Evidence map›Paper›PMID 39643761›Full record

ArticleBiogerontology2024

AcidAGE: a biological age determination neural network based on urine organic acids.

Anastasia A Kobelyatskaya, Fedor I Isaev, Anna V Kudryavtseva, Zulfiya G Guvatova, Alexey A Moskalev

Abstract read
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Article in Biogerontology, 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. Review
  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

5 authors.

Anastasia A KobelyatskayaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
Fedor I IsaevKivach Clinic, 186202, Konchezero, Republic of Karelia, Russia.
Anna V KudryavtsevaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
Zulfiya G GuvatovaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
Alexey A MoskalevPetrovsky Russian Research Center for Surgery, Institute of Longevity, Moscow, 117418, Russia. moskalev1976@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organic acids reflect the course of all important metabolic processes and the effects of diet, nutrient deficiency, lifestyle, and microbiota composition. In present work, we focused on identifying age-related changes in organic acids in urine, and creating a neural network model based on them to determine biological age. The investigation involves data on concentrations of 60 organic acids in urine of 863 samples. Due to data analysis we found these acids could be used to determine human biological age. Two models were created for calculating biological age: a comprehensive AcidAGE model and a concise AcidAGE model based on 10 indicators. Both models demonstrate high accuracy. The presented models are useful for dynamically assessing the impact of medical interventions, lifestyle and diet amendments, and taking nutraceuticals on overall health and the risk of disease occurrence or progression. Their advantage lies in their ability to quickly update estimates as the corresponding biological processes change.

Indexed as

AgingNeural Networks, ComputerAcidsAdolescentAdultAgedAged, 80 and overChildFemaleHumansMaleMiddle AgedModels, BiologicalYoung AdultAcidsBiological ageMetabolismNeural networkOrganic acids

Identifiers

PMID39643761

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.