Evidence map›Paper›PMID 34075054›Full record

ReviewNPJ science of food2021

Advances in 3D peptide hydrogel models in cancer research.

Jingwen Xu, Guangyan Qi, Weiqun Wang, Xiuzhi Susan Sun

Erratum issuedAbstract readReview
In one paragraph

Review in NPJ science of food, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Advanced Hydrogels in Breast Cancer Therapy.Gels (Basel, Switzerland) · 2024
    Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Engineering complexity in human tissue models of cancer.Advanced drug delivery reviews · 2022
    Review
  18. Review
  19. Bacterial Nanocellulose as a Scaffold forNanomaterials (Basel, Switzerland) · 2021
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jingwen XuCollege of Food Science and Technology, Shanghai Ocean University, Shanghai, China.ORCID http://orcid.org/0000-0003-1683-5662
Guangyan QiDepartment of Grain Science and Industry, Kansas State University, Manhattan, KS, USA.
Weiqun WangDepartment of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA.ORCID http://orcid.org/0000-0002-1295-8246
Xiuzhi Susan SunDepartment of Grain Science and Industry, Kansas State University, Manhattan, KS, USA. xss@ksu.edu.ORCID http://orcid.org/0000-0002-1207-9380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In vitro cell culture models on monolayer surfaces (2D) have been widely adapted for identification of chemopreventive food compounds and food safety evaluation. However, the low correlation between 2D models and in vivo animal models has always been a concern; this gap is mainly caused by the lack of a three-dimensional (3D) extracellular microenvironment. In 2D models, cell behaviors and functionalities are altered, resulting in varied responses to external conditions (i.e., antioxidants) and hence leading to low predictability. Peptide hydrogel 3D scaffolding technologies, such as PGmatrix for cell culture, have been recently reported to grow organoid-like spheroids physiologically mimicking the 3D microenvironment that can be used as an in vitro 3D model for investigating cell activities, which is anticipated to improve the prediction rate. Thus, this review focuses on advances in 3D peptide hydrogels aiming to introduce 3D cell culture tools as in vitro 3D models for cancer-related research regarding food safety and nutraceuticals.

Identifiers

PMID34075054
PMCPMC8169659

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.