Applicability of Low-Cost Binders for the Quantitative Elemental Analysis of Urinary Stones Using EDXRF Based on Fundamental Parameter Approach

Utilizing X-ray fluorescence (XRF) method to evaluate the content of metal elements in soil and their effects on the total phenolic and flavonoid contents of some medicinal plants

Soil factors, especially metal elements in the soil, play a significant role in forming and accumulating secondary metabolites, which determine the medicinal properties of medicinal herbs. In this study, the concentrations of some metal elements (K, Mn, Fe, Cu, Zn, and Cr) in Cam Mountain and Tinh Bien Town, An Giang Province, Vietnam, were determined using the XRF method. We simultaneously determined the total phenolic and flavonoid content of some medicinal herbs collected from the collected soil sample areas, thereby assessing the influence of these elements on the formation of secondary metabolites in medicinal plants. The results showed that K, Mn, and Cr were mainly concentrated in the topsoil and transition layers; Fe and Cu elements tended to concentrate in the transition layer and the subsoil when surveying the soil profile. K, Mn, Cu, and Cr concentrations were more focused in Tinh Bien area, while Fe and Zn had higher concentrations at Cam Mountain. Additionally, results from evaluating the relationship between the content of the elements in the soil and the content of two active compounds also showed the correlation regression model between Zn and flavonoid expression by level 4 at the 5% significance level. Thus, the nonlinear model is suitable for evaluating the relationship between the content of metal elements in the soil and the active compound in medicinal plants.

Quantitative analysis of heavy metals in soil by X-ray fluorescence with PCA-ANOVA and support vector regression

Heavy metal concentration is an important index for evaluating soil pollution. It is of great significance to measure the trace element content accurately for green agriculture development. In order to detect the trace element content accurately, a new prediction framework including pre-processing, signal extraction, feature selection and decision-making was proposed. The energy dispersive X-ray fluorescence (ED-XRF) spectra of 57 national standard soil samples were investigated based on the proposed methods. Firstly, an innovative background deduction method called iterative adaptive window empirical wavelet transform (IAWEWT) was introduced to extract effective counts of characteristic peaks, and the proposed approach was validated by the coefficient of determination (R²) of the instrumental calibration curve compared with two other conventional methods. Secondly, principal component analysis (PCA) was combined with the analysis of variance (ANOVA) for variable selection optimization of the ED-XRF spectrum. After PCA feature extraction and ANOVA variable selection treatment, the optimum number of principal components for V, Cr, Cu, Zn, Mo, Cd and Pb were determined to be 7, 15, 4, 4, 4, 5 and 12 respectively. Furthermore, the support vector regression (SVR) model was adopted for heavy metal estimation. The evaluation indices included R² and root mean square error (RMSE). It was demonstrated that the predictive capabilities of seven heavy metal elements were improved substantially for elemental analysis by the proposed PCA-ANOVA-SVR model, with excellent results for V, Cr, Cu, Zn, Mo, Cd and Pb estimates, and the R² values were 0.993, 0.996, 0.999, 0.999, 0.997, 0.998 and 0.998 respectively. Therefore, the new framework proposed in this paper can effectively eliminate redundant features and determine the concentration of trace elements in soil. It provides an effective alternative for the quantitative analysis of X-ray fluorescence spectrometry.

Seasonal Variability of Elemental Composition and Phytochemical Analysis of Moringa oleifera Leaves Using Energy-Dispersive X-ray Fluorescence and Other Related Methods

The elemental contents and the phytochemical components of Moringa oleifera are crucial for nutrition and medical purposes. Therefore, the monthly and seasonal variations of the elemental composition and phytochemical analysis of Moringa oleifera leaves collected from the same ecological area have been investigated. For this purpose, Moringa oleifera leaves were collected monthly from the same tree's branches during the whole year from January 2019 to December 2019. A non-destructive elemental analysis technique was used, namely energy-dispersive X-ray fluorescence spectrometry. The seasonal variations are different from one season to another. The highest concentrations of Mo, Cr, Fe, Ti, and Si were found during winter, whereas the highest concentrations of Br, Cl, and Cu were found during the summer seasons. Based on Pearson's correlation analysis, a strong correlation between Ca and Sr was found, whereas Sr has a negative correlation with other detected elements. Similarly, Cu and Zn as well as Br and Cl have a strong correlation. Remarkable different concentrations were found during May which has the lowest positive correlation. The phytochemical analysis revealed that Moringa oleifera leaves collected during the spring season resulted in the highest chlorophyll content, phenol content, and the greatest scavenging activity. Therefore, the mineral contents and phytochemical compounds are affected by the changing of the seasons of the year. Collectively, the current results are useful for optimizing the harvest time of Moringa oleifera leaves with respect to the quality.

Spectroscopic Characterization of Urinary Stones Richening with Calcium Oxalate

Intact and non-intact urinary stones richening with calcium oxalate were collected and characterized. The elemental analysis, phase quantifications, and function groups were determined by different spectroscopic techniques, namely: energy-dispersive X-ray fluorescence (EDXRF), the synchrotron radiation X-ray diffraction (SR-XRD), and attenuated total reflection Fourier transform infrared (ATR-FTIR). The quantitative analysis of twenty elements was demonstrated in the most of the urinary stones and these elements are: Ca, Na, P, S, Mg, Cl, Zn, K, Ti, Sr, Ni, Co, Fe, Cu, Cd, Br, Pb, Se, I, and Mn. Using the Rietveld method, the diffraction phase quantification was illustrated. The main found phases are calcium oxalate (monohydrate and dihydrate) and hydroxyapatite phase. The FTIR outcomes reveal that the functional groups of O-H, N-H, C=O, and C-O indicate to the calcium oxalate whereas the P-O and O-P-O, and PO₄^3- groups indicate to the calcium phosphates in the hydroxyapatite. A considerable correlations between the oxalate urinary stones and the group of elements were found. These elements are Zn, Sr, Ni, and Fe. These correlations could lead to new therapeutic approaches. Furthermore, the elements of sodium and chlorine have no vital role in the formation of calcium oxalate urinary stones.