Evidence map›Paper›PMID 40243410›Full record

ReviewInternational journal of molecular sciences2025

Applications of Green Carbon Dots in Personalized Diagnostics for Precision Medicine.

Habtamu F Etefa, Francis B Dejene

Erratum issuedAbstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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
  2. Carbon dots derived fromFrontiers in molecular biosciences · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Habtamu F EtefaDepartment of Chemical and Physics Science, Walter Sisulu University, Private Bag X-1, Mthatha 5117, South Africa.
Francis B DejeneDepartment of Chemical and Physics Science, Walter Sisulu University, Private Bag X-1, Mthatha 5117, South Africa.ORCID 0000-0002-4474-199X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Green carbon dots (GCDs) have emerged as a revolutionary tool in precision medicine, offering transformative capabilities for personalized diagnostics and therapeutic strategies. Their unique optical and biocompatible properties make them ideal for non-invasive imaging, real-time monitoring, and integration with genomics, proteomics, and bioinformatics, enabling accurate diagnosis and tailored treatments based on patients' genetic and molecular profiles. This study explores the potential of GCDs in advancing individualized patient care by examining their applications in precision medicine. It evaluates their utility in non-invasive diagnostic imaging, targeted therapy delivery, and the formulation of personalized treatment plans, emphasizing their interaction with advanced genomic, proteomic, and bioinformatics platforms. GCDs demonstrated exceptional versatility in enabling precise diagnostics and delivering targeted therapies. Their integration with cutting-edge technologies showed significant promise in crafting personalized treatment strategies, enhancing their functionality and effectiveness in real-time monitoring and patient-specific applications. The findings underscore the pivotal role of GCDs in reshaping healthcare by advancing precision medicine and improving patient outcomes. The ongoing development and integration of GCDs with emerging technologies promise to further enhance their capabilities, paving the way for more effective, individualized medical care.

Indexed as

CarbonPrecision MedicineQuantum DotsHumansCarbondrug delivery systemsGCDsgenomicsproteomicstheranostics

Identifiers

PMID40243410
PMCPMC11988419

What OpenQuestion holds

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LicenceCC BY
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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.