Large Uncertainty Factors Research Articles

Fast uncertainty reduction of chemical kinetic models with complex spaces using hybrid response-surface networks

Response-surface (RS) surrogate approaches permit efficient inverse uncertainty quantification (UQ) of combustion kinetic models, wherein the uncertainty of reaction rates is reduced from observed targets. For kinetic models with parameters characterized by large uncertainty factors, strong nonlinearities, and reaction couplings (e.g., reduced mechanisms of real fuels; such models are referred to be “complex” in this work), the global RS is difficult to approximate, precluding conventional surrogate approaches. This paper proposes a framework that is extendable to such systems, termed Hybrid Response Surface Networks followed by a Stochastic Gradient Descent Ensemble (HRSN-SGDE). This technique focuses on mapping the local RS of just the uncertain spaces in the vicinity of the observed target, referred to as the rate target subspace. Two neural network surrogates are considered: a classifier that predicts the probability of data residing in the rate target subspace and a local RS surrogate which maps the RS of this subspace. A hybrid surrogate loss function is then defined using these surrogates to optimize uncertain rates repeatedly to get an ensemble of solutions representing the constrained rate space. HRSN-SGDE is demonstrated on a complex jet fuel model developed using the hybrid chemistry (HyChem) approach with a low temperature chemistry sub-model using a series of ignition delay times as targets. Results show that the method's local RS objective enables efficient and accurate construction of the surrogates through active learning-based sampling. Also, the unique formulation of the surrogate loss function enables optimization that is robust to suboptimal local minima and faster than evolutionary algorithms by several orders of magnitude. It is shown that HRSN-SGDE method is highly efficacious and suitable to conducting inverse UQ on such complex kinetic models.

An Analytical Strategy Based on Multiple Complementary and Orthogonal Chromatographic and Detection Methods (Multidetector Approach) to Effectively Manage the Analytical Evaluation Threshold (AET).

To address patient safety, a drug product is chromatographically screened for organic leachables. Similarly, medical device and packaging system extracts are chromatographically screened for organic extractables as probable leachables. To protect patient health, the screening methods must respond to all potentially unsafe substances. To be efficient, analytes determined to be below the toxicologically relevant threshold are removed from consideration before the subsequent analytical tasks of identification and quantitation are performed. The analytical evaluation threshold (AET) was established for use as a toxicologically relevant threshold to differentiate between chromatographic peaks that are unlikely to be unsafe (and thus do not need safety assessment) and those that are possibly unsafe (and thus require safety assessment). In practice, the instrumental response associated with the AET is determined using surrogate standards. It is then assumed that the response strength for an unknown extractable is equivalent to that for the surrogate standard at the AET concentration (i.e., relative response factor = 1). It is an unfortunate reality that response factors vary for different compounds on nearly all detector systems. This complicates the application of the AET and can result in a failure to include potentially toxicologically relevant compounds in the identification phase of the analysis. To ensure protection, an uncertainty factor was built into the AET equation that adjusts the AET downward to address response variation. Although this mechanism does increase the protectiveness of the AET, it assumes that the available methodology and instrumentation is sufficiently sensitive to reach the new lowered AET value. However, in some cases, the response variation is so great and the resulting uncertainty factor so large that the revised AET is below the achievable sensitivity specifications of even state-of-the art, expertly operated instrumental technologies. The only option then remaining is to concentrate the samples, which can result in adverse effects on analysis quality-counteracting the perceived benefit of lowering the AET. This article demonstrates how an analytical strategy based on methods with multiple complementary and orthogonal detection techniques (a multidetector approach) mitigates the problem of response factor variation and thus eliminates the need for large uncertainty factors and the resulting lower AET values. The primary concept is that all analytes only need to be effectively detected by at least one of the combination of detectors applied, and it is this effective technique (combination of all detectors and chromatographic methods utilized) that is used to perform the AET assessment.

Reducing relative response factor variation using a multidetector approach for extractables and leachables (E&L) analysis to mitigate the need for uncertainty factors

