journal article·2025

A non-enzymatic dual sensing approach for the detection of cholesterol in real samples using silk fiber functionalized phosphorene quantum dots

Nasrin Sultana, Shreyash Vijay Andagonde, Ratul Chakraborty, Asis Bala, Neelotpal Sen Sarma

Nanoscale· Volume 17· Issue 6
Publisher page

Abstract

Reliable point-of-care (POC) detection of the specific biomarkers responsible for different diseases is crucial for health monitoring. For the routine detection of important biomarkers, rapid, precise, and cost-effective analytical techniques are more and more in demand. Cardiovascular diseases like hypertension, myocardial infarction, and stroke can occur due to high cholesterol levels. Herein, we have proposed an inner filter effect-based optical sensing platform for the selective and sensitive detection of cholesterol in aqueous media and real samples, i.e. human blood serum, rat blood serum, and milk. The sensing platform was developed by utilizing silk fiber functionalized phosphorene quantum dots (Ph-SF) using a simple hydrothermal approach. The obtained limit of detection (LOD) was 22 nM for aqueous media, 21.7 nM for human blood serum, 11.01 nM for rat blood serum, and 19.9 nM for milk in the linear range of 0-80 μL for the concentration range of 4.5-36.36 μM. Moreover, we have also fabricated a paper-based electronic device using a Ph-SF-incorporated cellulose nitrate membrane for detecting the same. The membrane shows a current value of about 7.74 × 10-6 A. However, upon interaction with cholesterol, it shows a current value of about 2.16 × 10-5 A. We have also calculated the LOD in this regard which was found to be about 0.263 μM, 1.69 μM, 1.402 μM, and 1.192 μM for aqueous media, human blood serum, rat blood serum, and milk respectively in the linear range of 1-5 mM.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · Silk-based biomaterials and applications · GaN-based semiconductor devices and materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Advanced Study in Science and Technology, Paschim Boragaon, Guwahati-35, Assam, India

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002, India

Funding

Department of Science and Technology, Ministry of Science and Technology

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