Evidence map›Paper›PMID 37244906›Full record

ArticleScientific reports2023

Bioinspired 5-caffeoylquinic acid capped silver nanoparticles using Coffee arabica leaf extract for high-sensitive cysteine detection.

E S Harsha Haridas, Susmita Bhattacharya, M K Ravi Varma, Goutam Kumar Chandra

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In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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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

4 authors at 2 institutions in 2 countries.

E S Harsha HaridasDepartment of Physics, National Institute of Technology, Kozhikode, Kerala, 673601, India.
Susmita BhattacharyaRadiation Laboratory, University of Notre Dame, Notre Dame, IN, 46556, USA.
M K Ravi VarmaDepartment of Physics, National Institute of Technology, Kozhikode, Kerala, 673601, India.
Goutam Kumar ChandraDepartment of Physics, National Institute of Technology, Kozhikode, Kerala, 673601, India. goutam@nitc.ac.in.
National Institute of Technology Calicut · INUniversity of Notre Dame · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selection of plant extracts as bioactive phytochemical source to synthesize nanoparticles is highly demanding due to the biocompatibility, nontoxicity, and cost-effectiveness over other available physical and chemical methods. Here, for the first time, Coffee arabica leaf extracts (CAE) were used to produce highly stable silver nanoparticles (AgNPs) and the corresponding bio reduction, capping and stabilization mechanism mediated by dominant isomer 5-caffeoylquinic acid (5-CQA) is discussed. UV-Vis, FTIR, μRaman spectroscopy, TEM, DLS and Zeta potential analyzer measurements were employed to characterize these green synthesized NPs. The affinity of 5-CQA capped CAE-AgNPs to thiol moiety of amino acid is utilized for the selective as well as sensitive detection of L-cysteine (L-Cys) to a low detection limit of 0.1 nM, as obtained from its μRaman spectra. Hence, the proposed novel, simple, eco-friendly, and economically sustainable method can provide a promising nanoplatform in the field of biosensors compliant with large-scale industrial production of AgNPs without aid of further instrumentation.

Indexed as

Metal NanoparticlesAnti-Bacterial AgentsCoffeeCysteinePlant ExtractsPlant LeavesQuinic AcidSilverSpectroscopy, Fourier Transform InfraredAnti-Bacterial Agentscaffeoylquinic acidCoffeeCysteinePlant ExtractsQuinic AcidSilver

Identifiers

PMID37244906
PMCPMC10224661
OpenAlexW4378575906

What OpenQuestion holds

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LicenceCC BY
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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.