Cellulose has been integral to a range of essential applications throughout history and remains relevant today. This research highlights an important topic: the study of cellulose-based and wood-derived supports in works by Portuguese artists from the twentieth century. Such an investigation is valuable for conservation and heritage science, as materials such as cardboard, plywood, hardboard, and particleboard are common in modern and contemporary artworks but are often not thoroughly characterized or discussed. Micro-infrared spectroscopy, when combined with reference materials, offers a promising means of identifying and analyzing these supports. The study focuses on works by Portuguese artists from 1915 to 1986. Applying principal component analysis to infrared data in the 1000–1200 cm−1 range enabled us to distinguish among the artists. For Pomar, Rodrigo, Vespeira, Calvet, and Hatherly, using hardboard in this range appears most suitable. For Salazar, Teles, and Pinheiro, particleboard is the optimal choice. Beech and eucalyptus plywood are preferable for Pires Vieira and Carlos Botelho. The effort to connect material knowledge with sustainable conservation practices is commendable. The research also aims to relate cellulose-based supports adhering to the European Union’s Sustainable Development Goals, fostering more sustainable and meaningful approaches to cultural preservation.

Fluoride (F) exposure is widely recognized for its role in systemic fluorosis; however, its effects on alveolar bone, a structurally and functionally complex tissue, remain poorly understood. This study investigated the molecular, physicochemical, and morphological alterations in alveolar bone following prolonged, dose-dependent F exposure. Thirty male Swiss mice were assigned to three groups receiving deionized water containing 0, 10, or 50 mg F/L for 60 days. Plasma F levels were measured, and hemimandibles were analyzed using proteomics, gene expression, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, micro-computed tomography, as well as osteocyte density and collagen content assessments. F exposure increased plasma levels in a dose-dependent manner and promoted molecular dysregulation involving proteins associated with DNA organization, cytoskeleton, and energy metabolism, alongside altered expression of genes related to BMP, TGFB1, IL, CCL, MMP, and RANKL pathways. These changes were accompanied by modifications in the mineral and physicochemical profile, including reduced crystallinity and alterations in phosphate, carbonate, and amide composition. Structural impairments were evidenced by reduced osteocyte density, decreased collagen content, and compromised alveolar bone architecture, particularly at higher exposure levels. Collectively, these findings demonstrate that prolonged fluoride exposure induces dose-dependent alterations linking molecular dysregulation to structural impairment in alveolar bone, providing mechanistic insight into how environmental exposure may impact oral tissue integrity and function.

Secondary raw materials (SRM) such as phosphogypsum, pyritic mining wastes, and metallurgical slags constitute increasingly important alternative sources of critical raw materials within circular economy strategies. However, these materials commonly exhibit strong compositional heterogeneity at micro- to millimeter scales, making their characterization challenging using conventional bulk analytical approaches. This study presents a multivariate n-dimensional synthetic µ-XRF fluorescence mapping workflow for the automated characterization and classification of heterogeneous secondary resources. High-resolution µ-EDXRF elemental maps were integrated into multidimensional feature spaces combining elemental intensities, spatial relationships, and statistical descriptors. Unsupervised machine learning approaches, including hierarchical clustering, K-means and Gaussian mixture models (GMM), were applied to identify compositional domains and reconstruct synthetic fluorescence maps representing statistically coherent elemental associations. Case studies involving phosphogypsum and slag resulting from pyrite roasting demonstrate the capability of the proposed workflow to distinguish complex mineralogical textures, identify elemental associations related to critical raw materials, and detect environmentally relevant compositional domains. The developed methodology provides a non-destructive and transferable computational framework for advanced secondary resource characterization and process-oriented evaluation of complex waste-derived materials.

