Molecularly imprinted polymer filter modified with natural polyphenols for extraction of levothyroxine from biological samples

In this study, a molecularly imprinted polymer (MIP) filter, modified with natural polyphenols extracted from green tea, was employed for the extraction of levothyroxine, followed by analysis <i>via</i> high-performance liquid chromatography with ultraviolet-visible detection (HPLC-UV). The filter's characteristics were comprehensively assessed using Fourier-transform infrared spectroscopy (FT-IR) to identify functional groups, scanning electron microscopy (SEM) to examine surface morphology, energy-dispersive spectroscopy (EDS) for elemental analysis, and X-ray diffraction (XRD) to elucidate crystalline structure. Following the passage of sample solutions through the filter, which was integrated with a solvent delivery system, and optimization of extraction parameters by response surface methodology (RSM), a linear range of 1 to 1000 μg L<sup>-1</sup> was achieved for levothyroxine, with a coefficient of determination of 0.9999. The limit of detection and limit of quantification were 0.36 μg L<sup>-1</sup> and 1.19 μg L<sup>-1</sup>, respectively. The method has an enrichment factor ranging from 245.0 to 250.5. Furthermore, the effect of the matrix on the extraction was insignificant. Applying this method to biological samples of blood serum and urine yielded recoveries exceeding 98.3%, with RSD below 6.1%.

Authors

Institutions

Publication Details

Journal
Analytical Methods
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ay00617a
Primary Topic
Analytical chemistry methods development
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecularly imprinted polymer filter modified with natural polyphenols for extraction of levothyroxine from biological samples

Tahere Khezeli, Fatemeh Yeksan
Analytical Methods
Analytical chemistry methods development
article

Molecularly imprinted polymer filter modified with natural polyphenols for extraction of levothyroxine from biological samples

Tahere Khezeli, Fatemeh Yeksan
article en

Abstract

In this study, a molecularly imprinted polymer (MIP) filter, modified with natural polyphenols extracted from green tea, was employed for the extraction of levothyroxine, followed by analysis <i>via</i> high-performance liquid chromatography with ultraviolet-visible detection (HPLC-UV). The filter's characteristics were comprehensively assessed using Fourier-transform infrared spectroscopy (FT-IR) to identify functional groups, scanning electron microscopy (SEM) to examine surface morphology, energy-dispersive spectroscopy (EDS) for elemental analysis, and X-ray diffraction (XRD) to elucidate crystalline structure. Following the passage of sample solutions through the filter, which was integrated with a solvent delivery system, and optimization of extraction parameters by response surface methodology (RSM), a linear range of 1 to 1000 μg L<sup>-1</sup> was achieved for levothyroxine, with a coefficient of determination of 0.9999. The limit of detection and limit of quantification were 0.36 μg L<sup>-1</sup> and 1.19 μg L<sup>-1</sup>, respectively. The method has an enrichment factor ranging from 245.0 to 250.5. Furthermore, the effect of the matrix on the extraction was insignificant. Applying this method to biological samples of blood serum and urine yielded recoveries exceeding 98.3%, with RSD below 6.1%.

Analytical MethodsVol. 17(28)
Ilam University (IR)
Ilam University
Openalex Percentile: Top 83%
Analytical chemistry methods development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.