Characterization of Extractables and Leachables (E&Ls) is an important aspect of product quality in important fields such as pharmaceuticals, medical devices and food contact materials. The main goal of an E&L study is identification and quantification of those species which may leach from packaging materials used to contain pharmaceuticals or which may leach directly out of a medical device or food contact material and thus may result in patient exposure. It is common practice to perform relative quantitation of extractables and leachables using surrogate standards due to the large diversity of species observed and the lack of available reference standards. A key problem in obtaining accurate E&L results arises due to response factor (RF) variation. Different compounds at the same concentration give different signal intensities and thus have different RF values. Two key aspects of study quality are affected by this problem. First, the evaluation of the number of compounds which are above the toxicologically relevant threshold (analytical evaluation threshold, (AET)) can be affected (RF Problem 1: AET Underreporting). Second, quantitative accuracy is affected which can reduce the reliability of the margin of safety (MOS) calculations which serves as the basis of the toxicological evaluation (RF Problem 2: Quantitative Error). RF databases have been the main solution proposed for solving these problems but do not reduce the underlying RF variation and lack the scope required to address quantitative error for compounds not contained in the database. In the absence of other solutions, large uncertainty factors (UF) have been applied in the AET calculations to account for RF Problem 1: AET Underreporting. These UF factors have been assigned values of 4 for GCMS and up to 10 for LCMS. Large uncertainty factors have a number of unintended negative consequences including the need for large amounts of sample concentration (>10X) prior to analysis resulting in potential compound loss or degradation and increased matrix effects. To overcome these problems, this publication demonstrates a multidetector approach using an HPLC system coupled with a Quadrupole Time of Flight Liquid Chromatography Mass Spectrometer (QTOF-LCMS), Charged Aerosol Detector (CAD) and an Ultraviolet-Visible Detector (UV) and a dual detection Gas Chromatography Mass Spectrometry (GCMS) system using a Polyarc Reactor system with Flame Ionization Detection (FID). Herein, it is demonstrated that this combination of methods (the multidetector approach) allowed detection and accurate surrogate standard quantitation of 217 unique extractables spanning a wide range of chemical properties (Mw, logP, pKa and boiling point). The combination of optimized detector selection with appropriate standard selection was verified to provide positive detection for 94% of the compounds at the AET level and a high level of quantitative accuracy (± 20% for 85% of the compounds and ±40% for 91% of the compounds) while using only a UF of 2. Unlike the RF database approach, the multidetector approach is not limited to only those compounds contained in the database but is applicable to the majority of extractables.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes

PurposeTargeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively. MethodsIn this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework. ResultsThe mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3. ConclusionsIt is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.

NUMERICAL SIMULATION OF DIRECT MEASUREMENT TO DETERMINE THYROID 131I CONTENT OF TWO TEPCO WORKERS CONSIDERING INDIVIDUAL TISSUE THICKNESS.

After the Fukushima Daiichi Nuclear Power Station accident, the National Institute of Radiological Sciences examined seven heavily exposed emergency workers and performed internal dose estimations. The largest dose contributor was found to be (131)I, which was detected by thyroid monitor with an HPGe detector. Different energy peaks from (131)I were simultaneously identified in the pulse-height spectra of the two subjects with the highest doses regardless of late measurements. A closer look at the spectra indicated that the count ratio of the two peak areas at 80.2 and 365 keV differed somewhat between the individual workers, suggesting a difference in attenuation in the overlaying soft tissue and in the thyroid itself. In this study, the relationship between the count ratio (80.2/365 keV) and the thickness of soft tissue overlying the thyroid was investigated by means of numerical simulations performed using the Japanese Male (JM) phantom varying the thickness of the overlaying tissue. From the measured count ratios, it was possible to estimate that the overlaying tissue was thinner for Worker 1 (difference from the JM phantom: -0.34±1.29 cm) and thicker for Worker 2 (diff.: 2.5±1.2 cm). The thyroid (131)I contents evaluated taking into account the individual thicknesses were 4.3 kBq for Worker 1 and 8.4 kBq for Worker 2, resulting in a significant increase for Worker 2 compared with the content based on the default counting efficiency at 365 keV of the original JM phantom. However, the results have large uncertainty factors of 1.4 for Worker 1 and 1.3 for Worker 2 and should be carefully considered together with other factors influencing the attenuation.

Meta-analysis of preclinical studies of mesenchymal stromal cells for ischemic stroke

