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Theoretical realization of three-dimensional nanolattice structure fabrication based on high-order waveguide-mode interference and sample rotation

A theoretical method of using high-order waveguide-mode interference combined with sample rotation is proposed to fabricate different kinds of three-dimensional nanolattice structures. The lithography sample is assisted by an asymmetric metal-cladding dielectric waveguide structure. High-order waveguide modes can be excited in the photoresist layer by both transverse magnetic and transverse electric polarized light. By utilizing multiple exposures of high-order waveguide-mode interference combined with sample-rotation, various three-dimensional nanolattice structures can be obtained. The resulting optical field distributions are simulated using the finite element method in this study, and sample rotation is expressed by coordinate matrix transformation. As examples, the three-dimensional optical field distributions resulting from fifth-order waveguide-mode interference were simulated with 90° and 60° sample rotations and multiple exposures. The results show that a quasi-cuboid structure with a simple tetragonal arrangement and a quasi-hexagonal structure with a hexagonal close-packed lattice can be obtained. Moreover, the numerical simulation results revealed that the shapes, sizes, arrangements, and periods of the structures can be controlled by the rotation method, photoresist thickness, waveguide modes used for exposure, and so on.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗

Colloidal gold nanoparticle probe-based immunochromatographic assay for the rapid detection of chromium ions in water and serum samples

An immunochromatographic assay (ICA) using gold nanoparticles coated with monoclonal antibody (McAb) for the detection of chromium ions (Cr) in water and serum samples was developed, optimized, and validated. Gold nanoparticles coated with affinity- purified monoclonal antibodies against isothiocyanobenzyl-EDTA (iEDTA)-chelated Cr3+ were used as the detecting reagent in this completive immunoassay-based one- step test strip. The ICA was investigated to measure chromium speciation in water samples. Chromium standard samples of 0-80 ng/mL in water were determined by the test strips. The results showed that the visual lowest detection limit (LDL) of the test strip was 50.0 ng/mL. A portable colorimetric lateral flow reader was used for the quantification of Cr. The results indicated that the linear range of the ICA with colorimetric detection was 5-80 ng/mL. The ICA was also validated for the detection of chromium ions in serum samples. The test trips showed high stability in that they could be stored at at 37 C for at least 12 weeks without significant loss of activity. The test strip also showed good selectivity for Cr detection with negligible interference from other heavy metals. Because of its low cost and short testing time (within 5 min), the test strip is especially suitable for on-site large- scale screening of Cr-polluted water samples, biomonitoring of Cr exposure, and many other field applications.

74 ATOMIC AND MOLECULAR PHYSICS↗

Effects of mechanical stress and vitreous samples in retinal pigment epithelial cells

In rhegmatogenous retinal detachment (RRD), scattered RPE cells from the basement membrane into the vitreous cavity undergo an epithelial mesenchymal transition (EMT) and form the intraocular fibrous membrane in response to vitreous fluid. We investigated whether exposure to vitreous samples was associated with EMT-associated signals and mesenchymal characters. Human vitreous samples were collected from patients with RRD, epiretinal membrane (ERM), or macular hole (MH). We evaluated the effects of vitreous on ARPE-19 cells in suspension cultures using poly 2-hydroxyethyl methacrylate-coated dishes and three-dimensional (3D) Matrigel cultures. We found that exposure to vitreous samples did not induce morphological changes or accelerate wound closure in monolayers. Several samples showed increased phosphorylation of Smad2 and nuclear translocation of nuclear factor-κB. Mechanical stress triggered an elevation of phosphorylation levels in Smad2. In addition, exposure to vitreous fluid increased the phosphorylation of p38 mitogen-activated protein kinase in cell suspension cultures after mechanical stress. Moreover, ARPE-19 cells showed a stellate invasive phenotype in 3D Matrigel cultures with vitreous samples. In this study, we demonstrated that mechanical stress and vitreous were associated with EMT-associated signals and invasive phenotypes in 3D cultures but not in monolayers. These results have important implications for the role of vitreous humor in the induction of EMT and intraocular fibrosis.

