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At least 1,045 records · Page 58

Fine-scale evaluation of two standard 16S rRNA gene amplicon primer pairs for analysis of total prokaryotes and archaeal nitrifiers in differently managed soils

The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.

16S rRNA gene amplicon Illumina sequencing↗

Consensus Weighting of a Multi-Agent System for Load Shedding

An agent-based scheme is proposed for distributed underfrequency load shedding (UFLS). The key concept is a consensus weighting protocol (CWP) for agents to reach an agreement. Unlike the well adopted average-consensus protocol (ACP), the proposed CWP enables each agent to converge to its weighted portion of the sum of all initial values. Thus, the proposed CWP is more suitable for the UFLS application, as it allows load buses with a higher level of loading to shed more, rather than reducing by the same average value over all load buses as required by the ACP. Proof of convergence for the proposed CWP is derived and presented in this paper, together with the constraints. For implementation of the multi-agent system (MAS), the monitoring, estimation, and distribution steps are developed. Two study cases and the simulation results are provided to validate the performance of the proposed agent-based UFLS scheme.

Xie, Jing↗

Rapid kVp switching dual-energy CT in the assessment of urolithiasis in patients with large body habitus: preliminary observations on image quality and stone characterization

Purpose: The purpose of this study was to investigate the image quality (IQ) considerations of rapid kVp switching dual-energy CT (rsDECT) in the assessment of urolithiasis in patients with large body habitus and to evaluate whether it allows stone characterization. Materials and methods: In this IRB-approved, HIPAA compliant retrospective study, 93 consecutive patients (M/F = 72/21, mean age 56.9 years, range 23–83 years) with large body habitus (> 90 kg/198 lbs) who underwent dual-energy (DE) stone protocol CT on a rapid kVp switching DECT scanner between January 2013 and December 2016 were included. Scan acquisition protocol included an initial unenhanced single-energy CT (SECT) scan of KUB followed by targeted DECT in the region of stones. Two readers evaluated both CT data sets (axial 5 mm 120 kVp/140 kVp QC/70 keV monoenergetic, material density water/iodine images and coronal/sagittal 3 mm images) for the assessment of image quality (Scores: 1–4) and characterization of stone composition (reference standard: crystallography). Results: One hundred and five CT examinations were performed in 93 patients (mean body weight 105.12 ± 13.53 kg, range 91–154 kg), and a total of 321 urinary tract calculi (mean size-4.8 ± 3.2 mm, range 1.2–22 mm) were detected. Both SECT and targeted monoenergetic images were of acceptable image quality (mean IQ: 3.77 and 3.83, kappa 0.79 and 0.87 respectively). Material density water and iodine images had lower IQ scores (mean IQ: 2.97 and 3.09 respectively) with image quality deterioration due to severe photon starvation/streak artifacts in 20% (21/105) and 17% (18/105) scans, respectively. Characterization of stone composition into uric acid/non-uric acid stones was achieved in 93.14% (299/321) of calculi (mean size: 4.99 ± 3.3 mm, range 1.2–22 mm), while 7% (22/321) stones could not be characterized (mean size 3.03 ± 1.16 mm, range 1.6–6.4 mm) (p < 0.001). Most common reason for non-characterization was image quality deterioration of the material density iodine images due to severe photon starvation artifacts. On multivariate regression, stone size and patient weight were predictors of stone composition determination on DECT (p < 0.05). The transverse diameter had a weak negative correlation with stone composition determination, but it was not statistically significant. Stone characterization into uric acid vs. non-uric acid stones was accurate in 95% (n = 38/40) of stones in comparison with crystallography. Conclusion: In patients with large body habitus, rsDECT allowed characterization of most calculi (93%) despite image quality deterioration due to photon starvation/streak artifacts in up to 20% of material density images. Stone size and patient weight were predictors of stone composition determination on DECT, and small calculi in very large patients may not be characterized.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Aggregate attack surface management for network discovery of operational technology

Interconnectivity has become a substratum of technology as the benefits of data-driven functionality are being realized in nearly all industries. Increased connectivity of Operational Technology (OT) exacerbates cyber risks because Industrial Control Systems (ICS) are becoming exposed to the Internet. These exposures are often done inadvertently through misconfigurations as additional network devices come online. Attack surface management (ASM) platforms can be used to identify vulnerabilities by performing external network discovery over the Internet using web spiders. These web spiders enable big data analytics of Internet of Things (IoT) devices as identifiable information of Internet-exposed equipment are archived in searchable databases that are made publicly available. There are a multitude of ASM service providers on the market. Here, this study was conducted to evaluate several commonly known tools to determine the aggregate attack surface of control systems. Queries were crafted by targeting commonly known manufacturers and communication protocols found in OT networks. Identified devices were that categorized based on technology types. Each query was replicated between several tools to target identical ICS equipment. Findings in this paper suggested a significant variance in the exposures discovered by each tool, but unique contributions were identified for each tool when a merged attack surface was derived. Therefore, all tools should be used in aggregate.

