Quick Answer
Long AnswerRöntgen radiation, commonly known as X-rays, interacts with biological tissues during imaging procedures such as Cone Beam Computed Tomography (CBCT). This interaction can lead to significant biochemical changes in saliva, which can be effectively analyzed using Surface-Enhanced Raman Spectroscopy (SERS). A recent study investigated these effects by comparing saliva samples collected from patients before and after exposure to CBCT and traditional Computed Tomography (CT).
The following table summarizes the vibrational bands that exhibited significant increases in intensity post-radiation exposure:
| Vibrational Band (cm-1) | Assignment | Post-Irradiation Increase (CT) | Post-Irradiation Increase (CBCT) |
|---|---|---|---|
| 446 | Thiocyanate, phenylalanine | 100 ± 1.9% | 25 ± 0.6% |
| 1002 | L-Phenylalanine, uric acid, opiorphin | 95 ± 1.3% | 21 ± 0.6% |
| 1601 | Phenylalanine, adenine | 154 ± 2.1% | 63 ± 1.4% |
| 1656 | Amide I, glutathione | 129 ± 2.1% | 47 ± 1.1% |
The findings underscore the importance of monitoring biochemical markers in patients undergoing diagnostic imaging, as the exposure to ionizing radiation can lead to significant alterations in salivary composition. SERS proves to be a sensitive method for detecting these subtle molecular changes, which may have implications for understanding the systemic effects of ionizing radiation on human health.
For further details, refer to the original study: Understanding the Interaction of Röntgen Radiation Employed in Computed Tomography/Cone Beam Computed Tomography Investigations of the Oral Cavity by Means of Surface-Enhanced Raman Spectroscopy Analysis of Saliva [2024].
Key Insight
Bioinformatics Wizardimport pandas as pd import matplotlib.pyplot as plt # Sample data for vibrational bands and their increases data = { 'Vibrational Band (cm-1)': [446, 1002, 1601, 1656], 'Post-Irradiation Increase (CT)': [100, 95, 154, 129], 'Post-Irradiation Increase (CBCT)': [25, 21, 63, 47] } # Create DataFrame df = pd.DataFrame(data) # Plotting plt.figure(figsize=(10, 6)) plt.bar(df['Vibrational Band (cm-1)'], df['Post-Irradiation Increase (CT)'], color='blue', label='CT') plt.bar(df['Vibrational Band (cm-1)'], df['Post-Irradiation Increase (CBCT)'], color='orange', label='CBCT', alpha=0.7) plt.xlabel('Vibrational Band (cm-1)') plt.ylabel('Post-Irradiation Increase (%)') plt.title('Post-Irradiation Increase in Salivary Biomarkers') plt.legend() plt.show()
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