Evidence map›Paper›PMID 39954244›Full record

ReviewAging cell2025

Exploring Lymph Node Stroma Ageing: Immune Implications and Future Directions.

Yu Yang Ng, Andy Tay

Abstract readReview
In one paragraph

Review in Aging cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Immune responses in aging adults.The Journal of clinical investigation · 2026
    Review
  3. Article
  4. The spleen-brain axis in Alzheimer's disease and related dementias: Integrating immune and metabolic regulation.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  5. Article
  6. Article
  7. Review
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.

Yu Yang NgDepartment of Biomedical Engineering, National University of Singapore, Singapore City, Singapore.ORCID 0000-0003-2795-1423
Andy TayDepartment of Biomedical Engineering, National University of Singapore, Singapore City, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ageing is an inevitable biological process that impacts the immune system, leading to immunosenescence and inflammaging, which contribute to increased susceptibility to infections, autoimmune diseases and cancers in individuals over the age of 65. This review focuses on the ageing of lymph node stromal cells (LNSCs), which are crucial for maintaining lymph node (LN) structure and function. Age-related changes in LNs, such as fibrosis and lipomatosis, disrupt the LN architecture and reduce immune cell recruitment and function, impairing immune responses to infections and vaccinations. The review discusses the structural and functional decline of various LNSC subsets, including fibroblastic reticular cells (FRCs), lymphatic endothelial cells (LECs) and blood endothelial cells (BECs), highlighting their roles in immune cell activation and homeostasis. Potential strategies to restore aged LNSC function, such as enhancing LNSC activation during vaccination and using senotherapeutics, are explored. Outstanding questions regarding the mechanisms of LNSC ageing and how ageing of the LN stroma might impact autoimmune disorders are also addressed. This review aims to stimulate further research into the characterisation of aged LNSCs and the development of therapeutic interventions to improve immune function in the older adults.

Indexed as

AgingLymph NodesStromal CellsAnimalsHumansageingimmunityinfectionslymph nodestromal cells

Identifiers

PMID39954244
PMCPMC11896299

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.