ArticlePloS one2025
Inverse reconstruction of model cells: Extracting structural and molecular insights through infrared spectroscopic cytology.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Inverse Infrared Spectral Deconvolution for Quantitative Analysis of Polymer Mixtures in Scattering Media.Analytical chemistry · 2025Article
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2 authors.
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Abstract
Infrared (IR) microspectroscopy stands as a transformative clinical tool for analyzing single biological cells in biopsy samples, offering critical insights into their chemical composition. In this study, we further develop a recently proposed inverse scattering algorithm that accurately reconstructs the dielectric properties of single cells, considering both scattering and absorption. We demonstrate the method's effectiveness using spherical model cells filled with six organic test substances: polymethyl methacrylate (PMMA), polycarbonate (PC), polydimethylsiloxane (PDMS), polyetherimide (PEI), polyethylene terephthalate (PET), and polystyrene (PS). The permittivity values of these substances, reconstructed from their extinction efficiencies and known refractive indexes from the literature, show excellent agreement with experimental data. Our comparative analysis of the basis sets for the reconstruction algorithm reveals that using dielectric functions leads to more accurate results compared to anti-symmetrized Lorentzians. We find that compared to other methods in the literature on PMMA spheres, our approach yields reconstructions of significantly higher quality. These findings not only enhance reconstruction accuracy but also advance the potential of IR microspectroscopy for clinical cytology, where precise molecular analysis is crucial for disease diagnosis and monitoring at the cellular level.
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