Evidence map›Paper›PMID 38789508›Full record

ArticleScientific reports2024

Label-free electrochemical biosensor based on green-synthesized reduced graphene oxide/Fe

Mojtaba Hosseine, Seyed Morteza Naghib, Abbasali Khodadadi

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Dual functional rGO/FeScientific reports · 2026
    Article
  4. Review
  5. Review
  6. Review
  7. Review
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  9. Article
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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

3 authors.

Mojtaba HosseineSchool of Chemical Engineering, University of Tehran, P.O. Box 11155/4563, Tehran, Iran.
Seyed Morteza NaghibNanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology (IUST), P.O. Box 16846-13114, Tehran, Iran. naghib@iust.ac.ir.
Abbasali KhodadadiSchool of Chemical Engineering, University of Tehran, P.O. Box 11155/4563, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer stands as one of the most impactful illnesses in the modern world, primarily owing to its lethal consequences. The fundamental concern in this context likely stems from delayed diagnoses in patients. Hence, detecting various forms of cancer is imperative. A formidable challenge in cancer research has been the diagnosis and treatment of this disease. Early cancer diagnosis is crucial, as it significantly influences subsequent therapeutic steps. Despite substantial scientific efforts, accurately and swiftly diagnosing cancer remains a formidable challenge. It is well known that the field of cancer diagnosis has effectively included electrochemical approaches. Combining the remarkable selectivity of biosensing components-such as aptamers, antibodies, or nucleic acids-with electrochemical sensor systems has shown positive outcomes. In this study, we adapt a novel electrochemical biosensor for cancer detection. This biosensor, based on a glassy carbon electrode, incorporates a nanocomposite of reduced graphene oxide/Fe

Indexed as

Aniline CompoundsBiomarkers, TumorBiosensing TechniquesBreast NeoplasmsElectrochemical TechniquesErb-b2 Receptor Tyrosine KinasesFluorocarbon PolymersGraphiteCell Line, TumorElectrodesFemaleFerrosoferric OxideHumansLimit of DetectionAniline CompoundsBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesFerrosoferric OxideFluorocarbon Polymersgraphene oxideGraphiteperfluorosulfonic acidpolyanilineElectrochemical immunosensorFe3O4Green synthesisLabel-free detectionNafionPolyanilineReduced graphene oxideSKBR3

Identifiers

PMID38789508
PMCPMC11126587

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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.