97 MATHEMATICS AND COMPUTING↗

Differences Between Colon Cancer Primaries and Metastases Using a Molecular Assay for Tumor Radiation Sensitivity Suggest Implications for Potential Oligometastatic SBRT Patient Selection

Purpose: We previously developed a multigene expression model of tumor radiation sensitivity index (RSI) with clinical validation in multiple independent cohorts (breast, rectal, esophageal, and head and neck patients). The purpose of this study was to assess differences between RSI scores in primary colon cancer and metastases. Methods and Materials: Patients were identified from our institutional review board–approved prospective observational protocol. A total of 704 metastatic and 1362 primary lesions were obtained from a de-identified metadata pool. RSI was calculated using the previously published rank-based algorithm. An independent cohort of 29 lung or liver colon metastases treated with 60 Gy in 5 fractions stereotactic body radiation therapy (SBRT) was used for validation. Results: The most common sites of metastases included liver (n=374; 53%), lung (n=116; 17%), and lymph nodes (n=40; 6%). Sixty percent of metastatic tumors, compared with 54% of primaries, were in the RSI radiation-resistant peak, suggesting metastatic tumors may be slightly more radiation resistant than primaries (P=.01). In contrast, when we analyzed metastases based on anatomical site, we uncovered large differences in RSI. The median RSIs for metastases in descending order of radiation resistance were ovary (0.48), abdomen (0.47), liver (0.43), brain (0.42), lung (0.32), and lymph nodes (0.31) (P<.0001). These findings were confirmed when the analysis was restricted to lesions from the same patient (n=139). In our independent cohort of treated lung and liver metastases, lung metastases had an improved local control rate compared to that in patients with liver metastases (2-year local control rate of 100% vs 73.0%, respectively; P=.026). Conclusions: Assessment of radiation sensitivity between primary and metastatic tissues of colon cancer histology revealed significant differences based on anatomical location of metastases. These initial results warrant validation in a larger clinical cohort.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Coarse-Grained Molecular Simulation of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides

Self-assembled aggregates of peptides containing aromatic groups possess optoelectronic properties that make them attractive targets for the fabrication of biocompatible electronics. Molecular-level understanding of how the microscopic peptide chemistry influences the properties of the aggregates is vital for rational peptide design. We construct a coarse-grained model of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp (DFAG-OPV3-GAFD) peptides containing OPV3 (distyrylbenzene) π-conjugated cores explicitly parameterized against all-atom calculations and perform molecular dynamics simulations of the self-assembly of hundreds of molecules over hundreds of nanoseconds. We observe a hierarchical assembly mechanism wherein ~2-8 peptides assemble into stacks with aligned aromatic cores that subsequently form elliptical aggregates and ultimately a branched network with a fractal dimensionality of ~1.5. The assembly dynamics are well described by a Smoluchowski coagulation process for which we extract rate constants from the molecular simulations to both furnish insight into the microscopic assembly kinetics and extrapolate our aggregation predictions to time and length scales beyond the reach of molecular simulation. Lastly, this study presents new molecular-level understanding of the morphology and dynamics of the spontaneous self-assembly of DFAG-OPV3-GAFD peptides and establishes a systematic protocol to develop coarse-grained models of optoelectronic peptides for the exploration and design of π-conjugated peptides with tunable optoelectronic properties.

36 MATERIALS SCIENCE↗

Longitudinal dataset of human-building interactions in U.S. offices

Adaptive interactions between building occupants and their surrounding environments affect both energy use and environmental quality, as demonstrated by a large body of modeling research that quantifies the impacts of occupant behavior on building operations. Yet, available occupant field data are insufficient to explore the mechanisms that drive this interaction. This paper introduces data from a one year study of 24 U.S. office occupants that recorded a comprehensive set of possible exogenous and endogenous drivers of personal comfort and behavior over time. The longitudinal data collection protocol merges individual thermal comfort, preference, and behavior information from online daily surveys with datalogger readings of occupants’ local thermal environments and control states, yielding 2503 survey responses alongside tens of thousands of concurrent behavior and environment measurements. These data have been used to uncover links between the built environment, personal variables, and adaptive actions, and the data contribute to international research collaborations focused on understanding the human-building interaction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Matrix Effects in Biological Mass Spectrometry Imaging: Identification and Compensation

