Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Mechanisms of multidrug resistance: Differences between natural and acquired adriamycin -resistant human colon carcinoma cells

Mechanisms of multidrug resistance (MDR) were studied in two independent MDR sublines (AdR1.2 and SRA1.2) derived from the established human colon carcinoma cell line LoVo. AdR1.2 was developed by long-term continuous exposure of the cells to adriamycin (AdR) in stepwise increments of concentration, while SRA1.2 was selected by repetitive pulse treatments with AdR at a single concentration. In this dissertation, the hypothesis that the mechanism of drug resistance in SRA1.2 is different than that in AdR1.2 is tested. While SRA1.2 demonstrated similar biological characteristics when compared to the parental LoVo, AdR1.2 exhibited remarkable alterations in biological properties. The resistance phenotype of AdR1.2 was reversible when the cells were grown in the drug-free medium whereas SRA1.2 maintained its resistance for at least 10 months under similar conditions. Km and Vmax of carrier-mediated facilitated diffusion AdR transport were similar among the three lines. However, both resistant sublines exhibited an energy-dependent drug efflux. AdR1.2 appeared to possess an activated efflux pump, and a decreased nucleus-binding of AdR, whereas SRA1.2 showed merely a lower affinity in binding of AdR to the nuclei. Southern blot analysis showed no amplification of the MDR1 gene in either of the two resistant subclones. However, Western blot analysis using the C219 monoclonal antibody against P170 glycoprotein detected a Mr 150-kDa plasma protein (P150) in AdR1.2 but not in SRA1.2 or in the parental LoVo. In vitro phosphorylation studies revealed that P150 was a phosphoprotein; its phosphorylation was Mg$\sp{2+}$-dependent and could be enhanced by verapamil, an agent capable of increasing intracellular AdR accumulation in AdR1.2 cells. The phosphorylation studies also revealed elevated phosphorylation of a Mr 66-kDa plasma membrane protein that was detectable in the AdR1.2 revertant and in AdR1.2 when verapamil was present, suggesting that hyperphosphorylation of the Mr 66-kDa protein may be related to the reversal of MDR. SDS-PAGE of the plasma membrane protein demonstrated overproduction of a Mr 130-kDa, MDR-related protein in both the resistant sublines. The Mr 130-kDa, MDR-related protein in both the resistant sublines. The Mr 130-kDa protein was not immunoreactive with C219, but its absence in the AdR1.2 revertant and the parental LoVo suggests that it is an MDR-related plasma membrane protein. In conclusion, the results from this study support the author's hypothesis that the mechanisms responsible for "Acquired" and "Natural" MDR are not identical. ^

THE NATURAL BACKGROUND GAMMA RADIATION EXPOSURE IN THE METROPOLITAN AREA OF THE VALLEY OF MEXICO

Measurements of the natural background radiation have been made at numerous places throughout the world. Very little work in this field has been done in developing countries. In Mexico the natural radiation to which the population is exposed has not been assessed. This dissertation represents a pioneer study in this environmental area. The radiation exposure which occupants within buildings receive as a result of naturally occurring radionuclides present in construction materials is the principal focus.^ Data were collected between August 1979 and November 1980. Continuous monitoring was done with TLDs placed on site for periods of 3 to 6 months. The instrumentation used for "real-time" measurements was a portable NaI (Tl) scintillation detector. In addition, radiometric measurements were performed on construction materials commonly used in Mexican homes.^ Based on TLD readings taken within 75 dwellings, the typical indoor exposure for a resident of the study area is 9.2 (mu)Rh('-1). The average reading of the 152 indoor scintillometer surveys was 9.5 (mu)Rh('-1), the outdoor reading 7.5 (mu)Rh('-1). Results of one-way and multi-way analyses of the exposure data to determine the effect due to building materials type, geologic subsoil, age of dwelling, and elevation are also presented. The results of 152 indoor scintillometer surveys are described. ^

Use of a modified delphi process for establishing occupational exposure limits in support of health surveillance for space travelers

On-orbit exposures can come from numerous factors related to the space environment as evidenced by almost 50 years of environmental samples collected for water analysis, air analysis, radiation analysis, and physiologic parameters. For astronauts and spaceflight participants the occupational exposures can be very different from those experienced by workers performing similar tasks in workplaces on Earth, because the duration of the exposure could be continuous for very long orbital, and eventually interplanetary, missions. The establishment of long-term exposure standards is vital to controlling the quality of the spacecraft environment over long periods. NASA often needs to update and revise its prior exposure standards (Spacecrafts Maximum Allowable Concentrations (SMACs)). Traditional standards-setting processes are often lengthy, so a more rapid method to review and establish standards would be a substantial advancement in this area. This project investigates use of the Delphi method for this purpose. ^ In order to achieve the objectives of this study a modified Delphi methodology was tested in three trials executed by doctoral students and a panel of experts in disciplines related to occupational safety and health. During each test/trial modifications were made to the methodology. Prior to submission of the Delphi Questionnaire to the panel of experts a pilot study/trial was conducted using five doctoral students with the goals of testing and adjusting the Delphi questionnaire to improve comprehension, work out any procedural issues and evaluate the effectiveness of the questionnaire in drawing the desired responses. The remainder of the study consisted of two trials of the Modified Delphi process using 6 chemicals that currently have the potential of causing occupational exposures to NASA astronauts or spaceflight participants. To assist in setting Occupational Exposure Limits (OEL), the expert panel was established consisting of experts from academia, government and industry. Evidence was collected and used to create close-ended questionnaires which were submitted to the Delphi panel of experts for the establishment of OEL values for three chemicals from the list of six originally selected (trial 1). Once the first Delphi trial was completed, adjustments were made to the Delphi questionnaires and the process above was repeated with the remaining 3 chemicals (trial 2). ^ Results indicate that experience in occupational safety and health and with OEL methodologies can have a positive effect in minimizing the time experts take in completing this process. Based on the results of the questionnaires and comparison of the results with the SMAC already established by NASA, we conclude that use of the Delphi methodology is appropriate for use in the decision-making process for the selection of OELs.^