Evidence map›Paper›PMID 38886239›Full record

ReviewAnalytical and bioanalytical chemistry2024

Fluorescent carbon dots for discriminating cell types: a review.

Yaolong An, Zihao Wang, Fu-Gen Wu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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.

Yaolong AnState Key Laboratory of Digital Medical Engineering, Key Laboratory for Biomaterials and Devices of Jiangsu Province, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China.
Zihao WangState Key Laboratory of Digital Medical Engineering, Key Laboratory for Biomaterials and Devices of Jiangsu Province, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China.
Fu-Gen WuState Key Laboratory of Digital Medical Engineering, Key Laboratory for Biomaterials and Devices of Jiangsu Province, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China. wufg@seu.edu.cn.

Funding

Natural Science Foundation of Jiangsu Province BK20211510
6 · The paper itself

Abstract

Carbon dots (CDs) are quasi-spherical carbon nanoparticles with excellent photoluminescence, good biocompatibility, favorable photostability, and easily modifiable surfaces. CDs, serving as fluorescent probes, have emerged as an ideal tool for cellular differentiation owing to their outstanding luminescence performance and tunable surface properties. In this review, we summarize the recent research progress with CDs in the differentiation of cancer/normal cells, Gram-positive/Gram-negative bacteria, and live/dead cells, as well as the cellular differences used for differentiation. Additionally, we summarize the preparation methods, raw materials, and properties of the CDs used for cell discrimination. The differentiation mechanisms and the advantages or limitations of the differentiation methods are also introduced. Finally, we propose several research challenges in this field and future research directions that require extensive investigation. It is hoped that this review will help researchers in the design of new CDs as ideal fluorescent probes for realizing diverse cell differentiation applications.

Indexed as

CarbonFluorescent DyesQuantum DotsAnimalsCell DifferentiationHumansCarbonFluorescent DyesCancer and normal cellsCarbon dotsCell type discriminationGram-positive and Gram-negative bacteriaLive and dead cells

Identifiers

What Socratic 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 Socratic graph.