Evidence map›Paper›PMID 34184110›Full record

ArticleMikrochimica acta2021

CuO/Cu-MOF nanocomposite for highly sensitive detection of nitric oxide released from living cells using an electrochemical microfluidic device.

Negar Alizadeh, Abdollah Salimi, Tsun-Kong Sham

Abstract read
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In one paragraph

Article in Mikrochimica acta, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Article
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  4. Review
  5. Review
  6. GNP-CeOMikrochimica acta · 2021
    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

3 authors at 2 institutions in 2 countries.

Negar AlizadehDepartment of Chemistry, University of Kurdistan, Sanandaj, 66177-15175, Iran.
Abdollah SalimiDepartment of Chemistry, University of Kurdistan, Sanandaj, 66177-15175, Iran. absalimi@uok.ac.ir.
Tsun-Kong ShamUniversity of Western Ontario, London, Ontario, N6A 5B7, Canada.
University of Kurdistan · IRWestern University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of large surface area and high catalytic profiles of Cu-MOF and CuO nanoparticles is described toward electrochemical sensing of nitric oxide (NO) in a microfluidic platform. The CuO/Cu-MOF nanocomposite was prepared through hydrothermal method, and its formation was confirmed by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and energy-dispersive X-ray spectroscopy (EDS). The CuO/Cu-MOF nanostructured modified Au electrodes enabled electrocatalytic NO oxidation at 0.6 V vs. reference electrode, demonstrating linear response over a broad concentration range of 0.03-1 μM and 1-500 μM with a detection limit of 7.8 nM. The interference effect of organic molecules and common ions was negligible, and the sensing system demonstrated excellent stability. Finally, an electrochemical microfluidic NO sensor was developed to detect of NO released from cancer cells, which were stimulated by L-arginine. Furthermore, in the presence of Fe

Indexed as

Lab-On-A-Chip DevicesCopperElectrochemical TechniquesHumansLimit of DetectionMCF-7 CellsMetal-Organic FrameworksMicrofluidic Analytical TechniquesNanocompositesNitric OxideOxidation-ReductionReproducibility of ResultsCoppercupric oxideMetal-Organic FrameworksNitric OxideCuO/Cu-MOFElectrochemical detectionMicrofluidicNanocompositeNitric oxide detection

Identifiers

PMID34184110
OpenAlexW3175935087

What OpenQuestion holds

Textmetadata
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.