Scenario-specific Information Research Articles

Modeling Environmental Fate, Transport, and Transformation of Pesticides: First-Order Kinetic Models for Regional and Global Applications

Predicting pesticide residue masses in environments requires time- and cost-efficient fate models, particularly for high-throughput simulations of hundreds of active ingredients registered for use in agriculture. Due to the adaptability of first-order kinetics-based models for simulating the fate of pesticides in environments of varying scales, we conduct a review of these models in the present investigation. We discuss the application of first-order kinetics-based fate models in different types of compartments, such as environmental media, plant tissues, and animal bodies, and at different levels, such as the product-oriented life cycle impact assessment and the chemical-oriented health risk assessment. In addition, the first-order kinetics-based rate constants of pesticides provide process- and scenario-specific information on the fate, transport, and transformation of pesticides, which is essential for predicting pesticide residue masses in different environmental compartments. By varying the level of model complexity and site-specific rate constants of pesticides, the first-order kinetics-based fate models can be used as either comparable or absolute tools for conducting the life cycle impact assessment or the health risk assessment of pesticides, respectively. Bioconcentration, bioaccumulation, and biomagnification of pesticides may be evaluated with the aid of an inventory database of rate constants based on first-order kinetics in future research. We suggest incorporating non-first-order kinetic processes into the first-order kinetics-based model to advance risk assessment, as well as approximating non-first-order kinetic processes using first-order kinetics to facilitate life cycle impact or screening-level risk assessments.

Accuracy of professional judgments for dermal exposure assessment using deterministic models

ABSTRACT The accuracy of exposure judgments, particularly for scenarios where only qualitative information is available or a systematic approach is not used, have been evaluated and shown to have a relatively low level of accuracy. This is particularly true for dermal exposures, where less information is generally available compared to inhalation exposures. Relatively few quantitative validation efforts have been performed for scenarios where dermal exposures are of interest. In this study, a series of dermal exposure judgments were collected from 90 volunteer U.S. occupational health practitioners in a workshop format to assess the accuracy of their judgments for three specific scenarios. Accuracy was defined as the ability of the participants to identify the correct reference exposure category, as defined by the quantitative exposure banding categories utilized by the American Industrial Hygiene Association (AIHA). The participants received progressively additional information and training regarding dermal exposure assessments and scenario-specific information during the workshop, and the relative accuracy of their category judgments over time was compared. The results of the study indicated that despite substantial education and training in exposure assessment generally, the practitioners had very little experience in performing dermal exposure assessments and a low level of comfort in performing these assessments. Further, contrary to studies of practitioners performing inhalation exposure assessments demonstrating a trend towards underestimating exposures, participants in this study consistently overestimated the potential for dermal exposure without quantitative data specific to the scenario of interest. Finally, it was found that participants were able to identify the reference or “true” category of dermal exposure acceptability when provided with relevant, scenario-specific dermal and/or surface loading data for use in the assessment process. These results support the need for additional training and education of practitioners in performing dermal exposure assessments. A closer analysis of default loading values used in dermal exposure assessments to evaluate their accuracy relative to real-world or measured dermal loading values, along with consistent improvements in current dermal models, is also needed.

Methodology for scenario-based assessments and demonstration of treatment effectiveness using the Leaching Environmental Assessment Framework (LEAF)

A methodology for developing scenario-based leaching assessments as part of the Leaching Environmental Assessment Framework (LEAF) is illustrated using a hypothetical management/treatment scenario of contaminated soil from a copper and lead smelter. Scenario assessments refine the process beyond screening-level assessments by considering site- and scenario-specific information about the disposal or utilization environment. LEAF assessments assume (i) granular materials leach at local equilibrium with percolating water, while (ii) monolithic materials (e.g., low permeability solidified/stabilized soils) leach by diffusion-based mass transport toward surrounding contact water. Leaching concentrations, estimated using LEAF leaching test data and estimated or measured scenario information, are compared to threshold values. Demonstration results indicate that leaching from untreated soil is significantly (>10x) greater from solidified/stabilized soil than treated material, except for highly soluble constituents (Cl-, NO3−2) or when constituents have similar equilibrium concentrations in both materials (As, Pb). Comparison between wet and dry environments show that while dry environments lead to lower COPC mass-based rates of leaching, the leaching concentrations may be higher due to lower liquid-to-solid ratios. The presented assessment methodology can be used to evaluate treatment effectiveness when both physical and chemical retention characteristics of the material are altered.

