Evidence map›Paper›PMID 32849340›Full record

ReviewFrontiers in microbiology2020

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review.

Dan Wang, Shan Wang, Linming Bai, Muhammad Salman Nasir, Shanshan Li, Wei Yan

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Application of the LuminescentFoods (Basel, Switzerland) · 2023
    Article
  4. Article
  5. 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

6 authors at 2 institutions in 2 countries.

Dan WangDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Shan WangDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Linming BaiDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Muhammad Salman NasirDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Shanshan LiDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Wei YanDepartment of Environmental Science and Engineering, Xi'an Jiaotong University, Shaanxi, China.
Xi'an Jiaotong University · CNUniversity of Agriculture Faisalabad · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioassays has recently brought increasing attention to overcome the environmental risks. Based on the above viewpoint, this review included a brief introduction to the occurrence and characteristics of toxic bioassay based on the luminescent bacteria. In order to assess the environmental risk of mixtures, a series of models for the prediction of the joint effect of multi-component mixtures have been summarized and discussed in-depth. Among them, Quantitative Structure-Activity Relationship (QSAR) method which was widely applied

Indexed as

joint toxicityluminescent bacteriamechanismmodelQSAR

Identifiers

PMID32849340
PMCPMC7412757
OpenAlexW3046283792

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.