Nanoscale elemental and morphological imaging of nitrogen-fixing cyanobacteria.

Nitrogen-fixing cyanobacteria bind atmospheric nitrogen and carbon dioxide using sunlight. This experimental study focused on a laboratory-based model system, Anabaena sp., in nitrogen-depleted culture. When combined nitrogen is scarce, the filamentous prokaryotes reconcile photosynthesis and nitrogen fixation by cellular differentiation into heterocysts. To better understand the influence of micronutrients on cellular function, 2D and 3D synchrotron X-ray fluorescence mappings were acquired from whole biological cells in their frozen-hydrated state at the Bionanoprobe, Advanced Photon Source. To study elemental homeostasis within these chain-like organisms, biologically relevant elements were mapped using X-ray fluorescence spectroscopy and energy-dispersive X-ray microanalysis. Higher levels of cytosolic K+, Ca2+, and Fe2+ were measured in the heterocyst than in adjacent vegetative cells, supporting the notion of elevated micronutrient demand. P-rich clusters, identified as polyphosphate bodies involved in nutrient storage, metal detoxification, and osmotic regulation, were consistently co-localized with K+ and occasionally sequestered Mg2+, Ca2+, Fe2+, and Mn2+ ions. Machine-learning-based k-mean clustering revealed that P/K clusters were associated with either Fe or Ca, with Fe and Ca clusters also occurring individually. In accordance with XRF nanotomography, distinct P/K-containing clusters close to the cellular envelope were surrounded by larger Ca-rich clusters. The transition metal Fe, which is a part of nitrogenase enzyme, was detected as irregularly shaped clusters. The elemental composition and cellular morphology of diazotrophic Anabaena sp. was visualized by multimodal imaging using atomic force microscopy, scanning electron microscopy, and fluorescence microscopy. This paper discusses the first experimental results obtained with a combined in-line optical and X-ray fluorescence microscope at the Bionanoprobe.

Facilitating inorganic arsenic speciation and quantification in waters: Polymer inclusion membrane preconcentration and X-ray fluorescence detection.

BACKGROUND: Arsenic, classified as a priority pollutant and human carcinogen by the IARC, is subject to stringent regulatory limits in food and water. Among various arsenic species found in water samples, arsenite (As(III)) is identified as the most toxic form. Given the limitations of conventional spectroscopic techniques in speciation analysis, there is a crucial need for innovative and sustainable methodologies that enable arsenic speciation. Simplifying these methodologies is essential for widespread applicability and effective environmental monitoring. RESULTS: This study proposes a simple and cost-effective analytical methodology for speciating inorganic arsenic in water samples. The method involves extracting As(III) into a polymer inclusion membrane (PIM) containing the extractant Cyanex 301 (bis(2,4,4-trimethylpentyl) dithiophosphinic acid), followed by analysis using energy dispersive X-ray fluorescence (EDXRF) spectrometry. The concentration of arsenate was measured after a reduction step using a thiosulfate/iodide mixture. This simple methodology allows a limit of quantification for trivalent arsenic (2 µg L-1), which is well below the World Health Organization's recommended maximum permissible level of As in drinking water (10 µg L-1). The method that is developed allows the determination of As at trace levels in waters with naturally occurring arsenic. SIGNIFICANCE AND NOVELTY: This study represents a significant advance in the field, providing a novel and efficient methodology for arsenic speciation analysis in water samples. By combining the advantages of polymer inclusion membrane (PIM) extraction with energy dispersive X-ray fluorescence (EDXRF) spectrometry, this study offers a cost-effective and environmentally friendly approach to address the critical issue of arsenic contamination in water sources, thereby contributing to enhanced environmental monitoring and public health protection.

Complementary techniques for the reliable characterisation of tissue samples: A case study on pancreatic tumours analysed by means of X-ray fluorescence analysis and IR spectroscopy.

