Evidence map›Paper›PMID 30229098›Full record

ArticleData in brief2018

Protein carbonylation detection methods: A comparison.

Esra'a Alomari, Stefano Bruno, Luca Ronda, Gianluca Paredi, Stefano Bettati, Andrea Mozzarelli

Abstract read
In one paragraph

Article in Data in brief, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

6 authors.

Esra'a AlomariDepartment of Food and Drug, University of Parma, Parma, Italy.
Stefano BrunoDepartment of Food and Drug, University of Parma, Parma, Italy.
Luca RondaDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Gianluca ParediDepartment of Food and Drug, University of Parma, Parma, Italy.
Stefano BettatiDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Andrea MozzarelliDepartment of Food and Drug, University of Parma, Parma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The data reported here are a comparison among four different methods for the detection of carbonylated proteins, a validated biomarker of oxidative stress. The reference samples were heart and kidney extracts of Guinea pigs transfused with hemoglobin-based oxygen carriers (Alomari et al. FRBM, [11]). We measured the carbonyl content of organ extracts by using i) the Levine spectrophotometric method, which takes advantage of the chromogenic reaction of carbonyl groups with 2,4-dinitrophenylhydrazine (DNPH), ii) a commercially available ELISA assay based on an anti-DNPH antibodies, iii) a commercially available Western blot method based on anti-DNPH antibodies and iv) an in-gel detection approach with the fluorophoric reagent fluorescein-5-thiosemicarbazide. The former two methods measure total protein carbonylation of a sample, whereas the latter two require an electrophoretic separation and therefore potentially allow for the identification of specific carbonylated proteins.

Identifiers

PMID30229098
PMCPMC6141388

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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.