Impact of stressors in the aviation environment on xenobiotic dosimetry in humans: physiologically based prediction of the effect of +Gz-forces

ABSTRACT The application of physiologically based modeling approaches in evaluating health risks in diverse environments is limited by scarcity of comprehensive reviews detailing how physiological parameters are altered due to stressors. A modern high-performance aviation environment in particular has the potential for simultaneous exposure to chemical and non-chemical stressors which may interact via non-chemical stressor-mediated pharmacokinetic alterations. To support physiologically based pharmacokinetic (PBPK) modeling of in-flight disposition inhaled chemicals, literature review, and synthesis was conducted to determine the impact of gravitational (+Gz) forces on PBPK modeling inputs. Specifically, changes in cardiac output and related parameters heart rate and stroke volume, breathing frequency, tidal volume, and pulmonary and alveolar ventilation rate in vivo were extracted from 36 publications and related mathematically to +Gz intensity. A scenario was simulated where a pilot performing test flights might inhale organic chemicals at the occupational exposure guideline level while experiencing sustained, elevated +Gz. Peak arterial blood concentrations of 1,2,4-trimethylbenzene during a 1 h-flight at +4 Gz were predicted to increase 2-fold relative to would occur on the ground under baseline conditions. This case study demonstrates the potential value of scenario-specific physiological information in assessing changes in risk-relevant internal dosimetry, providing better information for potential risk management actions.

Modeling Tool for Decision Support during Early Days of an Anthrax Event.

Health officials lack field-implementable tools for forecasting the effects that a large-scale release of Bacillus anthracis spores would have on public health and hospitals. We created a modeling tool (combining inhalational anthrax caseload projections based on initial case reports, effects of variable postexposure prophylaxis campaigns, and healthcare facility surge capacity requirements) to project hospitalizations and casualties from a newly detected inhalation anthrax event, and we examined the consequences of intervention choices. With only 3 days of case counts, the model can predict final attack sizes for simulated Sverdlovsk-like events (1979 USSR) with sufficient accuracy for decision making and confirms the value of early postexposure prophylaxis initiation. According to a baseline scenario, hospital treatment volume peaks 15 days after exposure, deaths peak earlier (day 5), and recovery peaks later (day 23). This tool gives public health, hospital, and emergency planners scenario-specific information for developing quantitative response plans for this threat.

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Tailoring a cognitive model for situation awareness using machine learning

Using a pure machine learning approach to enable the generation of behavior for agents in serious gaming applications can be problematic, because such applications often require human-like behavior for agents that interact with human players. Such human-like behavior is not guaranteed with e.g. basic reinforcement learning schemes. Cognitive models can be very useful to establish human-like behavior in an agent. However, they require ample domain knowledge that might be difficult to obtain. In this paper, a cognitive model is taken as a basis, and the addition of scenario specific information is for a large part automated by means of machine learning techniques. The performance of the approach of automatically adding scenario specific information is rigorously evaluated using a case study in the domain of fighter air combat. An evolutionary algorithm is proposed for automatically tailoring a cognitive model for situation awareness of fighter pilots. The standard algorithm and several extensions are evaluated with respect to performance in air combat. The results show that it is possible to apply the algorithm to optimize belief networks for cognitive models of intelligent agents (adversarial fighters) in the aforementioned domain, thereby reducing the effort required to elicit knowledge from experts, while retaining the required `human-like' behavior.

Abstract 2389: Positive or negative clinical implications of PI3K/Akt/mTOR pathway activation for predicting patient response to targeted therapy using multiplexed protein imaging of tumor tissue.

