Evidence map›Paper›PMID 36012486›Full record

ArticleInternational journal of molecular sciences2022

Red-Emissive Sulfur-Doped Carbon Dots for Selective and Sensitive Detection of Mercury (II) Ion and Glutathione.

Jinjin Zeng, Linhong Liao, Xiao Lin, Genyan Liu, Xiaogang Luo, Ming Luo, Fengshou Wu

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Review
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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

7 authors.

Jinjin ZengHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.
Linhong LiaoHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.
Xiao LinHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.
Genyan LiuHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.
Xiaogang LuoHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.
Ming LuoSchool of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China.
Fengshou WuHubei Key Laboratory of Novel Reactor and Green Chemical Technology, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430072, China.

Funding

Natural Science Foundation of Hubei Province 2021CFB228
6 · The paper itself

Abstract

Carbon dots (CDs) show great potential in bioimaging and biosensing because of their good biocompatibility and excellent optical properties. However, CDs with intense red emissions for sensitive and selective detection are rarely reported. Herein, we prepared the red-emissive carbon dots (RCDs) through a facile hydrothermal method using tetra (4-carboxyphenyl) porphyrin (TCPP) and thiourea as starting materials. The obtained RCDs were characterized by TEM, XRD, and XPS. RCDs exhibited high water solubility and strong red emission (λ

Indexed as

MercuryQuantum DotsCarbonFluorescent DyesGlutathioneNitrogenSpectrometry, FluorescenceSulfurCarbonFluorescent DyesGlutathioneMercuryNitrogenSulfurbioimagingcarbon dotsglutathioneHg2+red emission

Identifiers

PMID36012486
PMCPMC9409242

What OpenQuestion holds

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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.