Phosphogypsum (PG), a by-product of wet-process phosphoric acid production, presents a promising secondary source of rare earth elements (REEs) due to its significant REEs concentrations and high production volumes. This study has two main objectives: first, to analyze and compare the chemical and mineralogical compositions of two PG types, magmatic PG (MPG) from the Wizów Chemical Plant in Poland and sedimentary PG (SPG) from the Jorf Lasfar plant in Morocco, using various characterization techniques; and second, to explore the leaching behavior of REEs from PG using different acids and additives. Leaching experiments were carried out with 2 M H2SO4 alone, as well as in combination with oxidizing agents (NaClO3 and H2O2) and reducing agents (Fe and Zn), which are introduced here for the first time to improve REEs extraction from PG. The results demonstrated that MPG achieved a high REE recovery rate of 85% using 2 M H2SO4 alone. In contrast, SPG showed a lower recovery of 34% under the same conditions, which increased to 46% with H2O2 and 48% with Fe, while the combined use of NaClO3 and Fe resulted in 47% recovery. These additives had no significant effect on MPG. Micro-EDXRF analysis revealed that the disparity in leaching performance is attributed to the differing REEs occurrences: MPG hosts REEs as soluble salts, whereas in SPG, REEs are structurally incorporated into the gypsum matrix via isomorphic substitution, making them less accessible. Effective REEs recovery from PG not only mitigates environmental contamination but also supports its valorization in agriculture and construction, aligning with circular economy and sustainability goals.

Determination of elemental concentrations in biological tissues is crucial for realizing both normal physiological functions and disease-related processes. Energy Dispersive X-ray Fluorescence (EDXRF) aided by the Fundamental Parameters (FP) method offers an accurate, reliable, non-destructive and multi-element approach for that purpose, nonetheless, its quantitative accuracy is known to be influenced by sample thickness and matrix effects. This study aims to assess the impact of sample's available mass, hence, pellet thickness on the quantification accuracy of FP method when applied to EDXRF spectra. This way, pressed pellets of NIST SRM 1566 Oyster Tissue were prepared at varying thicknesses (1.28-8.70 mm) and analyzed using an EDXRF system to systematically evaluate the impact of thickness on elemental intensities and calculated concentrations. Results show that for light and medium elements (P, S, Cl, K, Ca, Mn, Fe), both net intensities and concentrations remain largely independent of pellet thickness, indicating that saturation conditions are achieved even in relatively thin samples. In contrast, higher-Z elements (Cu, Zn, Br) exhibit clear thickness dependence at lower pellet thicknesses, with concentrations increasing progressively as saturation is approached. Residual deviations from certified values persist for most elements regardless of thickness, demonstrating that matrix assumptions in the FP model, rather than sample geometry, are the primary source of quantitative uncertainty. These findings demonstrate that pellet thickness is a critical factor for accurate quantification of heavier elements but less relevant for lighter elements, providing practical guidance for sample preparation in biomedical EDXRF studies using low available amounts of sample.

Early detection of dental caries remains a significant clinical challenge, as conventional diagnostic methods lack sensitivity for incipient lesions. Raman spectroscopy offers high chemical specificity for enamel characterization; however, clinical translation is hindered by the complexity of conventional polarized confocal systems. In this work, we present a Raman-based fiber-optic sensing approach for the detection and classification of dental enamel conditions, including sound, affected, and carious tissues. A custom fiber-optic probe was developed for remote measurements and evaluated against a reference polarized confocal Raman system. In addition to spectral discrimination, key factors affecting sensing performance were investigated, including spatial variability across enamel surfaces and angular sensitivity due to probe misalignment. Raman-derived features (carbonate-to-phosphate ratio, phosphate peak intensity, position, and bandwidth) were analyzed using a multinomial logistic regression classifier. The fiber-optic sensor achieved an overall classification accuracy of 73% (F1-scores: 0.55 sound, 0.63 affected, 0.9 carious), confirmed by leave-one-tooth-out cross-validation. Probe misalignment studies revealed robustness up to 10° angular deviation. These results demonstrate that a simplified non-polarized fiber-optic Raman system provides competitive diagnostic performance and clinically relevant robustness, supporting its development as a point-of-care sensing platform for early dental caries detection.

