Fusion of three spectroscopic techniques for prediction of fatty acid in processed lamb.

The application of individual spectroscopic techniques for meat analysis has been widely explored. Attempts to fuse data from multiple spectroscopic instruments for meat analysis are still lacking. Comparative assessment of the performance of mid infrared (MIR), near infrared (NIR) and Raman spectroscopy to estimate fatty acid (FA) composition in processed lamb was investigated. The acquired data from these individual techniques were then utilised in estimating similar parameters using a multi-block partial least square data fusion approach. Model performance was assessed with respect to the determination coefficient and ratio of predictive deviation upon cross-validation of the model. The fused data had slight improvements for the prediction of four FA parameters including MUFA, C18:0, C18:1 c9 and C9, t11- CLA), suggesting possible information enhancement with use of multiple instruments. However, MIR offered better predictability (RPD values) across the FA parameters considered.

Evaluating low- mid- and high-level fusion strategies for combining Raman and infrared spectroscopy for quality assessment of red meat.

The implementation of Raman and infrared spectroscopy with three data fusion strategies to predict pH and % IMF content of red meat was investigated. Raman and FTIR systems were utilized to assess quality parameters of intact red meat. Quantitative models were built using PLS, with model performances assessed with respect to the determination coefficient (R2), root mean square error and normalized root mean square error (NRMSEP). Results obtained on validation against an independent test set show that the high-level fusion strategy had the best performance in predicting the observed pH; with RP2 and NRMSEP values of 0.73 and 12.9% respectively, whereas low-level fusion strategy showed promise in predicting % IMF (NRMSEP = 8.5%). The fusion of data from more than one technique at low and high level resulted in improvement in the model performances; highlighting the possibility of information enhancement.

Molecular monitoring of glioblastoma's immunogenicity using a combination of Raman spectroscopy and chemometrics.

Raman spectroscopy (RS) has been used as a powerful diagnostic and non-invasive tool in cancer diagnosis as well as in discrimination of cancer and immune cells. In this study RS in combination with chemometrics was applied to cellular Raman spectral data to distinguish the phenotype of T-cells and monocytes after incubation with media conditioned by glioblastoma stem-cells (GSCs) showing different molecular background. For this purpose, genetic modulations of epithelial-to-mesenchymal transition (EMT) process and expression of immunomodulator CD73 were introduced. Principal component analysis of the Raman spectral data showed that T-cells and monocytes incubated with tumour-conditioned media (TCMs) of GSCs with inhibited EMT activator ZEB1 or CD73 formed distinct clusters compared to controls highlighting their differences. Further discriminatory analysis performed using linear discriminant analysis (LDA) and support vector machine classification (SVM), yielded sensitivities and specificities of over 70 and 67% respectively upon validation against an independent test set. Supporting those results, flow cytometric analysis was performed to test the influence of TCMs on cytokine profile of T-cells and monocytes. We found that ZEB1 and CD73 influence T-cell and monocyte phenotype and promote monocyte differentiation into a population of mixed pro- and anti-tumorigenic macrophages (MΦs) and dendritic cells (DCs) respectively. In conclusion, Raman spectroscopy in combination with chemometrics enabled tracking T-cells and monocytes.

Monitoring the Isothermal Dehydration of Crystalline Hydrates Using Low-Frequency Raman Spectroscopy.

Detection of the solid-state forms of pharmaceutical compounds is important from the drug performance point of view. Low-frequency Raman (LFR) spectroscopy has been demonstrated to be very sensitive in detecting the different solid-state forms of pharmaceutically relevant compounds. The potential of LFR spectroscopy to probe the in situ isothermal dehydration was studied using piroxicam monohydrate (PXM) and theophylline monohydrate (TPMH) as the model drugs. The dehydration of PXM and TPMH at four different temperatures (95, 100, 105, and 110 °C and 50, 60, 70, and 80 °C, respectively) was monitored in both the low- (20-300 cm-1) and mid-frequency (335-1800 cm-1) regions of the Raman spectra. Principal component analysis and multivariate curve resolution were applied for the analysis of the Raman data. Spectral differences observed in both regions highlighted the formation of specific anhydrous forms of piroxicam and theophylline from their respective monohydrates. The formation of the anhydrous forms was detected on different timescales (approx. 2 min) between the low and mid-frequency Raman regions. This finding highlights the differing nature of the vibrations being detected between these two spectral regions. Computational simulations performed were also in agreement with the experimental results, and allowed elucidating the origin of different spectral features.

Diagnostics of skin features through 3D skin mapping based on electro-controlled deposition of conducting polymers onto metal-sebum modified surfaces and their possible applications in skin treatment.

Analytical diagnostics of skin features was developed through application of portable and fast skin mapping based on electro-controlled deposition of conducting polymers onto metal-sebum modified surfaces. In this analytical diagnostic technique, the development of skin pattern is based on electropolymerization of conducting polymers within insulating barriers in skin stamp provided by natural sebum to monitor the 3D nature of various skin features. The recorded skin maps reach a µm-level resolution and are proved to be capable of recognition, enhancement, and reproduction of surface outlines of various skin topographies, subsequently assisting dermatological diagnosis. The technique can precisely record skin surface morphology and reflect the vertical dimension information within 10 min and is aimed to assist dermatologists working with patients suffering from skin diseases via recording or monitoring the skin surface conditions. Additionally, successful trials of loading and electro-controlled release of Cu2+ into/from the developed skin patterns reveals its potential to be also utilized for treatment of pathological skin conditions. Based on the developed analytical diagnostic technique, a well-designed 3D printed portable prototype device based on electrosynthesis of the conducting polymer powered by an ordinary battery (1.5 V) was tested and was found to have excellent performance in onsite 3D skin pattern reproduction from live human skin.

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy.

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spectroscopy posit an effective technique for red meat discrimination.