An improvement in the reliability and comparability of tissue characterization results is crucial for enabling further progress in cancer detection and the assessment of therapeutic effects. This can only be achieved by integrating quantitative methods into well-established qualitative characterization routines. This case study presents a hybrid metrological approach for tissue characterisation including vibrational Fourier Transform InfraRed (FTIR) spectroscopy and traceable reference-free X-Ray Fluorescence analysis (XRF). Through the combination of spatially resolved qualitative molecular information with quantitative elemental concentrations an all-encompassing sample characterisation can be provided. The study was performed on tissue sections of syngeneic murine pancreatic ductal adenocarcinoma KPC (KrasG12D/+; Trp53R172H/+; Pdx-1-Cre) tumours ex-vivo. Sections from healthy pancreatic tissues, sham-exposed tumours and tumours subjected to low dose radiotherapy treatment (2 Gray and 6 Gray) were analysed using both methods. Additional sample integrity studies using Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy at the carbon and nitrogen K-edges were performed to assess the effect of sample aging and XRF investigations on the samples. Results showed an increase in the concentrations of elemental biomarkers, including S, K and amide I structures in malignant pancreatic tissue compared to healthy pancreatic tissue. The exposure of tumours to 6 Gy radiation decreases the levels of these elements towards a phenotype seen in the healthy pancreas. A protocol for hybrid investigations is presented, with emphasis on the sample preparation, minimizing the impact of consecutive applied methods on their measurands, and ensuring the compatibility and reliability of achieved results. The study demonstrates the cancer recognition capabilities, and the sensitivity for low dosage radiotherapy treatment monitoring for each method individually and assesses the potential of combining molecular fingerprinting with non-destructive quantitative elemental information for tissue sample characterization.

Assessment of portable X-ray fluorescence (pXRF) for plant-available nutrient prediction in biochar-amended soils.

Portable X-ray Fluorescence probe (pXRF) is a tool used to measure many elements quickly and efficiently in soil with minimal sample preparation. Although this sensing technique has been widely used to determine total elemental concentrations, it has not been calibrated for plant-available nutrient predictions. We evaluated the potential of using pXRF for fast plant-available nutrient quantification. Two experiments were conducted in soils treated with two types of biochars to obtain a practical range of soil pH (5.5 - 8.0) and organic carbon (2.0 - 5.5%). Biochars applied were derived from switchgrass (SGB) and poultry litter (PLB). The first experiment received biochars at application rates up to 8% (w/w) and had no plants. The second experiment had up to 4% of SGB or PLB planted with ryegrass (Lolium perenne). Linear regression (LR), polynomial regression (PolR), power regression (PowR), and stepwise multiple linear regression (SMLR) were the models tested. Regardless of the extraction method, phosphorus (P) showed a strong relationship between pXRF and several laboratory extraction methods; however, K prediction via pXRF was sensitive to the plant factor. The optimum soil available-P corresponding to the maximum P uptake in plant tissues can be assessed with pXRF. The LR was inconsistent for calcium (Ca), sulfur (S), and copper (Cu) and non-significant for magnesium (Mg), iron (Fe), and zinc (Zn). Our results showed that pXRF is applicable to estimate P availability in soils receiving organic amendments. More evaluations are needed with diverse soil types to confirm the findings before using pXRF for fertilizer recommendation.

Examining the Physicochemical Composition of Three Bioceramic Putties for Endodontic Use.