In situ X-ray fluorescence is a non-invasive technique that is widely used in historical objects, namely in pieces of gilded silver, to determine the composition of the alloy and gilding. In the case of gilded silver, fire gilding was a mercury-based historical technique that is no longer practiced. Moreover, with traditional XRF analysis is possible to determine the thickness of the gilding by using given intensity ratios of the characteristic lines of silver. However, this requires the analysis of the substrate, for the calculation of the intensity ratio without gilding, which is not always accessible. This study presents and validates a methodology for the calculation of the thickness of fire gilding silver pieces using XRF analysis with a commercial spectrometer and without the need to analyse the isolated substrate. Six silver alloy mock-up samples were produced following historical techniques and generic intensity ratio for K alpha and K(3 lines of silver in the alloy was calculated (6.35 +/- 0.05), to be used in any alloy with a silver composition over 75 %. Since attenuation of the silver's characteristic lines depends on the gilding composition, different Hg concentrations (5 %-20 %) were tested. The results obtained with this approach for the mock-ups was compared with SEM-EDS measurements for gauging uncertainty and the methodology was then applied to three pieces of 16th century Portuguese silverware. This adaptation of previously established principles, proved to be effective to calculate the thickness of fire gilding on silver and was validated to be applied, in situ, in real museum artworks without the need for sample collection.

Phosphogypsum (PG), a by-product of the fertilizer industry, is a potential source of rare earth elements (REEs) such as Lanthanum (La), Cerium (Ce), Neodymium (Nd), and Yttrium (Y). These elements were efficiently detected using micro-Energy Dispersive X-Ray Fluorescence (μ-EDXRF). Although a homogeneous REE distribution was expected in μ-EDXRF 2D maps, significant heterogeneity and variations in elemental associations (EA) were observed at a micrometric scale. To enhance and better interpret μ-EDXRF mapping results, a specialized image processing methodology was developed, incorporating Principal Component Analysis (PCA), Hierarchical Clustering (HC), and Multiple Linear Regression (MLA) which were applied to process and analyse 2D RGB pixel data. Identification of spatial overlaps, and multivariate correlations among the detected elements could be achieved. Notably, distinct EA patterns were found, with Ti, Ba, Y, and K playing a key role in REEs spatial distribution. Strong positive spatial correlations were identified between La and Ti, while Ce, Nd, and Y exhibited independent spatial distributions relative to La in certain sample areas. MLA further revealed strong EA between La, Ce, Nd, Y, and K, particularly in locations where Ti or Ba were also present. Additional elemental interactions were detected with Al, Cl, Ni, and Fe, with P and Cl showing significant correlations. Multicollinearity effects suggest strong interdependencies among elements. These findings highlight distinct REE spatial distributions within PG, demonstrating that mineralogical and compositional variations within the PG matrix influence REE spatial distribution patterns. Understanding these associations can improve strategies for REEs recovery from PG waste.

Excessive fluoride (F) exposure is associated with adverse effects at different life stages and can affect various biological systems, including the mineralized tissues of the oral cavity. However, there is limited evidence that early F exposure during pregnancy and lactation impairs the development of offspring dental enamel. From a translational perspective, this study aimed to investigate the effects of F at different concentrations on the ultrastructural, physicochemical, and functional properties of dental enamel in the offspring of rats exposed during the prenatal and lactation periods. Pregnant Wistar rats were divided into: control (deionized water), 10 mg F/L, and 50 mg F/L. F exposure was conducted from the first day of pregnancy until the 21st day of lactation. Enamel samples from the offspring's upper incisors were collected to evaluate F levels, ultrastructural characteristics, and physicochemical composition through scanning electron microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Raman spectroscopy, and X-ray diffraction (XRD). The results showed that increased levels of F triggered changes in phosphate and carbonate contents, with no alterations in the ultrastructure of the prisms or enamel crystallinity. Nevertheless, a significant increase in enamel hardness was observed in F exposed groups. These findings suggest that while F exposure did not affect the ultrastructure integrity of enamel, it significantly altered its chemical composition and mechanical properties. Our data suggest that maternal exposure to excessive levels of F during the prenatal and lactation periods leads to increased enamel hardness, which could impact enamel friability.

