Pregnancy detection based on blood serum sample Raman spectroscopy.

Area of Science:

• Biomedical Spectroscopy
• Analytical Chemistry
• Biochemistry

Background:

• Raman spectroscopy analyzes molecular vibrations to determine chemical composition.
• It has been applied to disease detection, including cancer, using minimally invasive samples like blood serum.
• Monitoring patient health status can be challenging with conventional methods.

Purpose of the Study:

• To investigate the potential of Raman spectroscopy for diagnosing pregnancy using blood serum samples.
• To identify specific biomolecular changes in serum associated with pregnancy.
• To evaluate the efficacy of Principal Component Analysis (PCA) in discriminating between pregnant and non-pregnant individuals.

Main Methods:

• Blood serum samples were collected from 12 pregnant women and 11 non-pregnant controls.
• Raman spectra were acquired using an 830 nm laser and processed for noise and baseline correction.
• Multivariate statistical analysis, specifically PCA, was employed to analyze spectral data.

Main Results:

• Distinct spectral differences were observed between pregnant and non-pregnant women, primarily linked to variations in glutathione, tryptophan, tyrosine, and phenylalanine.
• PCA effectively discriminated between the two groups, forming two distinct clusters on the PCA plot.
• The method achieved high sensitivity and specificity for pregnancy detection.

Conclusions:

• Raman spectroscopy of blood serum is a viable method for pregnancy diagnosis.
• This technique offers an alternative to conventional urine-based tests (e.g., Human Chorionic Gonadotropin detection).
• The findings suggest potential applications in further gynecological and fetal health studies.