Evidence map›Paper›PMID 34041401›Full record

ArticleHeliyon2021

Evaluation of some biological parameters of gasoline station attendants in Damascus, Syria.

Mohammad Alses, Samar Alzeer

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Mohammad AlsesDepartment of Pharmacology and Toxicology, Faculty of Pharmacy, University of Damascus, Damascus, Syria.
Samar AlzeerDepartment of Pharmacology and Toxicology, Faculty of Pharmacy, University of Damascus, Damascus, Syria.
Damascus University · SY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGasoline is a blend of organic compounds used in internal combustion engines. gasoline station attendants (GSA) are exposed to gasoline vapours, which promotes oxidative stress through the production of ROS, which can damage biological structures with the formation of new metabolites which can be used as markers of oxidant/antioxidant imbalance. This is a comparative cross-sectional study. This study aims to evaluate some biological parameters as indicators of toxicity as a result of exposure to gasoline in workers at gas stations in Damascus.

methodsBlood samples were collected from GSA (n = 30) and non-exposed (NE) (n = 30) with no history of occupational exposure, and the following markers of oxidative stress were analysed: malondialdehyde (MDA), advanced oxidation protein products (AOPP), catalase activity (CAT), CBC, ALT and AST.

resultsWe have found that the levels of MDA, AOPP, CAT, RBC and Hgb in GSA were significantly higher than NE (p = 0.000, p = 0.02, p = 0.002, p = 0.018 and p = 0.015 respectively). On the other hand, there were no statistically significant (p > 0.05) in HCT, MCV, WBC, PLT, ALT and AST between the two groups. In the GSA group, there was no effect of the smoking habit and the number of years of work on biological parameters, but alcohol consumption habit had a clear effect on increasing both levels of MDA and CAT (

conclusionsthe early identification of these biomarkers can be very useful to promote programs on health protection and prevention for those populations more susceptible to the adverse effects of gasoline exposure.

Indexed as

GasolineHaematologicalHepatic functionsOxidative stress

Identifiers

PMID34041401
PMCPMC8144008
OpenAlexW3162828670

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.