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At least 955 records · Page 53

Sample size estimation for case‐crossover studies

Case‐crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case‐crossover study is self‐controlled, its advantages include better control for confounding because the design controls for any time‐invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self‐matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case‐crossover study, investigators currently use Dupont's formula ( Biometrics 1988; 43 :1157‐1168), which was originally developed for a matched case‐control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self‐controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case‐crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.

Dharmarajan, Sai↗

Robust surfactant-assisted one-pot sample preparation for label-free single-cell and nanoscale proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.

Single-cell proteomics, nanoscale proteomics, SOP-↗

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rapid Determination Of Radiostrontium In Large Soil Samples

A new method for the determination of radiostrontium in large soil samples has been developed at the Savannah River Environmental Laboratory (Aiken, SC, USA) that allows rapid preconcentration and separation of strontium in large soil samples for the measurement of strontium isotopes by gas flow proportional counting. The need for rapid analyses in the event of a Radiological Dispersive Device (RDD) or Improvised Nuclear Device (IND) event is well-known. In addition, the recent accident at Fukushima Nuclear Power Plant in March, 2011 reinforces the need to have rapid analyses for radionuclides in environmental samples in the event of a nuclear accident. The method employs a novel pre-concentration step that utilizes an iron hydroxide precipitation (enhanced with calcium phosphate) followed by a final calcium fluoride precipitation to remove silicates and other matrix components. The pre-concentration steps, in combination with a rapid Sr Resin separation using vacuum box technology, allow very large soil samples to be analyzed for {sup 89,90}Sr using gas flow proportional counting with a lower method detection limit. The calcium fluoride precipitation eliminates column flow problems typically associated with large amounts of silicates in large soil samples.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Rapid fusion method for the determination of Pu, Np, and Am in large soil samples

A new rapid sodium hydroxide fusion method for the preparation of 10-20 g soil samples has been developed by the Savannah River National Laboratory (SRNL). The method enables lower detection limits for plutonium, neptunium, and americium in environmental soil samples. The method also significantly reduces sample processing time and acid fume generation compared to traditional soil digestion techniques using hydrofluoric acid. Ten gram soil aliquots can be ashed and fused using the new method in 1-2 hours, completely dissolving samples, including refractory particles. Pu, Np and Am are separated using stacked 2mL cartridges of TEVA and DGA Resin and measured using alpha spectrometry. The method can be adapted for measurement by inductively-coupled plasma mass spectrometry (ICP-MS). Two 10 g soil aliquots of fused soil may be combined prior to chromatographic separations to further improve detection limits. Total sample preparation time, including chromatographic separations and alpha spectrometry source preparation, is less than 8 hours.

54 ENVIRONMENTAL SCIENCES↗

Rapid method to determine actinides and 89/90 Sr in limestone and marble samples

A new method for the determination of actinides and radiostrontium in limestone and marble samples has been developed that utilizes a rapid sodium hydroxide fusion to digest the sample. Following rapid pre-concentration steps to remove sample matrix interferences, the actinides and 89/90 Sr are separated using extraction chromatographic resins and measured radiometrically. The advantages of sodium hydroxide fusion versus other fusion techniques will be discussed. Lastly, this approach has a sample preparation time for limestone and marble samples of <4 hours.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

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↗