A classification model for detection of ductal carcinoma in situ by Fourier transform infrared spectroscopy based on deep structured semantic model

At present, deep learning is widely used in spectral data processing. Deep learning requires a large amount of data for training, while the collection of biological serum spectra is limited by sample numbers and labor costs, so it is impractical to obtain a large amount of serum spectral data for disease detection. In this study, we propose a spectral classification model based on the deep structured semantic model (DSSM) and successfully apply it to Fourier Transform Infrared (FT-IR) spectroscopy for ductal carcinoma in situ (DCIS) detection. Compared with the traditional deep learning model, we match the spectral data into positive and negative pairs according to whether the spectra are from the same category. The DSSM structure is constructed by extracting features according to the spectral similarity of spectra pairs. This new construction model increases the data amount used for model training and reduces the dimension of spectral data. Firstly, the FT-IR spectra are paired. The spectra pairs are labeled as positive pairs if they come from the same category, and the spectra pairs are labeled as negative pairs if they come from different categories. Secondly, two spectra in each spectra pair are put into two deep neural networks of the DSSM structure separately. Then the spectral similarity between the output feature maps of two deep neural networks is calculated. The DSSM structure is trained by maximizing the conditional likelihood of the spectra pairs from the same category. Thirdly, after the training of DSSM is done, the training set and testing set are input into two deep neural networks separately. The output feature maps of the training set are put into the reference library. Lastly, the k-nearest neighbor (KNN) model is used for classification according to Euclidean distances between the output feature map of each unknown sample to the reference library. The category of the unknown sample is judged according to the categories of k nearest samples. We also use principal component analysis (PCA) to reduce dimension for comparison. The accuracies of the KNN model, principal component analysis-k nearest neighbor (PCA-KNN) model, and deep structured semantic model-k nearest neighbor (DSSM-KNN) model are 78.8%, 72.7%, and 97.0%, which proves that our proposed model has higher accuracy.

Mechanism of Phase Separation in Aqueous Two-Phase Systems

Liquid-liquid phase separation underlies the formation of membrane-less organelles inside living cells. The mechanism of this process can be examined using simple aqueous mixtures of two or more solutes, which are able to phase separate at specific concentration thresholds. This work presents the first experimental evidence that mesoscopic changes precede visually detected macroscopic phase separation in aqueous mixtures of two polymers and a single polymer and salt. Dynamic light scattering (DLS) analysis indicates the formation of mesoscopic polymer agglomerates in these systems. These agglomerates increase in size with increasing polymer concentrations prior to visual phase separation. Such mesoscopic changes are paralleled by changes in water structure as evidenced by Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopic analysis of OH-stretch bands. Through OH-stretch band analysis, we obtain quantitative estimates of the relative fractions of four subpopulations of water structures coexisting in aqueous solutions. These estimates indicate that abrupt changes in hydrogen bond arrangement take place at concentrations below the threshold of macroscopic phase separation. We used these experimental observations to develop a model of phase separation in aqueous media.

Properties of sodium caseinate as affected by the β-casein phenotypes

The aim of the study was to investigate the properties of sodium caseinate dispersions and oil-in-water emulsions obtained from cows' milk of either A1/A1, A1/A2, or A2/A2 β-casein phenotype. Protein structural characterisation was examined using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopies, with physicochemical and interfacial properties assessed by analysing adsorbed protein content, hydrophobicity, solubility, and emulsion stability of the samples. Results showed variations in the secondary structure of all samples dependent of the presence of A1 or A2 β-caseins. The main differences included greater amounts of α-helix and β-sheet in A1/A1 and A1/A2 sodium caseinate dispersions that influenced their lower solubility, while random coils/polyproline II helixes were found only in A2/A2 sodium caseinate dispersion. In contrast, upon adsorption on the interface of A2/A2 sodium caseinate emulsion, the protein adopted ordered conformational motifs. This conformational shift supposedly arose from structural differences between the two β-casein proteoforms, which most likely enhanced the emulsion properties of A2/A2 sodium caseinate compared to either A1/A1 or A1/A2 sodium caseinates. The A2 β-casein in both, A1/A2 and A2/A2 sodium caseinates, appears to be able to more rapidly reach the oil droplet surface and was more efficient as emulsifying agent. The current results demonstrated that the conformational rearrangement of proteins upon adsorption to emulsion interfaces was dependent not only on hydrophobicity and on solubility, but also on the conformational flexibility of A1/A1, A1/A2, and A2/A2 β-casein phenotypes. These findings can assist in predicting the behaviour of sodium caseinates during relevant industrial processing.