Matrix effects in mass spectrometry imaging (MSI) may affect the observed molecular distribution in chemical and biological systems. In this study, we introduce an experimental approach that efficiently compensates for matrix effects in nanospray desorption electrospray ionization (nano-DESI) MSI without introducing any complexity into the experimental protocol. We demonstrate compensation for matrix effects in nano-DESI MSI of phosphatidylcholine (PC) in normal and ischemic mouse brain tissue by doping the nano-DESI solvent with PC standards. Specifically, we use mouse brain tissue of a middle cerebral artery occlusion (MCAO) stroke model with an ischemic region localized to one hemisphere of the brain. Due to similar suppression in ionization of endogenous PC molecules extracted from the tissue and PC standards added to the solvent, matrix effects are eliminated by normalizing the intensity of the sodium and potassium adducts of endogenous PC to the intensity of the corresponding adduct of the PC standard. This approach efficiently compensates for signal variations resulting from differences in the local concentrations of sodium and potassium in tissue sections and from the complexity of the extracted analyte mixture derived from local variations in molecular composition.

Environmental Molecular Sciences Laboratory↗

Influence of near-surface oxide layers on TiFe hydrogenation: mechanistic insights and implications for hydrogen storage applications

The inevitable formation of passivating oxide films on the surface of the TiFe intermetallic compound limits its performance as a stationary hydrogen storage material. Extensive experimental efforts have been dedicated to the activation of TiFe, i.e. oxide layer removal prior to utilization for hydrogen storage. However, development of an efficient activation protocol necessitates a fundamental understanding of the composition and structure of the air-exposed surface and its interaction with hydrogen, which is currently absent. Therefore, in this study we explored the growth and nature of oxide films on the most exposed TiFe surface (110) in depth using static and dynamic first-principles methods. We identified the lowest energy structures for six oxygen coverages up to approximately 1.12 nm of thickness with a global optimization method and studied the temperature effects and structural evolution of the oxide phases in detail via ab initio molecular dynamics (AIMD). Based on structural similarity and coordination analysis, motifs for TiO 2 and TiFeO 3 as well as Ti(FeO 2 ) x (x = 2, 3 or 5) phases were identified. On evaluating the interaction of the oxidized surface with hydrogen, a minimal energy barrier of 0.172 eV was predicted for H 2 dissociation while H migration from the top of the oxidized surface to the bulk TiFe was limited by several high-lying energy barriers above 1.4 eV. Our mechanistic insights will prove themselves valuable for informed designs towards new activation methods of TiFe and related systems as hydrogen storage materials.

08 HYDROGEN↗

Quantum model learning agent: characterisation of quantum systems through machine learning

Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distil empirically. Here, we report an algorithm—the quantum model learning agent (QMLA)—to reverse engineer Hamiltonian descriptions of a target system. We test the performance of QMLA on a number of simulated experiments, demonstrating several mechanisms for the design of candidate Hamiltonian models and simultaneously entertaining numerous hypotheses about the nature of the physical interactions governing the system under study. QMLA is shown to identify the true model in the majority of instances, when provided with limited a priori information, and control of the experimental setup. Our protocol can explore Ising, Heisenberg and Hubbard families of models in parallel, reliably identifying the family which best describes the system dynamics. We demonstrate QMLA operating on large model spaces by incorporating a genetic algorithm to formulate new hypothetical models. The selection of models whose features propagate to the next generation is based upon an objective function inspired by the Elo rating scheme, typically used to rate competitors in games such as chess and football. In all instances, our protocol finds models that exhibit F 1 score ≥ 0.88 when compared with the true model, and it precisely identifies the true model in 72% of cases, whilst exploring a space of over 250 000 potential models. By testing which interactions actually occur in the target system, QMLA is a viable tool for both the exploration of fundamental physics and the characterisation and calibration of quantum devices.