Energy dispersive X-ray fluorescence spectrometry has been widely used for the analysis of trace and minor elements in applications that extend from biomedical to environmental assessment, due to its non-destructive nature, rapid analysis and suitable detection limits. However, EDXRF quantification is frequently hampered by matrix effects, introducing significant inaccuracies in the obtained results. In this work, we present an automated methodology for sample matrix determination using EDXRF spectra, leveraging on the analysis of the Compton and Rayleigh peaks of the characteristic lines of the X-ray tube anode. First, a model was created to fit these scattering peaks, allowing the plotting of a calibration curve that correlated the Compton-to-Rayleigh ratio with the average atomic number (Z) of the sample. Matrix composition was quantified using a developed algorithm combining support vector regression (SVR) and bootstrapping to optimize the determination of the best matrix composition. SVR with a Radial Basis Function kernel was applied to handle non-linear data, and Bootstrapping was utilized to train the algorithm, enhancing model generalization. The study demonstrates that the developed algorithm and matrix-based approach effectively quantified elemental compositions across various certified reference materials (CRMs). The chosen Matrix provided more accurate results, especially for heavier elements like Fe, Cu, and Zn, while deviations of around 20% were observed for lighter elements in biological matrices. In geological samples like phosphate rock and clay, heavier elements aligned well with reference values, but trace elements like Cu and Ni showed larger deviations due to low concentrations. Despite discrepancies for some elements like Pb in wood, the methodology proved effective, particularly for elements like Cr with minimal deviation, highlighting its versatility across diverse matrices. The methodology successfully integrated computational tools and open-source libraries to establish a reliable, efficient workflow for average atomic number determination and spectral analysis, achieving strong agreement with reference materials.

Management and reuse of wood waste can be a challenging process due to the frequent presence of hazardous contaminants. Conventional detection methods are often limited by the need for excessive sample preparation and lengthy and expensive analysis. Laser-induced Breakdown Spectroscopy (LIBS) is a rapid and micro-destructive technique that can be a promising alternative, providing in-situ and real-time analysis, with minimal to no sample preparation required.In this study, LIBS imaging was used to analyze wood waste samples to determine the presence of contaminants such as As, Ba, Cd, Cr, Cu, Hg, Pb, Sb, and Ti. For this analysis, a methodology based on detecting three lines per element was developed, offering a screening method that can be easily adapted to perform qualitative analysis in industrial contexts with high throughput operations. For the LIBS experimental lines selection, control and reference samples, and a pilot set of 10 wood wastes were analysed. Results were validated by two different X-ray Fluorescence (XRF) systems, an imaging XRF and a handheld XRF, that provided spatial elemental information and spectral information, respectively. The results obtained highlighted LIBS ability to detect highly contaminated samples and the importance of using a 3-line criteria to mitigate spectral interferences and discard outliers.To increase the dataset, a LIBS large-scale study was performed using 100 samples. These results were only corroborated by the XRF-handheld system, as it provides a faster alternative. In particular cases, ICP-MS analysis was also performed. The success rates achieved, mostly above 88%, confirm the capability of LIBS to perform this analysis, contributing to more sustainable waste management practices and facilitating the quick identification and remediation of contaminated materials.

Globally, there is a growing demand for healthy and sustainable food products, where seafood can play a relevant role, because it is widely recognized as a healthy food item and is an important source of essential nutrients. Still, one third of the world population suffers from food insecurity and different forms of malnutrition. Hence, developing tailor-made fortified farmed fish is a promising solution to overcome nutritional deficiencies and increase consumer confidence in these products. The aim of this study is to evaluate differences in nutritional elements distribution in biofortified and non-biofortified fillets from gilthead seabream and common carp, using micro-X-ray fluorescence (mu-XRF). This technique is a fast and nondestructive multielement mapping method with simple operation and sample preparation procedures. Results showed that calcium was mainly accumulated in the skin layer, which includes the scales and spines (skeleton), whereas iron, potassium, and zinc were uniformly distributed in the fish muscle. Compared with the control, biofortified gilthead seabream fillets showed a higher concentration of iron in the inner area of the skin layer (dermis) and muscle tissue, whereas biofortified common carp fillets showed a higher concentration of iron in muscle tissue and zinc in the abdominal cavity tissue of the sample. This study demonstrates that micro-X-ray is a suitable technique to assess the elemental distribution with micrometer resolution in fish fillets.