OBJECTIVE: This study aimed to address the lack of comparative analyses of newly developed bioceramic materials by examining the chemical composition, thermodynamic profile, and microscopic surface features of three bioceramic putties: EndoSequence BC Root Repair Material Fast Set Putty (ESRRM-FS), BIO-C Repair (BCR), and Cera Putty (CP). METHODS: Samples of each of the three bioceramic putty obtained directly from manufacturers were prepared for analysis of physicochemical composition and microscopic features by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) imagery, and energy-disper-sive X-ray spectroscopy (EDS). The data obtained was qualitatively and statistically analysed. Statistical signif-icance was determined at p≤0.05. RESULTS: DSC analysis indicated a standard polymeric vehicle for BCR and CP, coinciding with the polyethene glycol (PEG) thermal profile; the polymeric vehicle in ESRRM-FS remains to be identified. The material with the highest heat capacity was CP (p<0.05), followed by ESRRM-FS and BCR. TGA revealed an inflexion point at 394.12 ºC for ESRRM-FS, which may correspond to the mass loss of dihydroxylation of calcium hydroxide. A more homogenous structure was observed in scanning electron microscopy (SEM) images for ESRRM-FS. EDS analysis indicated BCR had minimal amounts of aluminium (2.06+-0.44%) and a lower percentage of cal-cium than ESRRM-FS (9.11+-1.38% vs. 11.3+-0.87%). CP was composed of aluminium (49.35+-7.01%), carbon (30.65+-5.62%), and oxygen (16.75+-2.44%); no silicon was identified. ESRRM-FS had no aluminium present and the highest calcium percentage (11.3+-0.87%) (p<0.05). CONCLUSION: BCR is a Portland cement-derived material with a lower percentage of calcium than ESRRM-FS and minimal amounts of aluminium. CP is a monocalcium aluminate cement, mainly composed of aluminium, carbon, and oxygen. ESRRM-FS is a biphasic material with the highest calcium percentage among all materials studied and no aluminium.

Placental Element Content Assessed via Synchrotron-Based X-ray Fluorescence Microscopy Identifies Low Molybdenum Concentrations in Foetal Growth Restriction, Postdate Delivery and Stillbirth.

Placental health and foetal development are dependent upon element homeostasis. Analytical techniques such as mass spectroscopy can provide quantitative data on element concentrations in placental tissue but do not show spatial distribution or co-localisation of elements that may affect placental function. The present study used synchrotron-based X-ray fluorescence microscopy to elucidate element content and distribution in healthy and pathological placental tissue. The X-ray fluorescence microscopy (XFM) beamline at the Australian Synchrotron was used to image trace metal content of 19 placental sections from healthy term (n = 5, 37-39 weeks), foetal growth-restricted (n = 3, <32 weeks, birth weight <3rd centile), postdate (n = 7, >41 completed weeks), and stillbirth-complicated pregnancies (n = 4, 37-40 weeks). Samples were cryo-sectioned and freeze-dried. The concentration and distribution of fourteen elements were detected in all samples: arsenic, bromine, calcium, chlorine, copper, iron, molybdenum, phosphorous, potassium, rubidium, selenium, strontium, sulphur, and zinc. The elements zinc, calcium, phosphorous, and strontium were significantly increased in stillbirth placental tissue in comparison to healthy-term controls. Strontium, zinc, and calcium were found to co-localise in stillbirth tissue samples, and calcium and strontium concentrations were correlated in all placental groups. Molybdenum was significantly decreased in stillbirth, foetal growth-restricted, and postdate placental tissue in comparison to healthy-term samples (p < 0.0001). Synchrotron-based XFM reveals elemental distribution within biological samples such as the placenta, allowing for the co-localisation of metal deposits that may have a pathological role. Our pilot study further indicates low concentrations of placental molybdenum in pregnancies complicated by foetal growth restriction, postdate delivery, and stillbirth.

A supervised multiclass framework for mineral classification of Iberian beads.

Research on personal adornments depends on the reliable characterisation of materials to trace provenance and model complex social networks. However, many analytical techniques require the transfer of materials from the museum to the laboratory, involving high insurance costs and limiting the number of items that can be analysed, making the process of empirical data collection a complicated, expensive and time-consuming routine. In this study, we compiled the largest geochemical dataset of Iberian personal adornments (n = 1243 samples) by coupling X-ray fluorescence compositional data with their respective X-ray diffraction mineral labels. This allowed us to develop a machine learning-based framework for the prediction of bead-forming minerals by training and benchmarking 13 of the most widely used supervised algorithms. As a proof of concept, we developed a multiclass model and evaluated its performance on two assemblages from different Portuguese sites with current mineralogical characterisation: Cova das Lapas (n = 15 samples) and Gruta da Marmota (n = 10 samples). Our results showed that decisión-tres based classifiers outperformed other classification logics given the discriminative importance of some chemical elements in determining the mineral phase, which fits particularly well with the decision-making process of this type of model. The comparison of results between the different validation sets and the proof-of-concept has highlighted the risk of using synthetic data to handle imbalance and the main limitation of the framework: its restrictive class system. We conclude that the presented approach can successfully assist in the mineral classification workflow when specific analyses are not available, saving time and allowing a transparent and straightforward assessment of model predictions. Furthermore, we propose a workflow for the interpretation of predictions using the model outputs as compound responses enabling an uncertainty reduction approach currently used by our team. The Python-based framework is packaged in a public repository and includes all the necessary resources for its reusability without the need for any installation.

