Evidence map›Paper›PMID 37026499›Full record

ReviewCurrent molecular medicine2024

Metabolomics to Study Human Aging: A Review.

Claudia Martins, Sandra Magalhães, Idália Almeida, Vanessa Neto, Sandra Rebelo, Alexandra Nunes

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Claudia MartinsDepartment of Medical Sciences, iBiMED: Institute of Biomedicine, University of Aveiro, Agra do Crasto, Aveiro 3810-193, Portugal.
Sandra MagalhãesDepartment of Surgery and Physiology, Faculty of Medicine, UnIC@RISE, Cardiovascular Research & Development Centre, University of Porto, Alameda Prof. Hernâni Monteiro, Porto 4200-319, Portugal.
Idália AlmeidaDepartment of Medical Sciences, iBiMED: Institute of Biomedicine, University of Aveiro, Agra do Crasto, Aveiro 3810-193, Portugal.
Vanessa NetoDepartment of Medical Sciences, iBiMED: Institute of Biomedicine, University of Aveiro, Agra do Crasto, Aveiro 3810-193, Portugal.
Sandra RebeloDepartment of Medical Sciences, iBiMED: Institute of Biomedicine, University of Aveiro, Agra do Crasto, Aveiro 3810-193, Portugal.
Alexandra NunesDepartment of Medical Sciences, iBiMED: Institute of Biomedicine, University of Aveiro, Agra do Crasto, Aveiro 3810-193, Portugal.

Funding

Institute of Biomedicine (iBiMED)-UIDP/04501/2020 and UIDB/04501/2020,
6 · The paper itself

Abstract

In the last years, with the increase in the average life expectancy, the world's population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

Indexed as

AgingBiomarkersMetabolomicsAnimalsCellular SenescenceHumansBiomarkersAginganimal modelsbiomarkers of senescence.cellular modelsmetabolomicssenescence

Identifiers

What OpenQuestion holds

Textmetadata
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.