Evidence map›Paper›PMID 35098992›Full record

ReviewThe Biochemical journal2022

Systems approaches to investigate the role of NF-κB signaling in aging.

Masatoshi Haga, Mariko Okada

Open access · hybridAbstract readReview
In one paragraph

Review in The Biochemical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
5.5field-weighted citation impact, top 3% of its field
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

39 citing papers in PubMed, 62 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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 at 2 institutions in 1 country.

Masatoshi HagaLaboratory for Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.
Mariko OkadaLaboratory for Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.ORCID 0000-0002-6210-8223
National Institute of Biomedical Innovation, Health and Nutrition · JPRohto Pharmaceutical (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The nuclear factor-κB (NF-κB) signaling pathway is one of the most well-studied pathways related to inflammation, and its involvement in aging has attracted considerable attention. As aging is a complex phenomenon and is the result of a multi-step process, the involvement of the NF-κB pathway in aging remains unclear. To elucidate the role of NF-κB in the regulation of aging, different systems biology approaches have been employed. A multi-omics data-driven approach can be used to interpret and clarify unknown mechanisms but cannot generate mechanistic regulatory structures alone. In contrast, combining this approach with a mathematical modeling approach can identify the mechanistics of the phenomena of interest. The development of single-cell technologies has also helped clarify the heterogeneity of the NF-κB response and underlying mechanisms. Here, we review advances in the understanding of the regulation of aging by NF-κB by focusing on omics approaches, single-cell analysis, and mathematical modeling of the NF-κB network.

Indexed as

AgingAnimalsCellular SenescenceHumansInflammationKineticsModels, TheoreticalNF-kappa BSignal TransductionSingle-Cell AnalysisSystems BiologyTranscriptomeNF-kappa Bagingmathematical modelnuclear factor kappa Bsystems biologytranscription factors

Identifiers

PMID35098992
PMCPMC8883486
OpenAlexW4210335358

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.