Study of multi-elemental concentration and nano-micro structural morphology in medicinal plants by FE-SEM and EDX method.

Medicinal plants of the Moraceae family, such as Ficus racemosa linn, have been traditionally used in the North Karnataka region for treating various ailments. This study aims to analyze the elemental composition and nano-micro structural morphology of selected species of Moraceae family medicinal plants, focusing on their potential therapeutic applications. Samples were collected from the Dharwad and Gadag districts in North Karnataka. The surface morphology at nano and micro levels was examined using a field emission scanning electron microscope, while the elemental composition was analyzed through energy-dispersive X-ray spectroscopy. The study emphasizes the detailed examination of the specific weight percent of elemental concentration and the morphological features observed. The analysis revealed fine, irregularly shaped particles with an average diameter of 20 to 50 µm on the plant surface. Elemental composition analysis showed the presence of Mg, Al, Si, Cl, K, Ca, Mn, Fe, Cu, and Zn within WHO-recommended limits.

Sample Preparation for X-Ray Fluorescence Microscopy of Iron Distribution in Biological Specimen.

Characterizing the two- and three-dimensional distribution of trace metals in biological specimens is key to better understand their role in biological processes. Iron (Fe) is of particular interest in these trace metals due to its widespread role in maintaining cellular health and preventing disease. X-ray fluorescence microscopy (XFM) is emerging as the method of choice for investigators to interrogate the cellular and subcellular distribution of Fe. XFM utilizes the intrinsic X-ray fluorescence properties of each element to produce quantitative 2D and 3D distributions of trace metals within a sample. Herein, methods for sample preparation of cells and tissue for the determination of Fe distribution by XFM are described.

Elemental profiling of agricultural soil in Hoshiarpur utilizing analytical techniques.

Our study aimed to assess the soil quality in Punjab's Hoshiarpur district through a meticulous analysis of nutrient and elemental composition. Using a variety of analytical techniques, including Neutron Activation Analysis (NAA), external Particle-induced Gamma-ray Emission (PIGE) an Ion beam analysis Technique, and energy-dispersive X-ray fluorescence (ED-XRF), we delved into soil characterization for 22 agricultural soil samples in the Punjab region. Within the NAA framework, utilizing the Pneumatic Carrier Facility and the self-serve facility at Dhruva reactor in Mumbai, a brief 1-min irradiation procedure identified pivotal elements-Na, Mg, V, Al, Mn, and K. Conversely, an extended neutron irradiation process of approximately 4 h within the self-serve facility enabled the estimation of nearly 12 elements, including Rare Earth Elements (REEs), Transition elements, and other significant elements. The external PIGE technique quantified low Z elements (Na, Mg, Al, and Si), contributing to our analytical arsenal. Rigorously validating both NAA and PIGE methodologies, we compared results meticulously against established geological standard reference materials-specifically USGS RGM-1 and USGS AGV-1.Instrumental in elemental analysis, ED-XRF spectroscopy fortified our investigative endeavors by quick assessment of ten crucial elements. The elemental analysis revealed notable accumulations of Mn and Zn in the soil, surpassing the suggested permissible limits, whereas Co, Cr, and Pb were found to be within the recommended thresholds set by WHO/UNEP. Beyond elemental profiling, our study extended to estimate the accumulation levels of various elements utilizing ecological risk factors such as Contamination Factor, Potential Ecological Risk Index, Pollution Load Index, and Geoaccumulation Factor. Our findings highlighted significant accumulation of REEs including La, Sm and Yb.. This evaluation sheds new light on the interplay between soil composition and environmental health, emphasizing the need for advanced accessible agricultural technologies to prevent and forecast contaminant discharge in arable soil. This commitment aligns with our broader goal of advancing sustainable practices in soil management.

