Alzheimer’s disease (AD) is a common neurodegenerative disease characterized by cognitive and memory function impairment. Studies have shown that the amyloid-beta (Aβ) plays an important role in the disease progression. The monomeric Aβ has been associated with biological functions, such as memory, learning, and neuroprotection, while the soluble Aβoligomers are the primary toxic agents and the resultant amyloid fibrils are relatively benign. Thus, the conformation detection of Aβ is quite necessary for AD research. IR spectroscopy is an excellent technique used for protein conformational analysis, for the C=O stretching vibration of the peptide is sensitive to the range of 1600-1700cm- 1. In this research, we proposed a method that detects the conformation of soluble Aβ by using Fourier transform infrared (FTIR) spectroscopy with a transmission approach. Although the attenuated total reflectance (ATR) accessory made from zinc selenide or germanium is the most popular approach for recording liquid spectra of the peptides, the volume requires almost 5 mL of soluble Aβ to cover the crystal to achieve a higher signal. Herein we designed a 25×4 mm calcium fluoride (CaF2) substrate with the center has a groove with 5μm deep and 10 mm diameter, it just needed 2uL of soluble amyloid β-peptide to fill the groove and also achieved a high transmission signal. Moreover, based on this method, we found that the process of oligomer-to-fibrils transition occurred much faster within the first 24 hours, and the secondary structure changed slowly in the following time of 48-96 h. These results demonstrated that FTIR is an exquisite way to characterize the aggregation process of peptides, it not only economizes the reagents but also enables give an almost continuous structural view of such process.
Intraoperative diagnosis plays an essential role in cancer surgery by providing fast and accurate information to clinicians to make a decision. The standard workflow for histopathology based intraoperative diagnosis is generally considered to be time-consuming and labor-intensive. Fourier transform infrared (FTIR) vibration spectroscopy technique has been demonstrated to be a useful tool that yields a molecular fingerprint and provides rapid, nondestructive, high-throughput and clinically relevant diagnostic information. In this study, FTIR spectrometer based on synchrotron radiation was applied to collect the IR spectra of the liver cancer tissues and the adjacent non-cancer tissues of hepatocellular carcinoma (HCC) patients. The FTIR data demonstrated that the ratio of 2959/2926cm-1, 1654/1548cm-1, 1084/1548cm-1 and 1455/1398cm-1 had a significant difference between the two groups, which could serve as indicators to distinguish the liver cancer region from the adjacent non-cancer tissue. Then the supervised machine learning techniques including discriminant analysis coupled with principal component analysis (PCA-DA), support vector machines (SVM) and backpropagation neural networks (BPNN) were applied to classify the spectra data. Finally the performance of these models, such as their precision, sensitivity, specificity and accuracy was assessed, and the results have proved that coupling the FTIR vibration spectroscopy with supervised machine learning techniques could be considered as an accurate and efficient method for the intraoperative diagnosis of HCC.
Hepatocellular carcinoma is a serious threat to human health and life, so early diagnosis of hepatocellular carcinoma is particularly important. A new method based on FTIR spectroscopy and classification tree is proposed in this paper to develop a rapid and accurate diagnosis method for hepatocellular carcinoma. FTIR spectroscopy was firstly used to compare the spectra of hepatocellular carcinoma and normal tissues. The spectra of hepatocellular carcinoma and normal tissues have showed remarkable differences, which implied that the structure and compositions of hepatocellular carcinoma tissues have changed compared with those of normal tissues. 12 peak locations from both hepatocellular carcinoma tissues and normal tissues were analyzed and they had statistical differences by t test, or Wilcoxon rank test with a significance level of 0.05. Thus, peak locations were served as feature vectors for construction of diagnostic models based on classification tree. Diagnostic models based on classification tree were constructed and validated via a 10- fold cross validation method. The classification tree model based on Gdi split criterion achieved an accuracy of 99.24% for discrimination between hepatocellular carcinoma and normal tissue. The results demonstrated that FTIR spectroscopy combined with classification tree could be utilized for rapid and accurate diagnosis of hepatocellular carcinoma.
Terahertz time domain spectroscopy has been widely used in tumor detection, chemical analysis and nondestructive testing. However, the measurement errors of terahertz time domain spectrum frequently occur because of vibration of experiment instrument platform or temperature and humidity changes. Lifting wavelet transform based on different wavelet basis functions was applied to the denoising of terahertz time domain spectrum of PTFE. The denoising results were compared with denoising results of wavelet soft threshold method. The wavelet soft threshold method got a highest signal to noise ratio (SNR) of 58.75 dB and a least root mean square error (RMSE) of 3.56*10^ (-5), while lifting wavelet transform method achieved a highest SNR of 60.69 dB and a least RMSE of 2.85*10^ (-5). These results imply that lifting wavelet transform performs better in terahertz spectrum denoising than wavelet soft threshold.
Cross-linked polystyrene is a kind of thermosetting plastic which has excellent dielectric properties and high breakdown voltage. In this paper, cross-linked polystyrene and polystyrene were analyzed by Fourier transform infrared spectroscopy (FTIR), and the reflective spectra were measured. Subsequent Kramers-Kronig analysis provided the dispersion of the refractive index and the absorption index across the infrared region. The results showed that the refractive index of cross-linked polystyrene decreased rapidly from 1.5 to 1.1 in the spectral region 100cm-1-4000cm-1, which was much lower than that of polystyrene (around 1.5).
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