ArticleRSC advances2023
Electrochemical biosensor based on cellulose nanofibers/graphene oxide and acetylcholinesterase for the detection of chlorpyrifos pesticide in water and fruit juice.
Article in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- Biosensor Technologies for Water Quality: Detection of Emerging Contaminants and Pathogens.Biosensors · 2025Review
- Graphene oxide-cerium oxide nanocomposite modified gold electrode for ultrasensitive detection of chlorpyrifos pesticide.RSC advances · 2024Article
- Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater.Sensors (Basel, Switzerland) · 2024Review
- A new plant-esterase inhibition based electrochemical sensor with signal amplification by MoSRSC advances · 2024Article
- Open Meter Duo: Low-Cost Instrument for Fluorimetric Determination of Cholinesterase Activity.Sensors (Basel, Switzerland) · 2024Article
- A Laser-Induced Graphene-Based Sensor Modified with CeOSensors (Basel, Switzerland) · 2023Article
- Affordable Portable Platform for Classic Photometry and Low-Cost Determination of Cholinesterase Activity.Biosensors · 2023Article
- Recent Developments in the Applications of GO/rGO-Based Biosensing Platforms for Pesticide Detection.Biosensors · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, cellulose nanofibers and graphene oxide are used to fabricate a simple and reliable electrochemical biosensor, based on acetylcholinesterase (AChE) for the detection of highly dangerous organophosphates (OPs), utilizing chlorpyrifos as a representative sample. AChE is an enzyme that is essential for neurotransmission and catalyzes the conversion of acetylcholine (ATCh) into thiocholine and acetic acid. The pesticide used in this work, chlorpyrifos, inhibits the catalytic activity of AChE on ATCh, and this inhibition can be measured using square wave voltammetry (SWV). Utilizing a process of surface modification, layers of cellulose nanofibers, graphene oxide, a chitosan-graphene oxide composite, and acetylcholinesterase (AChE/CS-GO/GO/CNFs) were immobilized on a screen-printed carbon electrode (SPCE). The modified SPCE working electrode was characterized using scanning electron microscopy and graphene oxide trapped in the cellulose nanofibers was found to increase the sensitivity of the biosensor. The modified biosensor demonstrated good performance for detection of chlorpyrifos over a linear range of 25-1000 nM under optimum conditions, and the limits of detection and quantification were 2.2 nM and 73 nM, respectively. Our sophisticated technique might offer a more precise, straightforward, quick, and environmentally friendly way to assess chlorpyrifos contamination in water and juice samples.
Identifiers
What OpenQuestion holds
Registered trials
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.