60 APPLIED LIFE SCIENCES↗

Effective detection of CO 2 leakage: a comparison of groundwater sampling and pressure monitoring

Shallow aquifer monitoring is likely to be a required aspect to any geologic CO 2 sequestration operation. Collecting groundwater samples and analyzing for geochemical parameters such as pH, alkalinity, total dissolved carbon, and trace metals has been suggested by a number of authors as a possible strategy to detect CO 2 leakage. The effectiveness of this approach, however, will depend on the hydrodynamics of the leak-induced CO 2 plume and the spatial distribution of the monitoring wells relative to the origin of the leak. To our knowledge, the expected effectiveness of groundwater sampling to detect CO 2 leakage has not yet been quantitatively assessed. In this study we query hundreds of simulations developed for the National Risk Assessment Project (US DOE) to estimate risks to drinking water resources associated with CO 2 leaks. The ensemble of simulations represent transient, 3-D multi-phase reactive transport of CO 2 and brine leaked from a sequestration reservoir, via a leaky wellbore, into an unconfined aquifer. Key characteristics of the aquifer, including thickness, mean permeability, background hydraulic gradient, and geostatistical measures of aquifer heterogeneity, were all considered uncertain parameters. Complex temporally-varying CO 2 and brine leak rate scenarios were simulated using a heuristic scheme with ten uncertain parameters. The simulations collectively predict the spatial and temporal evolution of CO 2 and brine plumes over 200 years in a shallow aquifer under a wide range of leakage scenarios and aquifer characteristics. Using spatial data from an existing network of shallow drinking water wells in the Edwards Aquifer, TX, as one illustrative example, we calculated the likelihood of leakage detection by groundwater sampling. In this monitoring example, there are 128 wells available for sampling, with a density of about 2.6 wells per square kilometer. If the location of the leak is unknown a priori, a reasonable assumption in many cases, we found that the leak would be detected in at least one of the monitoring wells in less than 10% of the scenarios considered. This is because plume sizes are relatively small, and so the probability of detection decreases rapidly with distance from the leakage point. For example, 400m away from the leakage point there is less than 20% chance of detection. We then compared the effectiveness of groundwater quality sampling to shallow aquifer and/or reservoir pressure monitoring. For the Edwards Aquifer example, pressure monitoring in the same monitoring well network was found to be even less effective that groundwater quality monitoring. This is presumably due to the unconfined conditions and relatively high permeability, so pressure perturbations quickly dissipate. Although specific results may differ from site to site, this type of analysis should be useful to site operators and regulators when selecting leak detection strategies. Given the spatial characteristics of a proposed monitoring well network, probabilities of leakage detection can be rapidly calculated using this methodology. Although conditions such as these may not be favorable for leakage detection in shallow aquifers, leakage detection could be much more successful in the injection reservoir. We demonstrate proof-of-concept for this hypothesis, presenting a simulation where there is measurable pressure change at the injection well due to overpressurization, fault rupture, and consequent leakage up the fault into intermediate and shallow aquifers. The size of the detectible pressure change footprint is much larger in the reservoir than in either of the overlying aquifers. Further exploration of the range of conditions for which this technique would be successful is the topic of current study.

54 ENVIRONMENTAL SCIENCES↗

135 Cs/ 137 Cs isotopic composition of environmental samples across Europe: Environmental transport and source term emission applications

135 Cs/ 137 Cs isotopic analyses represent an important tool for studying the fate and transport of radiocesium in the environment; in this work the 135 Cs/ 137 Cs isotopic composition in environmental samples taken from across Europe is reported. Surface soil and vegetation samples from western Russia, Ukraine, Austria, and Hungary show consistent aged thermal fission product 135 Cs/ 137 Cs isotope ratios of 0.58 ± 0.01 (age corrected to 1/1/15), with the exception of one sample of soil-moss from Hungary which shows an elevated 135 Cs/ 137 Cs ratio of 1.78 ± 0.12. With the exception of the outlier sample from Hungary, surface soil/vegetation data are in quantitative agreement with values previously reported for soils within the Chernobyl exclusion zone, suggesting that radiocesium at these locations is primarily composed of homogenous airborne deposition from Chernobyl. Seawater samples taken from the Irish Sea show 135 Cs/ 137 Cs isotope ratios of 1.22 ± 0.11 (age corrected to 1/1/15), suggesting aged thermal fission product Cs discharged from Sellafield. Furthermore, the differences in 135 Cs/ 137 Cs isotope ratios between Sellafield, Chernobyl, and global nuclear weapons testing fallout indicate that 135 Cs/ 137 Cs isotope ratios can be utilized to discriminate between and track radiocesium transport from different nuclear production source terms, including major emission sources in Europe.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sampling two-dimensional isometric tensor network states

Sampling a quantum system’s underlying probability distributions is an important computational task, e.g., for quantum advantage experiments and quantum Monte Carlo algorithms. Tensor networks are an invaluable tool for efficiently representing states of large quantum systems with limited entanglement. Algorithms for sampling one-dimensional (1D) tensor networks are well-established and utilized in several 1D tensor network methods. In this paper we introduce two novel sampling algorithms for two-dimensional (2D) isometric tensor network states (isoTNS) that generalize existing 1D tensor network sampling algorithms. Our first proposed algorithm performs independent sampling and yields a single configuration together with its associated probability. The second algorithm employs a greedy search strategy to identify high-probability configurations and their corresponding probabilities. Numerical results demonstrate the effectiveness of these algorithms across quantum states with varying entanglement and system size.

