ftir imaging
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The Fourier transform infrared (FTIR) imaging technique was used in a transmission model for the evaluation of twelve oral hyperkeratosis (HK), eleven oral epithelial dysplasia (OED), and eleven oral squamous cell carcinoma (OSCC) biopsy samples in the fingerprint region of 1800–950 cm−1. A series of 100 µm × 100 µm FTIR imaging areas were defined in each sample section in reference to the hematoxylin and eosin staining image of an adjacent section of the same sample. After outlier removal, signal preprocessing, and cluster analysis, a representative spectrum was generated for only the epithelial tissue in each area. Two representative spectra were selected from each sample to reflect intra-sample heterogeneity, which resulted in a total of 68 representative spectra from 34 samples for further analysis. Exploratory analyses using Principal component analysis and hierarchical cluster analysis showed good separation between the HK and OSCC spectra and overlaps of OED spectra with either HK or OSCC spectra. Three machine learning discriminant models based on partial least squares discriminant analysis (PLSDA), support vector machines discriminant analysis (SVMDA), and extreme gradient boosting discriminant analysis (XGBDA) were trained using 46 representative spectra from 12 HK and 11 OSCC samples. The PLSDA model achieved 100% sensitivity and 100% specificity, while both SVM and XGBDA models generated 95% sensitivity and 96% specificity, respectively. The PLSDA discriminant model was further used to classify the 11 OED samples into HK-grade (6), OSCC-grade (4), or borderline case (1) based on their FTIR spectral similarity to either HK or OSCC cases, providing a potential risk stratification strategy for the precancerous OED samples. The results of the current study support the application of the FTIR-machine learning technique in early oral cancer detection.

Here, we propose a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy method for simultaneously monitoring the curing reaction and the diffusion behavior of curing agents at the surface of rubber in real-time. The proposed scheme was demonstrated by fluorine rubber (FKM) and FKM/carbon nanotube (CNT) nanocomposites with a target curing agent of triallyl-isocyanurate (TAIC). The broadening and the evolution of the C=O stretching of TAIC were quantitatively analyzed to characterize the reaction and the diffusion. Changes in the width of the C=O stretching indicated the reaction rate at the surface was even faster than that of the bulk as measured by a curemeter. The diffusion coefficient of the curing agent in the course of heating was newly calculated by the initial increase in the absorbance and our model based on Fickian diffusion. The diffusion coefficients of TAIC during curing were evaluated, and its temperature and filler dependency were identified. Cross-sectional ATR-FTIR imaging and in situ ATR-FTIR imaging measurements supported the hypothesis of the unidirectional diffusion of the curing agent towards the heated surface. It was shown that our method of in situ ATR-FTIR can monitor the degrees of cure and the diffusion coefficients of curing agents simultaneously, which cannot be achieved by conventional methods, e.g., rheological measurements.

Traumatic brain injury (TBI) can be defined as a disorder in the function of the brain after a bump, blow, or jolt to the head, or penetrating head injury. Mild traumatic brain injury (mTBI) can cause devastating effects, such as the initiation of long-term neurodegeneration in brain tissue. In the current study, the effects of mTBI were investigated on rat brain regions; cortex (Co) and corpus callosum (CC) after 24 h (subacute trauma) by Fourier transform infrared (FTIR) imaging and immunohistochemistry (IHC). IHC studies showed the formation of amyloid-β (Aβ) plaques in the cortex brain region of mTBI rats. Moreover, staining of myelin basic protein presented the shearing of axons in CC region in the same group of animals. According to FTIR imaging results, total protein and lipid content significantly decreased in both Co and CC regions in mTBI group compared to the control. Due to this significant decrease in both lipid and protein content, remarkable consistency in lipid/protein band ratio in mTBI and control group, was observed. Significant decrease in methyl content and a significant increase in olefinic content were observed in Co and CC regions of mTBI rat brain tissues. Classification amongst distinguishable groups was performed using principal component analysis (PCA) and hierarchical clustering (HCA). This study established the prospective of FTIR imaging for assessing biochemical changes due to mTBI with high sensitivity, precision and high-resolution.