Evidence map›Paper›PMID 41945191›Full record

ArticleMikrochimica acta2026

Aptamer discovery via GO-SELEX and GrNP-SELEX for monocrotophos and its comparative analysis.

Narlawar Sagar Shrikrishna, G Pratheeth Bhat, Sonu Gandhi

Abstract readComparative Study
PubMed Publisher
In one paragraph

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.

Narlawar Sagar ShrikrishnaBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad, Telangana, 500032, India.
G Pratheeth BhatBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad, Telangana, 500032, India.
Sonu GandhiBRIC-National Institute of Animal Biotechnology (NIAB), Hyderabad, Telangana, 500032, India. gandhi@niab.org.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The selection of high-affinity aptamers for small-molecule detection is a critical challenge in biosensor development. This study introduces a graphene nanoplatelet-based SELEX (GrNP-SELEX) and compares its performance with the graphene oxide-based SELEX (GO-SELEX) for generating monocrotophos-specific aptamers. Characterization studies confirmed the successful adsorption of ssDNA onto both GO and GrNP, enabling effective selection. The best-performing aptamers, MPGO-130 and MPGR-999, exhibited Kd values of 31.14 µM and 19.92 µM, respectively, indicating a slightly higher affinity for GrNP-derived aptamers. These aptamers were integrated into an electrochemical biosensor, achieving limits of detection (LOD) of 0.58 ng/mL and 0.78 ng/mL and limits of quantification (LOQ) of 1.91 ng/mL and 2.60 ng/mL, respectively. The biosensors demonstrated effective detection of monocrotophos in real-world samples such as tomato extract, lake water, soil, animal feed, and meat extract, with validation performed using HPLC. While both SELEX strategies yielded functional aptamers, GrNP-SELEX emerged as a cost-effective and viable alternative. This study highlights the potential of GrNP-SELEX in aptamer development, contributing to the advancement of biosensing technologies for environmental and agricultural monitoring.

Indexed as

Aptamers, NucleotideBiosensing TechniquesGraphiteMonocrotophosSELEX Aptamer TechniqueDNA, Single-StrandedElectrochemical TechniquesLimit of DetectionAptamers, NucleotideDNA, Single-Strandedgraphene oxideGraphiteMonocrotophosAptamersBiosensorsGraphene nanoplateletsGraphene oxideMonocrotophos

Identifiers

What OpenQuestion 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 OpenQuestion graph.