Investigation of an Optimal Sampling Resolution to Support Soil Management Decisions for Urban Plots.

The main objective of the current study was to use seven lots in Hartford, CT that are planned for community reuse to determine the optimal sampling density that allows for the detection of hotspots of lead pollution while limiting the labor of the sampling process. The sampling density was investigated using soil Pb measured by in situ X-ray Fluorescence as the indicator to evaluate soil health, with a new threshold of 200-mg/kg proposed by the USEPA in January of 2024. Even though this study takes place in an urban setting, where the new USEPA policy requires the use of a 100-mg/kg threshold for Pb due to the fact that there are other identifiable sources of the contaminant, only the 200-mg/kg threshold is discussed because it is evident from the analysis that compliance of a 100 mg/kg threshold in urban plots is highly unlikely (five out of seven sites would require complete site excavation prior to reuse). Using the inverse distance weighted geospatial interpolation of in situ pXRF determined lead measurements, grid sampling resolutions of 3-m, 4-m, 5-m, 6-m, 8-m, 10-m, and 12-m were compared. Ultimately, the case study finds that the largest grid resolution that can be implemented for soil screening to maintain hotspots of pollution to properly inform soil management decisions is a 6-m grid, or a density of approximately 1/36-m2.

Evaluating the portable X-ray fluorescence reliability for metal(loid)s detection and soil contamination status.

Marginalized communities experience barriers that can prevent soil monitoring efforts and knowledge transfer. To address this challenge, this study compared two analytical methods: portable X-ray fluorescence spectroscopy (pXRF, less time, cost) and inductively coupled plasma mass spectrometry (ICP-MS, "gold standard"). Surface soil samples were collected from residential sites in Arizona, USA (N = 124) and public areas in Troy, New York, USA (N = 33). Soil preparation differed between groups to account for community practice. Statistical calculations were conducted, paired t test, Bland-Altman plot, and a two-way ANOVA indicated no significant difference for As, Ba, Ca, Cu, Mn, Pb, and Zn concentrations except for Ba in the t test. Iron, Ni, Cr, and K were statistically different for Arizona soils and V, Ni, Fe, and Al concentrations were statistically different for New York soils. Zinc was the only element with high R2 and low p value. Pollution load index (PLI), enrichment factors (EF), and geo-accumulation index (Igeo) were calculated for both methods using U.S. Geological Survey data. The PLI were > 1, indicating soil pollution in the two states. Between pXRF and ICP-MS, the Igeo and EF in Arizona had similar degree of contamination for most elements except Zn in garden and Pb in yard, respectively. For New York, the Igeo of As, Cu, and Zn differed by only one classification index between the two methods. The pXRF was reliable in determining As, Ba, Ca, Cu, Mn, Pb, and Zn in impacted communities. Therefore, the pXRF can be a cost-effective alternative to using ICP-MS techniques to screen soil samples for several environmentally relevant contaminants to protect environmental public health.

The Combined ICP-MS, ESEM-EDX, and HAADF-STEM-EDX Approach for the Assessment of Metal Sub-Micro- and Nanoparticles in Wheat Grain.

