Evidence map›Paper›PMID 32509998›Full record

ReviewHeliyon2020

Aging - Oxidative stress, antioxidants and computational modeling.

Umm-E-Ammara Warraich, Fatma Hussain, Haroon Ur Rashid Kayani

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 2 pooled it
10.8field-weighted citation impact, top 1% 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

88 citing papers in PubMed, 2 syntheses or guidelines pooled it, 202 citations in OpenAlex.

  1. Pooled it
  2. Polysaccharides fromMolecules (Basel, Switzerland) · 2024
    Pooled it
  3. Trial
  4. Review
  5. [Deep learning-driven high-frequency ultrasound method for skin aging assessment].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    Article
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  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
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  17. Review
  18. International journal of molecular sciences · 2025
    Article
  19. Review
  20. Article

28 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 1 country.

Umm-E-Ammara WarraichDepartment of Biochemistry, Faculty of Sciences, University of Agriculture, Faisalabad, Pakistan.
Fatma HussainDepartment of Biochemistry, Faculty of Sciences, University of Agriculture, Faisalabad, Pakistan.
Haroon Ur Rashid KayaniDepartment of Software Engineering, Lahore Garrison University, Lahore, Pakistan.
University of Agriculture Faisalabad · PKLahore Garrison University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is a degenerative, biological, time-dependent, universally conserved process thus designed as one of the highest known risk factors for morbidity and mortality. Every individual has its own aging mechanisms as both environmental conditions (75%) and genetics (25%) account for aging. Several theories have been proposed until now but not even a single theory solves this mystery. There are still some queries un-answered to the scientific community regarding mechanisms behind aging. However, oxidative stress theory (OST) is considered one of the famous theories that sees mitochondria as one of the leading organelles which largely contribute to the aging process. Many reactive oxygen species (ROS) are produced endogenously and exogenously that are associated with aging. But the mitochondrial ROS contribute largely to the aging process as mitochondrial dysfunction due to oxidative stress is considered one of the contributors toward aging. Although ROS is known to damage cell machinery, new evidence suggests their role in signal transduction to regulate biological and physiological processes. Moreover, besides mitochondria, other important cell organelles such as peroxisome and endoplasmic reticulum also produce ROS that contribute to aging. However, nature has provided humans with free radical scavengers called antioxidants that protect from harmful effects of ROS. Future predictions regarding aging, biochemical mechanisms involved, biomarkers internal and external factors can be easily done with machine learning algorithms and other computational models. This review explains important aspects of aging, the contribution of ROS producing organelles in aging, importance of antioxidants fighting against ROS, different computational models developed to understand the complexities of the aging.

Indexed as

AntioxidantsBiochemistryBioinformaticsBiological sciencesComputer modelsMitochondriaPharmaceutical scienceReactive oxygen species

Identifiers

PMID32509998
PMCPMC7264715
OpenAlexW3029360938

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.