Evidence map›Paper›PMID 37450404›Full record

ArticleAging2023

Predicting lifespan-extending chemical compounds for

Caio Ribeiro, Christopher K Farmer, João Pedro de Magalhães, Alex A Freitas

Abstract read
In one paragraph

Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. HarnessingSensors (Basel, Switzerland) · 2025
    Review
  4. Article
  5. Article
  6. 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

4 authors.

Caio RibeiroSchool of Computing, University of Kent, Canterbury, Kent, UK.
Christopher K FarmerCentre for Health Services Studies, University of Kent, Canterbury, Kent, UK.
João Pedro de MagalhãesGenomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK.
Alex A FreitasSchool of Computing, University of Kent, Canterbury, Kent, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/R014949/1Biotechnology and Biological Sciences Research Council BB/V007971/1Biotechnology and Biological Sciences Research Council BB/V010123/1
6 · The paper itself

Abstract

Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse data from DrugAge, a database of chemical compounds (including drugs) modulating lifespan in model organisms. To this end, we created four types of datasets for predicting whether or not a compound extends the lifespan of

Indexed as

Caenorhabditis elegansLongevityMachine LearningAgingAlgorithmsDatabases, PharmaceuticalGene OntologyGlutathioneOxidation-ReductionGlutathionefeature selectionlifespan-extension compoundslongevity drugsmachine learning

Identifiers

PMID37450404
PMCPMC10373959

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.