The uptake of fluoride in the enamel matrix is an effective strategy to prevent demineralization and caries formation. In this study a comprehensive methodology is developed to evaluate and understand the uptake of fluoride in human enamel. Twenty-six healthy anterior teeth were sectioned in half; one half remained untreated, while the other was treated with 50 mg mL-1 NaF (equivalent to 22.6 mg of fluoride) through three 1-minute applications over a 12-day period, following the manufacturer's guidelines. Fluoride uptake was quantified with particle-induced gamma-ray emission (PIGE), revealing an average increase of 160% in treated samples. The formation of calcium fluoride (CaF2) and fluorapatite-like structures was confirmed through near edge X-ray absorption fine structure (NEXAFS) analysis. Due to the absence of reference spectra for hydroxyapatite, fluorapatite, and calcium fluoride, finite difference method near edge structure (FDMNES) simulations were employed to computationally model the fluorine K-edge and the Ca L-edge spectra. Density functional theory (DFT) and time-dependent DFT (TDDFT) approaches were applied to enhance spectral accuracy, enabling a refined comparison with experimental data. To establish a rapid and laboratory-based screening technique, Raman microscopy was used to analyze fluoride-treated and untreated samples. Spectral data were evaluated using both full-spectrum analysis and specific spectral features, including band intensity, full-width at half maximum (FWHM) of Raman peaks, and phosphate symmetric stretching depolarization ratios. Furthermore, machine learning algorithms were applied to classify treated and untreated enamel samples. The random forest classifier demonstrated strong predictive performance, successfully distinguishing fluoride-treated samples. This methodological approach provides an effective framework for analyzing fluoride uptake in enamel, potentially guiding future preventive dentistry strategies.

This article discusses the results of an interlaboratory comparison for the analysis of elemental concentration in human hair samples as an example of a human biological material. The analysis concerned the determination of the content of the following elements: P, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Mo, Pb and Hg. Six laboratories from five countries (Poland, Germany, Spain, Portugal, and Croatia) participated in the interlaboratory comparison and performed the analyses using the following methods: TXRF (three laboratories), mu-EDXRF (one laboratory), ICP-OES (one laboratory), and ICP-MS (two laboratories). The statistical analysis of the results was performed separately for the TXRF measurements and also including the results obtained using other measurement techniques. The element concentrations obtained by TXRF cover wide range from about 0.2 mg/kg (Mn As Se Rb Sr Pb) to 37,000 mg/kg (S). Additionally, for the TXRF technique, the detection limits (from 0.1 mg/kg to 20-80 mg/kg (the lightest element P)) as well as the intra-day (from 0.2 % to 22 %) and inter-day (from 0.3 % to 19 %) precisions were estimated. For identification and rejection of outliers the Dixon's and the Grubbs' tests were applied. For the remaining results the consensus mean values and standard deviations of element concentrations were calculated. Next, these parameters were used to determine the z-scores for concentration of each element ranging in the interval-2 <= z <= 2. In order to compare the dispersion of results, coefficients of variation were determined. It was shown, that the value of variation coefficient depends on the studied element and its concentration in the sample. The obtained results made it possible to estimate the reproducibility of elemental analysis of hair samples performed using various methods in a wide range of atomic numbers and element contents.

BACKGROUND:The accurate detection and quantification of elemental content in skin appendages, such as, hair and nails are pivotal in biomedical research, including disease diagnostics, environmental exposure monitoring, and forensic investigations. METHODS:This study evaluates and compares the suitability of different sample treatments and four spectroscopic techniques-Energy Dispersive X-ray Fluorescence (EDXRF), Total Reflection X-ray Fluorescence (TXRF), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) for multielemental analysis of these biological tissues. Making use of different Certified Reference Materials (CRMs), the performance of the developed methods was assessed based on their sensitivity, precision, range of detectable elements, and the extent of sample preparation required. RESULTS:EDXRF method is suited for rapid and non-destructive determination of light elements present at relatively high concentrations - Sulfur (S), Chlorine (Cl), Potassium (K) and Calcium (Ca) - in hair and nail samples. TXRF provides information of most of the elements present in the target samples, including Bromine (Br), but the determination of light element (i.e, Phosphorus (P), S, Cl) is not feasible. Finally, the proposed ICP-OES/ICP-MS method is useful for the determination of major, minor and trace elements, except chlorine. CONCLUSION:This comparative study reveals the distinct strengths, range of elements and suitable applications of each technique, providing a valuable framework for selecting appropriate methods based on specific analytical needs.

