Evidence map›Paper›PMID 42174314›Full record

ArticleMikrochimica acta2026

Green-synthesized N/S co-doped carbon dots for inner filter effect-based fluorescent detection of doxycycline with antibacterial activity.

Yanhui Li, Yongfang Wei, Xueqi Liao

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Article in Mikrochimica acta, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yanhui LiHunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, School of Pharmaceutical Science, Changsha Medical University, Changsha, China.
Yongfang WeiHunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, School of Pharmaceutical Science, Changsha Medical University, Changsha, China.
Xueqi LiaoHunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, School of Pharmaceutical Science, Changsha Medical University, Changsha, China. xueqi.liao38@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nitrogen/sulphur co-doped carbon dots (N/S-CDs) were synthesised on turmeric processing residue using a hydrothermal procedure. These carbon dots were subsequently analysed as antibacterial nanoparticles and as versatile carbon dots that could be used in fluorescent sensing. A fluorescent sensing platform was designed by utilising the inner filter effect (IFE) to detect doxycycline, which is characterised by an efficient spectral overlap with the excitation/emission bands of N/S-CDs. A high sensing response rate and a LOD at 0.131 µM of ions was identified within a linear response range of 0.5-50 µM. The platform exhibited satisfactory stability in a diverse range of solvents, temperatures, and pH levels, as well as a high tolerance to ionic strength. Selectivity was attained with respect to metal ions and common antibiotics. The method was found to be practical, with exceptional recoveries (98.5-99.3) and low RSD values (1.28-1.74), as evidenced by the actual sample analysis of river, lake, and pond water. Furthermore, it offers the added benefit of nanomaterials that are derived from biomass for biomedical and environmental applications.

Indexed as

Anti-Bacterial AgentsCarbon Quantum DotsDoxycyclineFluorescent DyesCarbonFluorescent Chemosensor CompoundsGreen Chemistry TechnologyLimit of DetectionNitrogenSpectrometry, FluorescenceAnti-Bacterial AgentsCarbonDoxycyclineFluorescent Chemosensor CompoundsFluorescent DyesNitrogenCarbon dotsDoxycycline detectionFluorescent sensingInner filter effectTurmeric processing residue

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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.