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy

Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma.

Influence of external energy sources on the dynamic setting process of glass-ionomer cements

OBJECTIVE

To evaluate the influence of external energy sources on the dynamic setting process of glass-ionomer restorative materials.

METHODS

Eighteen brands of GIC were studied: Bioglass R (Biodinâmica; G1), Chemfil Rock (Dentsply; G2), Equia Forte (GC; G3), Gold Label 2 (GC; G4), Gold Label 9 (GC; G5), Glass Ionomer Cement Type II - (Shofu; G6), Ionglass R (Maquira; G7), Ion Z (FGM; G8), Ionomaster (Wilcos; G9), Ionofil Plus (Voco; G10), Ionostar Plus (Voco; G11), Ketac Molar easymix (3M ESPE; G12), Magic Glass R (Vigodent; G13), Maxxion R (FGM; G14), Riva Self Cure (SDI; G15), Vidrion R (SS White; G16), Vitro Fil R (Nova DFL; G17) and Vitro Molar (Nova DFL; G18). LED, halogen light or ultrasound (n=20 for each set) applied for 30s was used to activate setting, and a control group of each material was allowed to set without activation. Samples were analyzed by FTIR spectroscopy using the ratio of intensities of bands at 1637cm^-1 (carboxylate) and 1720cm^-1 (carbonyl) as a function of time. Means and standard deviations were subjected to ANOVA and Tukey tests (p<0.05).

RESULTS

All three activation modes significantly reduced the time at which the carboxylate content became stable in G2, G4, G5, G6, G8, G10, G14, G16, G17 and G18. By contrast, in G1, G7, G12 and G15 no activation source had any significant effect (p>0.05).

SIGNIFICANCE

External activation sources, namely LED, halogen light and ultrasound, typically but not always increase the setting rate of restorative GICs.

Differentiation of Chronic and Aggressive Periodontitis by FTIR Spectroscopy

Without longitudinal clinical data, it is difficult to differentiate some cases of chronic periodontitis (CP) and aggressive periodontitis (AgP). Furthermore, both forms of disease are exacerbated by tobacco use. Therefore, this cross-sectional study was planned, primarily, to determine the ability of Fourier-transform infrared (FTIR) spectroscopy to distinguish CP and AgP patients by analysis of human saliva samples and, secondarily, to assess the potential confounding influence of smoking on discriminating disease-specific spectral signatures. FTIR spectra were collected from patients with a clinical diagnosis of CP (n = 18; 7 smokers) or AgP (n = 23; 9 smokers). Self-reported smoking status, which may be unreliable, was confirmed by salivary cotinine analysis. Spectral band area analysis and hierarchical cluster analyses were performed to clarify if the 2 periodontitis groups as well as smoker and nonsmoker patients could be differentiated from each other. Significant variations in lipid, amino acid, lactic acid, and nucleic acid content were found between nonsmoker CP and AgP groups. Although significantly lower lipid, phospholipid, protein, amino acid, lactic acid, and nucleic acid content was noted in the smoker AgP group compared with the nonsmoker AgP group, in the CP group, phospholipid, protein, amino acid, and lactic acid content was significantly lower for smokers compared with the nonsmokers. Based on these variations, nonsmoker CP and AgP patients were discriminated from each other with high sensitivity and specificity. Successful differentiation was also obtained for the smoker CP and AgP groups. Thiocyanate levels successfully differentiated smokers from nonsmokers, irrespective of periodontal status, with 100% accuracy. Differentiation of AgP and CP forms, concomitant with determination of smoking status, may allow the dental health professional to tailor treatment accordingly.

