monitoring to investigate the progressive alterations experienced by the immune system during ageing. Actually, numerous studies have focused on the changes in different lymphocyte subsets in diseases and immuno-senescence. However, quantitatively assessing host immunity remains a challenge, a comprehensive analysis of the alterations in both lymphocyte number and phenotype alterations induced by ageing remains lacking in China. Previous studies have primarily focused on the phenotypic changes in immune subsets during ageing, often utilizing a limited control cohort or lacking appropriate age-matched controls. Therefore, the standard immune markers and immune age evaluation model tailored to the Chinese population were currently needed. In a recent study, Jia et al. conducted a comprehensive investigation on a large-scale healthy Chinese cohort and successfully developed the first and largest immune age prediction model specifically tailored for the Chinese population. Here, we discussed this immune age evaluation model for the Chinese population and gave some suggestions for further improvement.

Indexed as

AgeingChinese PopulationImmune ageNK cellsT cellsγδ T cells

Identifiers

PMID39583307
PMCPMC11584808

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.