97 MATHEMATICS AND COMPUTING↗

Final Report for research grant entitled "Development of Reagents for Application of At-211 and Bi-213 to Targeted Radiotherapy of Cancer"

This grant was a one-year extension of another grant with the same title (DE-FG03-98ER62572). The objective of the studies was to continue in vivo evaluation of reagents to determine which changes in structure were most favorable for in vivo use. The focus of our studies was development and optimization of reagents for pretargeting alpha-emitting radionuclides At-211 or Bi-213 to cancer cells. Testing of the reagents was conducted in vitro and in animal model systems. During the funding period, all three specific aims set out in the proposed studies were worked on, and some additional studies directed at development of a method for direct labeling of proteins with At-211 were investigated. We evaluated reagents in two different approaches in 'two step' pretargeting protocols. These approaches are: (1) delivery of the radionuclide on recombinant streptavidin to bind with pretargeted biotinylated monoclonal antibody (mAb), and alternatively, (2) delivery of the radionuclide on a biotin derivative to bind with pretargeted antibody-streptavidin conjugates. The two approaches were investigated as it was unclear which will be superior for the short half-lived alpha-emitting radionuclides.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

2015 ESGF Progress Report

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration whose purpose is to develop the software infrastructure needed to facilitate and empower the study of climate change on a global scale. ESGF’s architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces. The cornerstones of its interoperability are the peer-to-peer messaging, which is continuously exchanged among all nodes in the federation; a shared architecture for search and discovery; and a security infrastructure based on industry standards. ESGF integrates popular application engines available from the open-source community with custom components (for data publishing, searching, user interface, security, and messaging) that were developed collaboratively by the team. The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs of the global climate science community.

54 ENVIRONMENTAL SCIENCES↗

Game Theoretic Approach for Understanding and Modeling Clinical Pathways (Stable Ischemic Heart Disease)

This research develops a game-theoretic agent model for stable ischemic heart disease (SIHD) clinical decisions, incorporating aspects of Bayesian game theory to model hidden information such as the patient’s true underlying medical condition(s). Preexisting observational medical data contained in the United States Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) is analyzed to obtain the required game-theoretic parameter values. Various statistical adjustments are performed to correct for bias in the preexisting treatment protocol selections and to obtain game-theoretic parameter values for contrafactual treatment protocol choices. Once the game-theoretic parameter values are determined, clinical pathways can be viewed as being mathematical strategies for playing the game and thus can be studied and evaluated using the techniques of game theory.

59 BASIC BIOLOGICAL SCIENCES↗

WE-FG-207B-11: Objective Image Characterization of Spectral CT with a Dual-Layer Detector

Purpose: To obtain objective reference data for the spectral performance on a dual-layer detector CT platform (IQon, Philips) and compare virtual monoenergetic to conventional CT images. Methods: Scanning was performed using the hospital’s clinical adult body protocol: helical acquisition at 120kVp, with CTDIvol=15mGy. Multiple modules (591, 515, 528) of a CATPHAN 600 phantom and a 20 cm diameter cylindrical water phantom were scanned. No modifications to the standard protocol were necessary to enable spectral imaging. Both conventional and virtual monoenergetic images were generated from acquired data. Noise characteristics were assessed through Noise Power Spectra (NPS) and pixel standard deviation from water phantom images. Spatial resolution was evaluated using Modulation Transfer Functions (MTF) of a tungsten wire as well as resolution bars. Low-contrast detectability was studied using contrast-to-noise ratio (CNR) of a low contrast object. Results: MTF curves of monoenergetic and conventional images were almost identical. MTF 50%, 10%, and 5% levels for monoenergetic images agreed with conventional images within 0.05lp/cm. These observations were verified by the resolution bars, which were clearly resolved at 7lp/cm but started blurring at 8lp/cm for this protocol in both conventional and 70 keV images. NPS curves indicated that, compared to conventional images, the noise power distribution of 70 keV monoenergetic images is similar (i.e. noise texture is similar) but exhibit a low frequency peak at keVs higher and lower than 70 keV. Standard deviation measurements show monoenergetic images have lower noise except at 40 keV where it is slightly higher. CNR of monoenergetic images is mostly flat across keV values and is superior to that of conventional images. Conclusion: Values for standard image quality metrics are the same or better for monoenergetic images compared to conventional images. Results indicate virtual monoenergetic images can be used without any loss in image quality or noise penalties relative to conventional images. This study was performed as part of a research agreement among Philips Healthcare, University Hospitals of Cleveland, and Case Western Reserve University.