Metal sub-microparticles (SMPs) and nanoparticles (NPs) presence in food is attributable to increasing pollution from the environment in raw materials and finished products. In the present study, a multifaceted analytical strategy based on Environmental Scanning Electron Microscopy and High-Angle Annular Dark-Field-Scanning Transmission Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDX, HAADF-STEM-EDX) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was proposed for the detection and characterization of metal and metal-containing SMPs and NPs in durum wheat samples, covering a size measurement range from 1 nm to multiple µm. ESEM-EDX and ICP-MS techniques were applied for the assessment of SMP and NP contamination on the surface of wheat grains collected from seven geographical areas characterized by different natural and anthropic conditions, namely Italy, the USA, Australia, Slovakia, Mexico, Austria, and Russia. ICP-MS showed significant differences among the mean concentration levels of metals, with the USA and Italy having the highest level. ESEM-EDX analysis confirmed ICP-MS concentration measurements and measured the highest presence of particles < 0.8 µm in size in samples from Italy, followed by the USA. Less marked differences were observed when particles < 0.15 µm were considered. HAADF-STEM-EDX was applied to a selected number of samples for a preliminary assessment of internal contamination by metal SMPs and NPs, and to expand the measurable particle size range. The multifaceted approach provided similar results for Fe-containing SMPs and NPs. ICP-MS and ESEM-EDX also highlighted the presence of a significant abundance of Ti- and Al-containing particles, while for STEM-EDX, sample preparation artifacts complicated the interpretation. Finally, HAADF-STEM-EDX results provided relevant information about particles in the low nm range, since, by applying this technique, no particles smaller than 50 nm were observed in accordance with ESEM-EDX.

Protocol for detecting micro(nano)plastics released from intravenous infusion products.

Approaches for detecting micro(nano)plastics (MNPs) released from intravenous infusion products (IVIPs) are vital for evaluating the safety of both IVIPs and their derived MNPs on human health, yet current understanding is limited. Here, we present a protocol for detecting polyvinyl chloride (PVC) MNPs by combining Raman spectroscopy, scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy (SEM-EDS), and pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS). We describe steps for collecting, pretreating, and measuring PVC MNPs released from IVIPs. For complete details on the use and execution of this protocol, please refer to Li et al.1.

Feasibility of using Vis-NIR spectroscopy and PXRF spectrometry to estimate regional soil cadmium concentration.

Conventionally, soil cadmium (Cd) measurements in the laboratory are expensive and time-consuming, involving complex processes of sample preparation and chemical analysis. This study aimed to identify the feasibility of using sensor data of visible near-infrared reflectance (Vis-NIR) spectroscopy and portable X-ray fluorescence spectrometry (PXRF) to estimate regional soil Cd concentration in a time- and cost-saving manner. The sensor data of Vis-NIR and PXRF, and Cd concentrations of 128 surface soils from Yunnan Province, China, were measured. Outer-product analysis (OPA) was used for synthesizing the sensor data and Granger-Ramanathan averaging (GRA) was applied to fuse the model results. Artificial neural network (ANN) models were built using Vis-NIR data, PXRF data, and OPA data, respectively. Results showed that: (1) ANN model based on PXRF data performed better than that based on Vis-NIR data for soil Cd estimation; (2) Fusion methods of both OPA and GRA had higher predictive power (R2) = 0.89, ratios of performance to interquartile range (RPIQ) = 4.14, and lower root mean squared error (RMSE) = 0.06, in ANN model based on OPA fusion; R2 = 0.88, RMSE = 0.06, and RPIQ = 3.53 in GRA model) than those based on either Vis-NIR data or PXRF data. In conclusion, there exists a great potential for the combination of OPA fusion and ANN to estimate soil Cd concentration rapidly and accurately.

In Situ Lung Dust Analysis by Automated Field Emission Scanning Electron Microscopy With Energy Dispersive X-ray Spectroscopy: A Method for Assessing Inorganic Particles in Lung Tissue From Coal Miners.

