Evidence map›Paper›PMID 28694875›Full record

ArticleGenes & nutrition2017

Diet-derived microRNAs: unicorn or silver bullet?

Kenneth W Witwer, Chen-Yu Zhang

Open access · goldAbstract read
In one paragraph

Article in Genes & nutrition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

27 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. The Conundrum of XenomiRs and Human Health.Advances in nutrition (Bethesda, Md.) · 2025
    Review
  5. Review
  6. Review
  7. Looking for Plant microRNAs in Human Blood Samples: Bioinformatics Evidence and Perspectives.Plant foods for human nutrition (Dordrecht, Netherlands) · 2023
    Article
  8. Article
  9. Extracellular Vesicles-Oral Therapeutics of the Future.International journal of molecular sciences · 2022
    Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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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 at 2 institutions in 2 countries.

Kenneth W WitwerDepartments of Molecular and Comparative Pathobiology and Neurology, Johns Hopkins University, Baltimore, USA.ORCID 0000-0003-1664-4233
Chen-Yu ZhangJiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Johns Hopkins University · USNanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In ancient lore, a bullet cast from silver is the only effective weapon against monsters. The uptake of active diet-derived microRNAs (miRNAs) in consumers may be the silver bullet long sought after in nutrition and oral therapeutics. However, the majority of scientists consider the transfer and regulation of consumer's gene activity by these diet-derived miRNAs to be a fantasy akin to spotting a unicorn. Nevertheless, groups like Dr. Chen-Yu Zhang's lab in Nanjing University have stockpiled breathtaking amounts of data to shoot down these naysayers. Meanwhile, Dr. Ken Witwer at John Hopkins has steadfastly cautioned the field to beware of fallacies caused by contamination, technical artifacts, and confirmation bias. Here, Dr. Witwer and Dr. Zhang share their realities of dietary miRNAs by answering five questions related to this controversial field.

Indexed as

BiotechnologyCross-kingdomDietGenetically engineeredMicrobiomemiRNAPlansRNA

Identifiers

PMID28694875
PMCPMC5501113
OpenAlexW2623957922

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.