Evidence map›Paper›PMID 29671083›Full record

ArticleAMB Express2018

Modeling photocatalytic degradation of diazinon from aqueous solutions and effluent toxicity risk assessment using Escherichia coli LMG 15862.

Ali Toolabi, Mohammad Malakootian, Mohammad Taghi Ghaneian, Ali Esrafili, Mohammad Hassan Ehrampoush, Mohsen AskarShahi, Maesome Tabatabaei

Abstract read
In one paragraph

Article in AMB Express, 2018. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

7 authors.

Ali ToolabiEnvironmental Science and Technology Research Center, Department of Environmental Health Engineering, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Mohammad MalakootianEnvironmental Health Engineering Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Mohammad Taghi GhaneianEnvironmental Science and Technology Research Center, Department of Environmental Health Engineering, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. mtghaneian@yahoo.com.
Ali EsrafiliDepartment of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Mohammad Hassan EhrampoushEnvironmental Science and Technology Research Center, Department of Environmental Health Engineering, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Mohsen AskarShahiDepartment of Biostatistics and Epidemiology, Shahid Sadoughi University of Medical Science, Yazd, Iran.
Maesome TabatabaeiDepartment of chemistry, Islamic Azad University, Yazd, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, modeling and degradation of diazinon from contaminated water by advanced oxidation process together with a new test for effluent bioassay using E. coli were investigated. The experiments were designed based on response surface methodology. Nanoparticles (NPs) were synthesized using the sol-gel method. The shape characteristics and specifications of elements in the nanoparticles were characterized using scanning electron microscope and energy dispersive X-ray, respectively. Diazinon was measured using high performance liquid chromatography device and by-products due to its decomposition were identified by gas chromatography-mass (GC-MS). In the present study, effluent bioassay tests were conducted by defining the rate of dehydrogenase enzyme reducing alamar blue method. According to statistical analyses (R

Indexed as

Dehydrogenase enzymeDiazinonEffluent bioassayModeling

Identifiers

PMID29671083
PMCPMC5906421

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.