Thermal and structural characterization of synthetic and natural nanocrystalline hydroxyapatite

The aim of this work was to study the thermal stability on heating and to obtain the processing parameters of synthetic and bone-derived hydroxyapatite over temperatures between room temperature and 1400°C by thermal analysis (thermogravimetry (TG)/differential scanning calorimetry (DSC) and thermo-mechanical analysis-TMA). Structural and surface modifications related to samples origin and calcination temperature were investigated by Fourier transformed infrared (FTIR) and Raman spectroscopy, X-ray diffraction (XRD) and BET method. FTIR spectra indicated that the organic constituents and carbonate are no longer present in the natural sample calcined at 800°C. Raman spectra highlighted the decomposition products of the hydroxyapatite. The calcination treatment modifies the processes kinetics of the synthetic samples, being able to isolate lattice water desorption processes of decarbonization and the dehydroxylation processes. Shrinkage of calcined synthetic sample increases by 10% compared to uncalcined synthetic powder. From the TMA correlated with TG analysis and heat capacity data it can be concluded that sintering temperature of the synthetic samples should be chosen in the temperature range of the onset of dehydroxylation and the temperature at which oxyapatite decomposition begins.

Improvement in antihypertensive and antianginal effects of felodipine by enhanced absorption from PLGA nanoparticles optimized by factorial design

Objective of the present investigation was to enhance the bioavailability of felodipine by targeting the M cells of Peyer's patches using PLGA nanoparticles (NPs). Felodipine exhibits poor bioavailability due to limited aqueous solubility and extensive first pass metabolism. NPs were prepared using nanoprecipitation and optimized by 3(2) factorial design. Particle size (PS) and entrapment efficiency (% EE) were dependent on Drug/PLGA ratio (X1) and Pluronic F-68 (X2) concentration. % EE, PS and Zeta potential for optimized batch were 91.56±3.21%, 161.3±2.23 nm and -25.7±2.52 mV respectively. DSC, XRD and FTIR studies confirmed compatibility of PLGA and drug. TEM image confirmed the spherical shape. The in vitro and ex vivo studies using rat stomach and intestinal segment confirmed sustained release from NPs. Pharmacodynamic studies in rats showed control of blood pressure and ECG changes for extended duration. Hence, NPs can be a suitable alternative to the current available therapy in hypertension and angina by enhancing the bioavailability.

XRD and FTIR crystallinity indices in sound human tooth enamel and synthetic hydroxyapatite

The crystallinity index (CI) is a measure of the percentage of crystalline material in a given sample and it is also correlated to the degree of order within the crystals. In the literature two ways are reported to measure the CI: X-ray diffraction and infrared spectroscopy. Although the CI determined by these techniques has been adopted in the field of archeology as a structural order measure in the bone with the idea that it can help e.g. in the sequencing of the bones in chronological and/or stratigraphic order, some debate remains about the reliability of the CI values. To investigate similarities and differences between the two techniques, the CI of sound human tooth enamel and synthetic hydroxyapatite (HAP) was measured in this work by X-ray diffraction (XRD) and Fourier Transform Infrared spectroscopy (FTIR), at room temperature and after heat treatment. Although the (CI)XRD index is related to the crystal structure of the samples and the (CI)FTIR index is related to the vibration modes of the molecular bonds, both indices showed similar qualitative behavior for heat-treated samples. At room temperature, the (CI)XRD value indicated that enamel is more crystalline than synthetic HAP, while (CI)FTIR indicated the opposite. Scanning (SEM) and transmission (TEM) images were also used to corroborate the measured CI values.