To evaluate the quality of preclinical evidence for mesenchymal stromal cell (MSC) treatment of ischemic stroke, determine effect size of MSC therapy, and identify clinical measures that correlate with differences in MSC effects. A literature search identified studies of MSCs in animal models of cerebral ischemia. For each, a Quality Score was derived, and effect size of MSCs was determined for the most common behavioral and histologic endpoints. Of 46 studies, 44 reported that MSCs significantly improved outcome. The median Quality Score was 5.5 (of 10). The median effect size was 1.78 for modified Neurological Severity Score, 1.73 for the adhesive removal test, 1.02 for the rotarod test, and 0.93 for infarct volume reduction. Quality Score correlated significantly and positively with effect size for the modified Neurological Severity Score. Effect sizes varied significantly with clinical measures such as administration route (intracerebral > intra-arterial > IV, although effect size for IV was nonetheless very large at 1.55) and species receiving MSCs (primate > rat > mouse). Because many MSC mechanisms are restorative, analyses were repeated examining only the 36 preclinical studies administering MSCs ≥ 24 hours poststroke; results were overall very similar. In preclinical studies, MSCs have consistently improved multiple outcome measures, with very large effect sizes. Results were robust across species studied, administration route, species of MSC origin, timing, degree of immunogenicity, and dose, and in the presence of comorbidities. In contrast to meta-analyses of preclinical data for other stroke therapies, higher-quality MSC preclinical studies were associated with larger behavioral gains. These findings support the utility of further studies to translate MSCs in the treatment of ischemic stroke in humans.

Comparison of methods for the determination of key reactions in chemical systems: Application to Titan’s atmosphere

A new paradigm is emerging in the field of photochemistry modeling in giant planets and Titan atmospheres. The emphasis is placed on the accurate predictions of the models and the quantification of their uncertainties. In order to improve photochemical models predictions, it is necessary to identify in chemical schemes the key reactions that should be studied in priority at conditions relevant to planetary atmospheres. We discuss the notion of key reactions in chemical schemes and we compare several methods dedicated to the search for these reactions. Our study focuses on the methods that have been published in the field of hydrocarbons photochemistry for giant planets and Titan atmospheres. These methods can be grouped into three families: determination of production paths, local sensitivity analysis methods and global sensitivity analysis methods. We first compare all these methods using a simple 0D photochemical toy model of Titan’s atmosphere as a study case. Then, we applied sensitivity analysis methods to a realistic hydrocarbons scheme. We show that, due to the current large uncertainty factors of the rate constants at low temperature (100 K < T < 200 K) and the nonlinearities in hydrocarbons photochemical models, global methods should be preferred to infer key reactions.

Toxicology of Micronutrients: Adverse Effects and Uncertainty

The establishment of safe upper intake levels for micronutrients must consider the intake-response relations for both deficiency and toxicity. Limited data are available on the toxicities of most micronutrients, and few studies that meet the criteria considered essential for the risk assessment of other chemicals in food, such as pesticides and food additives, have been performed. In some cases, the application of large uncertainty factors, which are used to establish the amount of a chemical that would be safe for daily intake throughout life, could result in nutritionally inadequate intakes of micronutrients. As a consequence, lower than normal uncertainty factors have been applied to determine safe or tolerable intakes of many micronutrients. There is no clear scientific rationale, on the basis of the metabolism and elimination of micronutrients or the nature of the adverse effects reported for high intakes, for the use of reduced uncertainty factors for micronutrient toxicity. A review of recent evaluations of selected vitamins and minerals shows little consistency in the application of uncertainty factors by different advisory groups, such as the Institute of Medicine in the United States and the Scientific Committee on Foods in the European Union. It is apparent that, in some cases, the uncertainty factor applied was selected largely to give a result that is compatible with nutritional requirements; therefore, the uncertainty factor represented part of risk management rather than hazard characterization. The usual risk assessment procedures for chemicals in food should be revised for micronutrients, so that the risks associated with intakes that are too low and too high are considered equally as part of a risk-benefit analysis.

ECOLOGICAL RISK OF MERCURY IN THE ENVIRONMENT: THE INADEQUACY OF “THE BEST AVAILABLE SCIENCE”

ECOLOGICAL RISK OF MERCURY IN THE ENVIRONMENT: THE INADEQUACY OF “THE BEST AVAILABLE SCIENCE”

In vivo thyroid monitoring for iodine-131 in the environment

Monitoring of air and milk samples is done routinely around nuclear facilities that release iodine-131 to the environment. Results from these measurements are used to calculate dose rates to the thyroids of people who live near such facilities. These calculated dose rates have large uncertainty factors associated with them due to the complexity of predicting the movement of iodine-131 through the environment. This paper describes an effort to monitor iodine-131 directly in the thyroids of individuals living in the environment. A NaI(Tl)-detector system was assembled in the back of a truck for rapid and convenient measurements of members of the general public. The monitoring system has a minimum detectable activity for thyroid-bound iodine-131 of approx. 35 pCi which is sensitive enough to satisfy all legal requirements for environmental monitoring in the U.S.A. except for the child who receives iodine-131 continuously from a nuclear-power plant. Thyroid doses are calculated with more certainty from in vivo measurements than from measurements made on environmental and effluent samples.