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Related Experiment Videos

Methods for detecting silicones in biological matrixes.

J J Kennan1, L L Breen, T H Lane

  • 1Dow Corning Corporation, Midland, Michigan 48686-0994, USA. john.j.kennan@dowcorning.com

Analytical Chemistry
|August 18, 1999
PubMed
Summary
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A new method accurately detects silicone in biological samples using microwave digestion and gas chromatography. This technique offers lower detection limits than 29Si NMR and is more specific than ICP-AES for silicone analysis.

Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Materials Science

Background:

  • Silicones are widely used in medical devices and implants.
  • Accurate quantification of silicones in biological matrices is crucial for safety and research.
  • Existing analytical methods have limitations in sensitivity, specificity, or applicability to biological samples.

Purpose of the Study:

  • To develop and validate a sensitive and specific method for analyzing silicon and silicone in biological matrices.
  • To compare the performance of the developed method with existing techniques like 29Si NMR and ICP-AES.

Main Methods:

  • Microwave digestion in acid solution to break down biological matrix and hydrolyze silicones.
  • Trimethylsilyl capping of monomeric silanol species.

Related Experiment Videos

  • Extraction into hexamethyldisiloxane.
  • Analysis by gas chromatography (GC).

    • Main Results:

    • The developed GC-based method achieved detection limits below 0.5 microgram of Si/mL in serum for silicone species.
    • 29Si NMR showed significantly lower sensitivity (64 micrograms of Si/mL in serum).
    • ICP-AES, while potentially sensitive, lacks silicone specificity and exhibits species-dependent responses.

    Conclusions:

    • The developed microwave digestion-GC method provides a sensitive and specific approach for silicone analysis in biological samples.
    • This technique surpasses the sensitivity of 29Si NMR and the specificity of ICP-AES for silicone detection.
    • The method is suitable for positive identification and quantification of silicone species in biological matrices.