Multi-technique computational assessment of fluoride uptake in enamel using PIGE, NEXAFS, and Raman spectroscopy

Area of Science:

• Biomaterials Science
• Dental Research
• Materials Science

Background:

• Fluoride uptake in enamel is crucial for preventing demineralization and caries.
• Accurate quantification and characterization of fluoride uptake are essential for optimizing preventive strategies.

Purpose of the Study:

• To develop and validate a comprehensive methodology for evaluating fluoride uptake in human enamel.
• To confirm the formation of specific fluoride-containing mineral phases.
• To establish a rapid, laboratory-based screening technique for fluoride-treated enamel.

Main Methods:

• Human enamel samples were treated with sodium fluoride (NaF) following standard guidelines.
• Fluoride uptake was quantified using particle-induced gamma-ray emission (PIGE).
• Calcium fluoride (CaF2) and fluorapatite formation were analyzed using near-edge X-ray absorption fine structure (NEXAFS) and finite difference method near-edge structure (FDMNES) simulations.
• Raman microscopy and machine learning (random forest classifier) were employed for rapid sample classification.

Main Results:

• Treated enamel samples showed an average fluoride uptake increase of 160% compared to untreated samples.
• NEXAFS and FDMNES confirmed the formation of CaF2 and fluorapatite-like structures.
• Raman microscopy combined with machine learning effectively distinguished between fluoride-treated and untreated enamel.

Conclusions:

• The developed methodology provides a robust framework for assessing fluoride uptake in human enamel.
• This approach can aid in the development and refinement of effective fluoride-based preventive dental treatments.
• The integration of spectroscopic techniques and machine learning offers a promising avenue for future dental material research.