Evidence map›Paper›PMID 35804721›Full record

ReviewFoods (Basel, Switzerland)2022

Potential Application of Living Microorganisms in the Detoxification of Heavy Metals.

Runqiu Chen, Huaijun Tu, Tingtao Chen

Open access · goldAbstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. 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

3 authors at 1 institution in 1 country.

Runqiu ChenDepartments of Geriatrics, the Second Affiliated Hospital of Nanchang University, Nanchang 330031, China.
Huaijun TuDepartments of Geriatrics, the Second Affiliated Hospital of Nanchang University, Nanchang 330031, China.
Tingtao ChenDepartments of Geriatrics, the Second Affiliated Hospital of Nanchang University, Nanchang 330031, China.ORCID 0000-0002-0506-8536
Nanchang University · CN

Funding

National Natural Science Foundation of China 514 Grant no. 82060638
6 · The paper itself

Abstract

Heavy metal (HM) exposure remains a global occupational and environmental problem that creates a hazard to general health. Even low-level exposure to toxic metals contributes to the pathogenesis of various metabolic and immunological diseases, whereas, in this process, the gut microbiota serves as a major target and mediator of HM bioavailability and toxicity. Specifically, a picture is emerging from recent investigations identifying specific probiotic species to counteract the noxious effect of HM within the intestinal tract via a series of HM-resistant mechanisms. More encouragingly, aided by genetic engineering techniques, novel HM-bioremediation strategies using recombinant microorganisms have been fruitful and may provide access to promising biological medicines for HM poisoning. In this review, we summarized the pivotal mutualistic relationship between HM exposure and the gut microbiota, the probiotic-based protective strategies against HM-induced gut dysbiosis, with reference to recent advancements in developing engineered microorganisms for medically alleviating HM toxicity.

Indexed as

dysbiosisengineered bacteriaheavy metalshuman healthmolecular techniquesprobiotics

Identifiers

PMID35804721
PMCPMC9265996
OpenAlexW4283658237

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.