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.^

Using service-learning to encourage community health advocacy among high school students

The project outlined throughout this program management plan aims to develop a health-focused student advocacy group in the San Antonio Independent School District (SAISD). At its core, this project will be an opportunity for SAISD students to engage in service-learning, through which they will learn and develop by designing, organizing and participating in meaningful public health service experiences. ^ This program management plan addresses the genuine need for public health community education by using the service-learning model as a framework to engage students to effect change. The plan delineates the process by which the student advocacy group is to be assembled, selection of service-learning project, project objectives, technical objectives, and communication requirements. Ideally, the plan should help to facilitate project coordination, communication, and planning, and to support the direction of resources. The appendices that follow also provide useful tools with which to follow through with project implementation. ^ The plan is about more than providing a tool to educate students about the health issues in their community. It is about providing a way to teach health advocacy and self-interest and encourage civic engagement via public health. Students have the potential to positively effect lasting change among their peers, in their schools and in the community.^

Description and analysis of variation in dairy product and concomitant nutrient purchases between Hispanic and non -Hispanic households using a panel of shoppers' purchase records

The purpose of this research was development of a method of estimating nutrient availability in populations as approximated by supermarket purchase records. Demographic information describing 12,516 panel households was obtained from a marketing and advertising program operated by H. E. Butt Grocery Company of San Antonio, Texas. A non-probability sample of 2,161 households meeting expenditure criteria was selected and all purchases of dairy products for this sample of households were organized into a database constructed to facilitate the retrieval, aggregation, and analysis of dairy product purchases and their nutrient contents. Two hypotheses were tested: (1) no difference would be found between Hispanic and non-Hispanic purchases of dairy product categories during the study period and (2) no difference would be found between Hispanic and non-Hispanic purchases of nutrients contained in those dairy products during the thirteen-week study period.^ Food purchase records were used to estimate nutrient exposure on a weekly, per capita basis for Hispanic and non-Hispanic households by linking some 40,000 dairy purchase Universal Product code (UPC) numbers with food composition values contained in USDA Handbook 8-1. Results of this study suggest Hispanic sample households consistently purchased fewer dairy products than did non-Hispanic sample households and consequently had fewer nutrients available from dairy purchases. While weekly expenditures for dairy products among the sample households remained relatively constant during the study period, shifts in the types of dairy products purchased were observed. The effect of ethnicity on dairy product and nutrient purchases was significant over the thirteen-week period. A database consisting of customer, household, and purchase information can be developed to successfully associate food item UPC numbers with a standard reference of food composition to estimate nutrient availability in a population over extended periods of time. ^

Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

Modulatory effects of bag cell peptides in {\it Aplysia}: Behavioral and electrophysiological studies

Reproductive hormones have effects on the nervous system not directly related to reproductive function. In the rat, for example, luteinizing hormone releasing hormone has dramatic effects on learning and memory. The present work attempts to examine the effects of reproductive hormones on non-reproductive behaviors and the neural loci and mechanisms underlying these effects in Aplysia, an animal whose behaviors, reproductive hormones and neural circuitry have been well characterized.^ In Aplysia, the neurosecretory bag cells release several peptides that are responsible for eliciting egg laying. The effects of these peptides on the defensive tail-siphon withdrawal reflex, as well as sensitization of this reflex, were examined. Sensitization, a simple form of nonassociative learning, refers to the behavioral enhancement of a response to a test stimulus after the presentation of a strong stimulus, that may last minutes (short-term) or days (long-term). An extract of the bag cells (BCE) inhibited the baseline siphon component of the tail-siphon withdrawal reflex and suppressed long-term, but not short-term, sensitization of the reflex. Preliminary experiments suggest that BCE also affects the tail component of the tail-siphon withdrawal reflex.^ To determine the neural mechanisms underlying the inhibition of the baseline reflex, electrophysiological studies were performed using an in vitro analogue of the tail-siphon withdrawal reflex to examine the ability of BCE, as well as the individual bag cell peptides (BCPs), to modulate the circuitry of the reflex. Bag cell extract attenuated the synaptic strength of the monosynaptic connections between tail sensory neurons and tail motor neurons. When individually applied only $\beta$-BCP produced a similar attenuation. This effect of $\beta$-BCP was not dependent on changes in duration of the presynaptic action potential.^ An in vitro analogue of long-term sensitization training was developed to examine the mechanisms by which the BCPs may affect long-term sensitization of the tail-siphon withdrawal reflex. This analogue exhibited both short- and long-term facilitation of the connections between the tail sensory and motor neurons.^ The results of these behavioral and electrophysiological experiments suggest that the BCPs inhibit the tail-siphon withdrawal reflex, at least in part, by modulating the synaptic strength of the connections between the sensory neurons and motor neurons underlying the reflex. One candidate for this effect is $\beta$-BCP. Thus, the peptides which elicit egg laying may also serve other functions such as the inhibition of defensive reflexes. In addition, these experiments raise the possibility that BCPs may exert a long lasting effect ($>$24 hr), suppressing long-term sensitization of the tail-siphon withdrawal reflex. ^