Dumitrescu, Eugene [ORNL] (ORCID:0000000158519567)↗

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗

Determination of the effective sample thickness via radiative capture

Our procedure for determining the effective thickness of non-uniform irregular-shaped samples via radiative capture is described. In this technique, partial γ-ray production cross sections of a compound nucleus produced in a neutron-capture reaction are measured using Prompt Gamma Activation Analysis and compared to their corresponding standardized absolute values. For the low-energy transitions, the measured cross sections are lower than their standard values due to significant photoelectric absorption of the γ rays within the bulk-sample volume itself. Using standard theoretical techniques, the amount of γ-ray self absorption and neutron self shielding can then be calculated by iteratively varying the sample thickness until the observed cross sections converge with the known standards. The overall attenuation provides a measure of the effective sample thickness illuminated by the neutron beam. This procedure is illustrated through radiative neutron capture using powdered oxide samples comprising enriched 186 W and 182 W from which their tungsten-equivalent effective thicknesses are deduced to be 0.077(3) mm and 0.042(8) mm, respectively.

(n, γ) radiative capture↗

Proof-of-concept chemometric approach for environmental forensic sourcing of crude oil samples using SPME-GC-MS

Environmental exposure to crude oil through seepage and spillage poses risks to the immediate environment and the broader ecosystem as areas along the oil distribution path are affected by the influx of crude petroleum as well as the environmental, economic, and civil unrest that accompanies it. There is a large financial burden associated with the lost resources, including the cost of rehabilitation, and the affected sources of revenue for communities affected by oil spills. As such, it is crucial to determine the responsible parties. This work outlines an environmental forensics approach to determining the source of an un-weathered crude oil sample. The researchers employed solid phase microextraction coupled with gas chromatography mass spectrometry (SPME-GC-MS) to capture and analyze the gaseous components emitted by crude oil samples sourced from five locations. Samples were analyzed using Spearman's rank correlation and 3D covariance analysis. Both chemometric approaches yielded optimal performance results with no misclassifications, true positive rate (TPR) = 100 % and false positive rate (FPR) = 0 %. The similarity metrics calculated by each test noted clear delineations between the values of same-source and differently sourced samples. The Spearman's rank correlation test and 3D covariance calculations both demonstrated the ability to correctly identify sample source origin in this dataset. Finally, the authors outline an approach to the future application of these tests and suggest their joint use in future crude oil sourcing endeavors.

3D covariance mapping↗

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography–Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method

Here, in this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

09 BIOMASS FUELS↗

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data. By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.

47 OTHER INSTRUMENTATION↗

Single-Particle Isotopic Analysis Using the Liquid Sampling-Atmospheric Pressure Glow Discharge Microplasma Coupled to an Orbitrap Mass Spectrometer

Isotope ratio (IR) determinations on individual particles can provide valuable information relative to the sample, including processing and dating, which could be valuable to geological and nuclear material analysis communities. In comparison to “bulk” measurements, in which all particle information is lost and homogenized within a sample, “particle” measurements allow for fingerprinting and can provide unique insights related to the sample’s nano- and micro- compositions. Furthermore, the complex nature of particles, with potential isobaric interferences from either the matrix or other elements within the same particle, poses a significant analytical challenge for conventional mass spectrometry platforms employed for elemental analysis due to their limited mass resolution. Presented here is the first demonstration of an ultrahigh resolution method for single particle (SP) isotopic analysis using the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an Orbitrap mass spectrometer and FTMS Booster X2T acquisition/processing system. For proof of concept, well-characterized CeO 2 microparticles with a nominal diameter of 1.0 μm were analyzed at a mass resolution of ∼330,000. Important instrumental parameters were optimized to enable the detection of single particles. The 142 Ce/ 140 Ce ratio of individual particles and the population average were determined and compared to an SP inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) analysis. The isotopic accuracy and precision were determined by two methods and found to be in good agreement with the SP-ICP-TOF-MS method, with the linear regression slope method providing a more accurate ratio, showing a ∼1.4% relative difference from the ratio determined from a particle digest. The encouraging performance of the method was further supported by a determined detection limit of 2.9 fg ( 142 Ce). The developed method is anticipated to overcome many of the challenges posed by isobaric interferences encountered in conventional mass spectrometry techniques when analyzing real-world samples for particle isotopic composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ambient Metabolic Profiling and Imaging of Biological Samples with Ultrahigh Molecular Resolution using Laser Ablation Electrospray Ionization 21 Tesla FTICR Mass Spectrometry