CONTEXT.­: Overexposure to respirable coal mine dust can cause severe lung disease including progressive massive fibrosis (PMF). Field emission scanning electron microscopy with energy dispersive x-ray spectroscopy (FESEM-EDS) has been used for in situ lung dust particle analysis for evaluation of disease etiology. Automating such work can reduce time, costs, and user bias. OBJECTIVE.­: To develop and test an automated FESEM-EDS method for in situ analysis of inorganic particles in coal miner lung tissue. DESIGN.­: We programmed an automated FESEM-EDS procedure to collect particle size and elemental data, using lung tissue from 10 underground coal miners with PMF and 4 control cases. A statistical clustering approach was used to establish classification criteria based on particle chemistry. Data were correlated to PMF/non-PMF areas of the tissue, using corresponding brightfield microscopy images. Results for each miner case were compared with a separate corresponding analysis of particles recovered following tissue digestion. RESULTS.­: In situ analysis of miner tissues showed higher particle number densities than controls and densities were generally higher in PMF than non-PMF areas. Particle counts were typically dominated by aluminum silicates with varying percentages of silica. Compared to digestion results for the miner tissues, in situ results indicated lower density of particles (number per tissue volume), larger size, and a lower ratio of silica to total silicates-probably due to frequent particle clustering in situ. CONCLUSIONS.­: Automated FESEM-EDS analysis of lung dust is feasible in situ and could be applied to a larger set of mineral dust-exposed lung tissues to investigate specific histologic features of PMF and other dust-related occupational diseases.

Gamma-rays and X-rays spectrometries applied to evaluate soil redistribution.

This work responds to the growing global demand for food, which requires improvements in agricultural production and sustainable management of natural resources. The focus is on soil erosion as a critical element in preserving agricultural productivity. From this perspective, the levels of radionuclides and chemical elements present in the soil, quantified through Gamma-Rays Spectrometry (GRS) and Energy Dispersive X-ray Fluorescence (EDXRF), were used to investigate soil redistribution over time. 27 soil samples ranging from 0 to 30 cm in depth were collected in an agricultural plot located in southern Brazil. Quantitative analysis indicated high mean concentrations of Fe (161 ± 7 gkg-1), Al (110 ± 17 gkg-1), Ca (2.6 ± 0.5 gkg-1), Mn (2.4 ± 0.3 gkg-1) and K (543 ± 165 mgkg-1) in comparison with the other detected elements. The quantification of 137Cs provided a mean inventory of 27 ± 17 Bqm-2. Using the proportional model, an estimated gross erosion rate of 28.2 tonha-1year-1 and a net soil deposition of 6.6 tonha-1year-1 were calculated. Therefore, a net soil loss of 21.6 tonha-1year-1 was experienced within the agricultural plot studied. The data set combination of both techniques with Principal Component Analysis (PCA) revealed correlations between the variables studied and the soil erosion dynamics. The PCA showed a tendency to separate the samples according to their sampling depth. Moreover, 137Cs behavior in soil proved to be similar to the behavior of elements found in fertilizers, like K. On the other hand, the individual influence of 137Cs was not enough to cause significant changes in the samples distribution in the scores plot, highlighting EDXRF as a promising technique to complement soil erosion studies.

Investigating Microbial Biosignatures in Aeolian Environments Using Micro-X-Ray: Simulation of PIXL Instrument Analyses at Jezero Crater Onboard the Perseverance Mars 2020 Rover.

