New insights into the Argan oil categories characterization: Chemical descriptors, FTIR fingerprints, and chemometric approaches

Diagnosis of Lung Cancer by ATR-FTIR Spectroscopy and Chemometrics

Lung cancer is the leading cause of cancer-related death in the world. Early diagnosis has great significance for the survival of patients with lung cancer. In this paper, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics was used to study the serum samples from patients with lung cancer and healthy people. The results of spectral band area comparison showed that the concentrations of protein, lipid and nucleic acids molecules in serum of patients with lung cancer were increased compared with those in healthy people. The original spectra were preprocessed to improve the accuracy of principal component regression (PCR) and partial least squares-discriminant analysis (PLS-DA) models. PLS-DA results for first derivative spectral data in nucleic acids (1250-1000cm-1) band showed 80% sensitivity, 91.89% specificity and 87.10% accuracy with highR c 2 of 0.8949 andR v 2 of 0.8153, low RMSEC of 0.3136 and RMSEV of 0.4180. It is shown that ATR-FTIR spectroscopy combined with chemometrics might be developed as a simple method for clinical screening and diagnosis of lung cancer.

Wax Separated Effectively from Fischer-Tropsch Wax Residue by Solvent Desorption: Thermodynamic and Kinetic Analysis

The separation and recycling of effective resources in Fischer-Tropsch wax residue (FTWR) are urgent because of the environmental hazards and energy waste they bring. In this study, organic solvents are used to separate recyclable resources from FTWR efficiently, achieving the goals of “Energy Recycle” and “Fisher-Tropsch Wax Residue Treatment”. The response surface methodology (RSM) response surface analysis model accurately evaluates the relationship among temperature, residence time, liquid–solid ratio, and desorption rate and obtains the best process parameters. The results show that the product yield can reach 82.28% under the conditions of 80 °C, 4 h, and the liquid–solid ratio of 24.4 mL/g. Through the kinetic analysis of the desorption process of FTWR, the results show that the desorption process conforms to the pseudo second-order kinetic model and the internal diffusion model. The thermodynamic function results showed that there were not only van der Waals forces in the desorption process, but other strong interaction forces such as hydrogen bonds. In addition, Langmuir, Freundlich, and BET equations are used to describe the desorption equilibrium. Scanning electron microscopy (SEM) were used to analyze the pore structure of FTWR during desorption. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and Gas chromatography-mass spectrometer (GC-MS) analysis confirmed that the desorption product’s main component was hydrocarbons (50.38 wt%). Furthermore, naphthenic (22.95 wt%), primary alcohol (11.62 wt%), esters (8.7 wt%), and aromatic hydrocarbons (6.35 wt%) compounds were found and can be further purified and applied to other industrial fields. This study shows that using petroleum ether to separate and recover clean resources from Fischer-Tropsch wax residue is feasible and efficient and has potential industrial application prospects.

Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way models which were used for analyzing NIRS data, as well as the advances, advantages and limitations of different multi-way models. The applications of multi-way analysis in NIRS for the food industry in terms of food process control, quality evaluation and fraud, identification and classification, prediction and quantification, and image analysis are also reviewed. It is evident from this report that multi-way analysis is presently an attractive tool for modeling complex NIRS data in the food industry while its full potential is far from reached. The combination of multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding about food systems and food processes. To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of multi-way analysis in NIRS for the food industry.