Mass spectrometry (MS) has been an indispensable analytical tool in capturing the complexity and array of biomolecules within biological systems. However, conventional MS-based analytical workflows are limited in both throughput and measuring the native molecular state these systems, due in large part to sample handling and preparation. The development of ambient ionization methods capable of sampling directly from tissues circumvent many of these issues but requires the use of high-performance MS to resolve the molecular complexity within these samples. Herein, we demonstrate the unique combination of laser ablation electrospray ionization (LAESI) coupled with a 21 Tesla Fourier transform ion cyclotron resonance (21T-FTICR-MS) for MS imaging applications. This analytical platform provides isotopic fine structure information directly from native tissues, delivering a higher degree of confidence for molecular identification. The ability to capture and visualize the complex metabolic behavior of living organisms in situ is a bioanalytical grand challenge that has yet to be fully realized. Due to their excellent sensitivity and selectivity, mass spectrometry (MS)-based platforms offer a unique opportunity to characterize an array of biomolecules from a variety of biological samples.[1] One method in particular, MS imaging (MSI), has demonstrated the ability to simultaneously determine the spatial distributions for hundreds of biomolecules, e. g., metabolites, lipids, peptides, and xenobiotics, within complex biological systems simultaneously.[2-3] Matrix-assisted laser desorption/ionization (MALDI)-MSI remains the most common of these methods.[4] However, the application of an exogenous matrix, and the limited availability of commercial sources that operate under atmospheric pressure,[5] has significantly prohibited the ability of MALDI to be useful for biomolecular mapping of living systems. Ambient ionization methods that require minimal to no sample preparation, like desorption electrospray ionization (DESI and nano-DESI) and laser ablation electrospray ionization (LAESI), demonstrated the ability to spatially map biomolecule distributions within live organisms.

Mass Spectometry, fourier transform ion cyclostron↗

Sample Preparation Methods for Targeted Single-Cell Proteomics

We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540–660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390–540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5–25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.

59 BASIC BIOLOGICAL SCIENCES↗

Sparge Sampling of Molten Salts for Online Monitoring via Laser-Induced Breakdown Spectroscopy

A method was developed to sample molten salts by sparging to generate and transport aerosols to an isolated instrument for compositional analysis by laser-induced breakdown spectroscopy (LIBS). Real-time monitoring of molten salt composition is critical to developing molten salt nuclear reactors, which offer enhanced safety and efficiency. In this article, the sparge sampling method is described and compared with sampling using a Collison nebulizer. The size distribution and transport of aerosols produced from molten eutectic NaNO 3 –KNO 3 salt were compared for multiple gas flow rates (75–1200 mL min –1 ) and transport distances (0.68–2.61 m). Both methods produced aerosols ranging from 0.5 to 5.0 μm determined using a cascade impactor. Aerosols were effectively transported without pre- or trace-heating of gas lines, but transport efficiency was reduced by the formation of agglomerates. Sparge sampling was found to use less sample and less gas than a Collison nebulizer while producing a more concentrated aerosol stream (up to 5 μg L –1 ). The effects of laser energy and delay time on the signal quality of LIBS measurements of these aerosols were also studied. High energy and short delay times were found to enhance signal and repeatability, whereas signal-to-background and signal-to-noise ratios were highest at low energy and longer delay times. The capabilities of this system for online monitoring of molten salts were demonstrated with calibrations for Sr and Li with relative standard deviations of 2.6% and 1.5% and limits of detection of 380 and 180 μg g –1 , respectively.

Aerosols↗

Microbial Diversity in Bushmeat Samples Recovered from the Serengeti Ecosystem in Tanzania

Bushmeat, the meat and organs derived from wildlife species, is a common source of animal protein in the diets of those living in sub-Saharan Africa and is frequently associated with zoonotic spillover of dangerous pathogens. Given the frequent consumption of bushmeat in this region and the lack of knowledge about the microbial communities associated with this meat, the microbiome of 56 fresh and processed bushmeat samples ascertained from three districts in the Western Serengeti ecosystem in Tanzania was characterized using 16S rRNA metagenomic sequencing. Here, the results show that the most abundant phyla present in bushmeat samples include Firmicutes (67.8%), Proteobacteria (18.4%), Cyanobacteria (8.9%), and Bacteroidetes (3.1%). Regardless of wildlife species, sample condition, season, or region, the microbiome is diverse across all samples, with no significant difference in alpha or beta diversity. The findings also suggest the presence of DNA signatures of potentially dangerous zoonotic pathogens, including those from the genus Bacillus, Brucella, Coxiella, and others, in bushmeat. Together, this investigation provides a better understanding of the microbiome associated with this major food source in samples collected from the Western Serengeti in Tanzania and highlights a need for future investigations on the potential health risks associated with the harvesting, trade, and consumption of bushmeat in Sub-Saharan Africa.

59 BASIC BIOLOGICAL SCIENCES↗