Abstract Background: In this ongoing clinical exploratory study, FFPE tissue sections are probed for protein biomarkers along the PI3K/Akt/mTOR pathway. A panel of assays was developed using Layered Immunohistochemistry (L-IHC). L-IHC allows for concurrent measurement of 6-8 proteins (total and/or phosphorylation sites) using a single tissue section. The goal was to discover applications of the technique based on complementary rationales about the implications of pathway activation. Those were: 1) in a scenario where the test indicates drug target activation, analysis for a positive response to an mTOR-targeted tyrosine kinase inhibitor (everolimus and/or temsirolimus) in kidney cancer; or 2) analysis for predicting no response to a HER2-targeted drug (trastuzumab) in breast cancer, assuming a scenario where the test would indicate activation of a functional by-pass pathway. Methods: FFPE pre-treatment tissue samples from patients (pts) with advanced renal cell carcinoma (aRCC) treated with temsirolimus and/or everolimus, and trastuzumab treated HER2-positive breast cancer pts were studied. In L-IHC tissue-transfer layers, the intensity of specific protein biomarker signals in the cancer regions is visually scored. The expression levels are then summed and correlated with the patient's clinical outcome status. Results: In the trastuzumab study, four biomarkers were determined to correlate with patient response. A total of 32 responders and 13 non-responders have been analyzed to date. The sum score for a 4-biomarker panel discriminated between responders and non-responders. The test correctly identified 28/32 responders and 10/13 non-responders for a sensitivity of 87%, specificity of 76%, and an accuracy of 81%. In the mTOR inhibitor study, 35 RCC cases were analyzed, and a composite score based on 6 biomarkers was found to correlate to patient response. 11/14 OR/SD pts (sensitivity 79%) and 18/21 PD pts (specificity 86%). Conclusions: These results indicate that multiplexed protein analysis of tumor tissue is capable of providing scenario-specific information, which could help guide targeted therapy with either a positive or a negative clinical significance. Funding source: Supported in part by NCI Grant 5R44CA123994-06 and by 20/20 GeneSystems. Citation Format: Alexandrine Derrien-Colemyn, Soon Park, John Gillespie, Michael Lebowitz, Peter Tunon. Positive or negative clinical implications of PI3K/Akt/mTOR pathway activation for predicting patient response to targeted therapy using multiplexed protein imaging of tumor tissue. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2389. doi:10.1158/1538-7445.AM2013-2389

Vaccine Administration Decision Making: The Case of Yellow Fever Vaccine

Providers must counsel travelers to yellow fever (YF)-endemic areas, although risk estimates of disease and vaccine serious adverse events (SAEs) may be imprecise. The impact of risk information and patients' requests for participation in vaccine decisions on providers' recommendations is unknown. Vaccine providers were surveyed regarding decisions for 4 patient scenarios before and after being presented information about risk of YF disease vs vaccine SAEs. Participants' theoretical attitudes were compared with actual responses to scenarios in which patients wanted to share vaccine decisions. Analyses were done by using χ(2) tests with significance level of .05. Forty-six percent of respondents made appropriate initial YF vaccine administration decisions for a pregnant woman, 73% for an immunosuppressed man, and 49% for an 8-month-old infant. After receiving scenario-specific information, 20%, 54%, and 23% of respondents respectively who initially responded incorrectly changed to a more appropriate decision. Thirty-one percent of participants made consistently appropriate decisions. Among participants who made ≥1 incorrect decision, 35.7% made no decision changes after receiving information. In the scenario in which either a decision to withhold or to administer vaccine was acceptable, 19% of respondents refused a patient's request for vaccine. Targeted information is necessary but insufficient to change the process of vaccine administration decision making. Providers need additional education to enable them to apply evidence, overcome cognitive decision-making errors, and involve patients in vaccine decisions.

Knowledge-based information management for biomedical applications

Current large-scale information sources (structural, textual and images) are designed to support general queries and lack the ability to support scenario-specific information navigation, gathering, and presentation. As a result, users are often unable to obtain the specific information they desire within a well-defined subject area. Today's information systems do not provide efficient content navigation, incremental approximate matching, or content correlation. In this talk, we will present the following innovative technologies to remedy these problems: 1) scenario-based proxies, enabling the gathering and filtering of information customized for users within a pre-defined domain; 2) knowledge-based context-sensitive navigation and matching, providing approximate matching (for structured data, text documents, and images) and similarity links when an exact match to a user's request is unavailable; 3) knowledge-based query expansion for improving document retrieval effectiveness; 4) content correlation of documents, creating semantic links between the document content with relevant documents in the information sources; 5) user models for customizing retrieved information and result presentation. A digital medical library is currently under development at UCLA using these technologies to provide customized information for the users. This will serve as a step toward the development of a future paperless hospital. The technologies we proposed are general in nature and can provide custom and scenario-specific information to many other domains (e.g. crisis management).

A medical digital library to support scenario and user-tailored information retrieval.

Current large-scale information sources are designed to support general queries and lack the ability to support scenario-specific information navigation, gathering, and presentation. As a result, users are often unable to obtain desired specific information within a well-defined subject area. Today's information systems do not provide efficient content navigation, incremental appropriate matching, or content correlation. We are developing the following innovative technologies to remedy these problems: 1) scenario-based proxies, enabling the gathering and filtering of information customized for users within a pre-defined domain; 2) context-sensitive navigation and matching, providing approximate matching and similarity links when an exact match to a user's request is unavailable; 3) content correlation of documents, creating semantic links between documents and information sources; and 4) user models for customizing retrieved information and result presentation. A digital medical library is currently being constructed using these technologies to provide customized information for the user. The technologies are general in nature and can provide custom and scenario-specific information in many other domains (e.g., crisis management).