Tissue specimens processed as Formalin-Fixed Paraffin-Embedded (FFPE) blocks are routinely collected during interventions for diagnostic purposes and stored for archival purposes. However, the elemental composition of these FFPE tissue samples remains largely unexplored due to the lack of suitable analytical tools. This study aimed to address this gap by investigating the elemental composition of FFPE tissue samples using Energy-Dispersive X-ray Fluorescence (EDXRF) spectroscopy. A total of 18 sets of mirrored tissue samples, processed either as pellets or FFPE blocks, were analyzed to develop calibration curves and assess the influence of paraffin embedding on elemental peak intensities (specifically S, Ca, Fe, Cu, and Zn) in the EDXRF spectrum. An additional set of samples was used for validation by comparing the intensity obtained from FFPE tissue blocks to that obtained from pellets (considered the true value). Our results demonstrate that the intensities obtained using this procedure exhibit a bias towards the true value of less than 9% for all elements analyzed. Furthermore, after applying calibration curves using the External Calibration Method, the concentrations of S, Ca, Fe, Cu, and Zn obtained from FFPE and pellet samples were not statistically different. These findings highlight the feasibility and accuracy of using EDXRF spectroscopy for elemental analysis of FFPE tissue samples, overcoming the limitations posed by the paraffin embedding process. This study contributes valuable insights into the elemental composition of FFPE tissue samples and paves the way for further research in biomedical and clinical applications.

Lead poisoning is a global public health concern. Maternal exposure during intrauterine and lactational periods can present a higher susceptibility of harm to the offspring. Thus, pregnant female Wistar rats (Rattus norvegicus) were randomly divided in two experimental groups: control group and Lead group. The animals were exposed to 50 mg/kg of Lead Acetate daily for 42 days (21 days of gestational period + 21 days of lactational period). After the exposure period, the mandibles of the offspring were collected for lead quantification, Raman spectroscopy analysis, micro-CT, morphometric e histochemical analysis. Lead exposure altered the physical–chemical composition of alveolar bone and caused histological damage associated with a reduction in osteocyte density and collagen area fraction, increase in collagen maturity, as well as a reduction in bone volume fraction. An increase in trabecular spaces with anatomical compromise of the vertical dimensions of the bone was observed. Thus, the results suggest that developing alveolar bone is susceptible to toxic effects of lead when organisms are exposed during intrauterine and lactation periods.

The use of bleaching agents to remove stains is one of the main dental procedures to improve the aesthetics of teeth. This review presents the main agents used for tooth whitening, existing clinical protocols, and the structural changes that may occur through their use. The main bleaching agents consist of hydrogen peroxide and carbamide peroxide, which are used in bleaching techniques for vital teeth. These techniques can be performed in the office by a professional or by the individual in a home en-vironment under professional guidance. Bleaching agents come in a variety of concentrations and there are over-the-counter products available on the market with lower concentrations of hydrogen peroxide. Due to the chemical characteristics of the agents, changes in the organic and inorganic content of the tooth structure can be observed. These changes are related to morphological changes characterized by in-creased permeability and surface roughness, such changes compromise the mechanical resistance of the tooth. Furthermore, bleaching agents can promote molecular changes after reaching the dental pulp, resulting in oxidative stress of pulp cells and the release of pro-inflammatory mediators. Despite the bleaching effectiveness, tooth sensitivity is considered the main side effect of use. Therefore, among the heterogeneity of protocols, those that used the bleaching agent for a prolonged time and in lower con-centrations presented more harmful effects on the tooth structure.