60 APPLIED LIFE SCIENCES↗

Comparison of 20 nm silver nanoparticles synthesized with and without a gold core. Structure, dissolution in cell culture media, and biological impact on macrophages

Widespread use of silver nanoparticles raises questions of environmental impact and toxicity. Both silver particles and silver ions formed by particle dissolution may impact biological systems. Therefore it is important to understand the characteristics of silver nanoparticles and their stability in relevant media. The synthesis route can impact physical and chemical characteristics of the particles and we report the characterization and solution stability of three types of silver nanoparticles (20 nm particles with and without gold cores and 110 nm particles with gold cores) in cell culture media with serum proteins: FBS10%/RPMI. These nanoparticles were synthesized in aqueous solution and characterized using both in situ and ex situ analysis methods. Dissolution studies were carried at particle concentrations from 1 µg/ml to 50 µg/ml. Particles with gold cores had smaller crystallite size and higher apparent solubility than pure silver particles. A dissolution model was found to describe the time variation of particle size and amount of dissolved silver for particle loadings above 9 µg/ml. An effective solubility product obtained from fitting the data was higher for the 20 nm gold core particles in comparison to the pure silver or 110 nm particles. Dissolution of the nanoparticles was enhanced by presence of serum proteins contained in fetal bovine serum. In addition, the protocol of the dispersion in the medium was found to influence particle agglomeration and dissolution. Results show that particle structure can impact the concentration of dissolved silver and the dose to which cells would be exposed during in vitro studies.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed. While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Here, starting with 70 150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

08 HYDROGEN↗

General Protocol for the Accurate Prediction of Molecular 13 C/ 1 H NMR Chemical Shifts via Machine Learning Augmented DFT

An accurate prediction of NMR chemical shifts at affordable computational cost is very important for different types of structural assignments in experimental studies. Density functional theory (DFT) and gauge-including atomic orbital (GIAO) are two of the most popular computational methods for NMR calculation, yet they often fail to resolve ambiguities in structural assignments. In this work, we present a new method that uses machine learning (ML) techniques (DFT + ML) that significantly increases the accuracy of 13 C/ 1 H NMR chemical shift prediction for a variety of organic molecules. The input of the generalizable DFT + ML model contains two critical parts: one is a vector providing insights into chemical environments, which can be evaluated without knowing the exact geometry of the molecule; the other one is the DFT-calculated isotropic shielding constant. The DFT + ML model was trained with a data set containing 476 13 C and 270 1 H experimental chemical shifts. For the DFT methods used here, the root mean square deviations (RMSDs) for the errors between predicted and experimental 13 C/ 1 H chemical shifts can be as small as 2.10/0.18 ppm, which is much lower than those from simple DFT (5.54/0.25 ppm), or DFT + linear regression (LR) (4.77/0.23 ppm) approaches. It also has a smaller maximum absolute error than two previously proposed NMR-predicting ML models. The robustness of the DFT + ML model is tested on two classes of organic molecules (TIC10 and hyacinthacines), where the correct isomers were unambiguously assigned to the experimental ones. Overall, the DFT + ML model shows promise for structural assignments in a variety of systems, including stereoisomers, that are often challenging to determine experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TH-AB-201-04: Clinical Protocol for Reuse of Optically Stimulated Luminescence Detectors

Purpose: OSLDs made of Al2O3:C have many useful dosimetric characteristics including their ability to be reused. The signal on an OSLD can be removed through heat or light. The objective of this study was to characterize the change in sensitivity associated with annealing OSLDs with light and in doing so define a range through which reuse is viable. Methods: Four groups of nanoDot OSLDs were repeatedly irradiated and bleached to create accumulated dose history. Each group’s repeated irradiation remained constant at either 50, 100, 200, or 500 cGy. Before both irradiation and bleaching the OSLDs were read out, giving the dose reading and ensuring that ample bleaching had occurred, respectively. New and used OSLDs were compared in several clinical situations to verify accuracy. One final test involved correcting the readout dose based on the loss of sensitivity seen in the accumulated dose data. Results: In the first 40 Gy of accumulated dose the sensitivity can be broken into two regions: a region of sensitivity change and a region of no sensitivity change. From 0 cGy to an average of 1080 cGy the sensitivity does not change. After 1080 cGy the sensitivity begins to decrease linearly with an average slope of 0.00456 cGy lost per cGy accumulated after the cutoff point. The slope and cutoff point were used to correct readings in the final test, reducing the error from 6.8% to 3.9%. Conclusion: In the region of no sensitivity change OSLDs can be reused without concern to the validity of their result. Readings must be corrected if OSLDs are to be used in the region of sensitivity change, above 1080 cGy. After 40 Gy OSLDs must be retired because the sensitivity change reverses, making linear correction no longer feasible.

60 APPLIED LIFE SCIENCES↗