Assessing the past habitability of Mars and searching for evidence of ancient life at Jezero crater via the Perseverance rover are the key objectives of NASA's Mars 2020 mission. Onboard the rover, PIXL (Planetary Instrument for X-ray Lithochemistry) is one of the best suited instruments to search for microbial biosignatures due to its ability to characterize chemical composition of fine scale textures in geological targets using a nondestructive technique. PIXL is also the first micro-X-ray fluorescence (XRF) spectrometer onboard a Mars rover. Here, we present guidelines for identifying and investigating a microbial biosignature in an aeolian environment using PIXL-analogous micro-XRF (µXRF) analyses. We collected samples from a modern wet aeolian environment at Padre Island, Texas, that contain buried microbial mats, and we analyzed them using µXRF techniques analogous to how PIXL is being operated on Mars. We show via µXRF technique and microscope images the geochemical and textural variations from the surface to ∼40 cm depth. Microbial mats are associated with heavy-mineral lags and show specific textural and geochemical characteristics that make them a distinct biosignature for this environment. Upon burial, they acquire a diffuse texture due to the expansion and contraction of gas-filled voids, and they present a geochemical signature rich in iron and titanium, which is due to the trapping of heavy minerals. We show that these intrinsic characteristics can be detected via µXRF analyses, and that they are distinct from buried abiotic facies such as cross-stratification and adhesion ripple laminations. We also designed and conducted an interactive survey using the Padre Island µXRF data to explore how different users chose to investigate a biosignature-bearing dataset via PIXL-like sampling strategies. We show that investigating biosignatures via PIXL-like analyses is heavily influenced by technical constraints (e.g., the XRF measurement characteristics) and by the variety of approaches chosen by different scientists. Lessons learned for accurately identifying and characterizing this biosignature in the context of rover-mission constraints include defining relative priorities among measurements, favoring a multidisciplinary approach to the decision-making process of XRF measurements selection, and considering abiotic results to support or discard a biosignature interpretation. Our results provide guidelines for PIXL analyses of potential biosignature on Mars.

A High-Sensitivity Benchtop X-Ray Fluorescence Emission Tomography (XFET) System With a Full-Ring of X-Ray Imaging-Spectrometers and a Compound-Eye Collimation Aperture.

The advent of metal-based drugs and metal nanoparticles as therapeutic agents in anti-tumor treatment has motivated the advancement of X-ray fluorescence computed tomography (XFCT) techniques. An XFCT imaging modality can detect, quantify, and image the biodistribution of metal elements using the X-ray fluorescence signal emitted upon X-ray irradiation. However, the majority of XFCT imaging systems and instrumentation developed so far rely on a single or a small number of detectors. This work introduces the first full-ring benchtop X-ray fluorescence emission tomography (XFET) system equipped with 24 solid-state detectors arranged in a hexagonal geometry and a 96-pinhole compound-eye collimator. We experimentally demonstrate the system's sensitivity and its capability of multi-element detection and quantification by performing imaging studies on an animal-sized phantom. In our preliminary studies, the phantom was irradiated with a pencil beam of X-rays produced using a low-powered polychromatic X-ray source (90kVp and 60W max power). This investigation shows a significant enhancement in the detection limit of gadolinium to as low as 0.1 mg/mL concentration. The results also illustrate the unique capabilities of the XFET system to simultaneously determine the spatial distribution and accurately quantify the concentrations of multiple metal elements.

High-Spatial-Resolution Benchtop X-ray Fluorescence Imaging through Bragg-Diffraction-Based Focusing with Bent Mosaic Graphite Crystals: A Simulation Study.

X-ray fluorescence imaging (XFI) can localize diagnostic or theranostic entities utilizing nanoparticle (NP)-based probes at high resolution in vivo, in vitro, and ex vivo. However, small-animal benchtop XFI systems demonstrating high spatial resolution (variable from sub-millimeter to millimeter range) in vivo are still limited to lighter elements (i.e., atomic number Z≤45). This study investigates the feasibility of focusing hard X-rays from solid-target tubes using ellipsoidal lens systems composed of mosaic graphite crystals with the aim of enabling high-resolution in vivo XFI applications with mid-Z (42≤Z≤64) elements. Monte Carlo simulations are performed to characterize the proposed focusing-optics concept and provide quantitative predictions of the XFI sensitivity, in silico tumor-bearing mice models loaded with palladium (Pd) and barium (Ba) NPs. Based on simulation results, the minimum detectable total mass of PdNPs per scan position is expected to be on the order of a few hundred nanograms under in vivo conform conditions. PdNP masses as low as 150 ng to 50 ng could be detectable with a resolution of 600 µm when imaging abdominal tumor lesions across a range of low-dose (0.8 µGy) to high-dose (8 µGy) exposure scenarios. The proposed focusing-optics concept presents a potential step toward realizing XFI with conventional X-ray tubes for high-resolution applications involving interesting NP formulations.