Evidence map›Paper›PMID 32535616›Full record

ReviewOncogene2020

The use of non-traditional models in the study of cancer resistance-the case of the naked mole rat.

Alyssa Shepard, Joseph L Kissil

Abstract readReview
PubMed Publisher
In one paragraph

Review in Oncogene, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Housing and Husbandry Alternatives for Naked Mole Rat Colonies Used in Research Settings.Journal of the American Association for Laboratory Animal Science : JAALAS · 2022
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Alternative Animal Models of Aging Research.Frontiers in molecular biosciences · 2021
    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.

Alyssa ShepardDepartment of Molecular Medicine, The Scripps Research Institute, Jupiter, FL, 33458, USA.
Joseph L KissilDepartment of Molecular Medicine, The Scripps Research Institute, Jupiter, FL, 33458, USA. jkissil@scripps.edu.ORCID http://orcid.org/0000-0002-6471-346X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-traditional model organisms are typically defined as any model the deviates from the typical laboratory animals, such as mouse, rat, and worm. These models are becoming increasingly important in human disease research, such as cancer, as they often display unusual biological features. Naked mole rats (NMRs) are currently one of the most popular non-traditional model, particularly in the longevity and cancer research fields. NMRs display an exceptionally long lifespan (~30 years), yet have been observed to display a low incidence of cancer, making them excellent candidates for understanding endogenous cancer resistance mechanisms. Over the past decade, many potential resistance mechanisms have been characterized. These include unique biological mechanisms involved in genome stability, protein stability, oxidative metabolism, and other cellular mechanisms such as cell cycle regulation and senescence. This review aims to summarize the many identified cancer resistance mechanisms to understand some of the main hypotheses that have thus far been generated. Many of these proposed mechanisms remain to be fully characterized or confirmed in vivo, giving the field a direction to grow and further understand the complex biology displayed by the NMR.

Indexed as

Disease Models, AnimalGenomic InstabilityAgingAnimalsDisease ResistanceHumansLongevityMole RatsNeoplasmsRats, Hairless

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.