Incomplete lung recovery following sub-acute inhalation of combustion-derived ultrafine particles in mice.

BACKGROUND: Particulate matter (PM) is one of the six criteria pollutant classes for which National Ambient Air Quality Standards have been set by the United States Environmental Protection Agency. Exposures to PM have been correlated with increased cardio-pulmonary morbidity and mortality. Butadiene soot (BDS), generated from the incomplete combustion of 1,3-butadiene (BD), is both a model PM mixture and a real-life example of a petrochemical product of incomplete combustion. There are numerous events, including wildfires, accidents at refineries and tank car explosions that result in sub-acute exposure to high levels of airborne particles, with the people exposed facing serious health problems. These real-life events highlight the need to investigate the health effects induced by short-term exposure to elevated levels of PM, as well as to assess whether, and if so, how well these adverse effects are resolved over time. In the present study, we investigated the extent of recovery of mouse lungs 10 days after inhalation exposures to environmentally-relevant levels of BDS aerosols had ended. METHODS: Female BALB/c mice exposed to either HEPA-filtered air or to BDS (5 mg/m(3) in HEPA filtered air, 4 h/day, 21 consecutive days) were sacrificed immediately, or 10 days after the final BDS exposure. Bronchoalveolar lavage fluid (BALF) was collected for cytology and cytokine analysis. Lung proteins and RNA were extracted for protein and gene expression analysis. Lung histopathology evaluation also was performed. RESULTS: Sub-acute exposures of mice to hydrocarbon-rich ultrafine particles induced: (1) BALF neutrophil elevation; (2) lung mucosal inflammation, and (3) increased BALF IL-1ß concentration; with all three outcomes returning to baseline levels 10 days post-exposure. In contrast, (4) lung connective tissue inflammation persisted 10 days post-exposure; (5) we detected time-dependent up-regulation of biotransformation and oxidative stress genes, with incomplete return to baseline levels; and (6) we observed persistent particle alveolar load following 10 days of recovery. CONCLUSION: These data show that 10 days after a 21-day exposure to 5 mg/m(3) of BDS has ended, incomplete lung recovery promotes a pro-biotransformation, pro-oxidant, and pro-inflammatory milieu, which may be a starting point for potential long-term cardio-pulmonary effects.

Data qualification: logic analysis applied toward neural network training.

For neural networks to develop good internal representations for pattern mapping, noise in the training set data must be controlled. Because of the many difficulties associated with manually validating training data, we have focused on using decision table techniques as a practical, domain-independent means of optimizing training set formulation. Decision tables provide a variety of mechanisms whereby training set data can be processed to remove ambiguity, contradictions, and other noise. In addition to serving as data filters, decision tables can be used in the evaluation of neural network training.

The representation of time in clinical patient simulations.

Simulated clinical scenarios are generally compressed in time to enhance educational effectiveness and to minimize testing time. Designers should consider how to best control potential sources of distortion in the perception of time and how to best communicate the passage of time to the user.

Morphing as a means of generating variation in visual medical teaching materials.

In computer-based medical education, there is frequently a need to present students with pictorial data representative of the natural variation associated with disease presentations as well as the progression of disease within an individual. Because of the difficulty in acquiring such data, image acquisition is often the most resource-intensive phase of multimedia courseware development. In light of the resource demands associated with image content, many courseware designers do not make opportune use of image data, but rely instead upon text descriptions to provide variation in content. The resulting lack of adequate pictorial content often lessens the overall impact of the courseware. To overcome constraints imposed by the difficulty in acquiring pictorial content of sufficient richness, a methodology of generating variation in visual teaching materials has been developed through the use of morphing. These techniques have general applicability in creating variation in pictorial teaching materials in a variety of image-intensive domains.

Enhancing the Metathesaurus with clinically relevant concepts: anatomic representations.

To create a comprehensive taxonomy for medical concepts it is necessary to identify gaps and reconcile differences that exist between clinical, bibliographic, and other source vocabularies. As part of the Unified Medical Language System project, we have proposed enhancements to the Metathesaurus by the inclusion of terms from two source vocabularies with different unique perspectives or views. This process has disclosed a number of issues that arise as complexity increases. These issues must be resolved if the resultant Metathesaurus is to support the variety of uses for which it is intended.

Composing user models through logic analysis.

The evaluation of tutorial strategies, interface designs, and courseware content is an area of active research in the medical education community. Many of the evaluation techniques that have been developed (e.g., program instrumentation), commonly produce data that are difficult to decipher or to interpret effectively. We have explored the use of decision tables to automatically simplify and categorize data for the composition of user models--descriptions of student's learning styles and preferences. An approach to user modeling that is based on decision tables has numerous advantages compared with traditional manual techniques or methods that rely on rule-based expert systems or neural networks. Decision tables provide a mechanism whereby overwhelming quantities of data can be condensed into an easily interpreted and manipulated form. Compared with conventional rule-based expert systems, decision tables are more amenable to modification. Unlike classification systems based on neural networks, the entries in decision tables are readily available for inspection and manipulation. Decision tables, descriptions of observations of behavior, also provide automatic checks for ambiguity in the tracking data.

Universal New York Health Care. A single-payer strategy linking cost control and universal access.

Now that universal access to health care is back on the governmental agenda, elected officials are faced with the dilemma of expanding our present pluralistic system of numerous private and public payers, with its built-in administrative inefficiencies and inflationary pressures, or scrapping the present system of financing and moving to a tax-based scheme like the Canadian Medicare program, an option fraught with political difficulties. There is, however, a third option. The New York State Department of Health has developed a proposal for universal access--Universal New York Health Care, or UNY-Care--that would retain the existing payers, including employer-based insurance coverage, but combine them in a one-payer framework. Providers would no longer have to interact with the many public and private payers, each with its own rules, criteria, and levels of payment. The single payer would serve as the only payer for most health care services and would also negotiate reimbursement rates. The single-payer framework should bring savings in administrative and billing costs and should move government closer to the goal of buying health care services--getting good value for payment rendered--rather than simply paying bills as they are submitted. Although the single-payer strategy could be implemented at either the state or the federal level, it seems ideal as the principal responsibility of the states in a national plan for universal coverage.

Methods for developing relative need criteria to accompany a health care capital expenditure limit.

In recent years capital spending in the health care industry has escalated tremendously, and most forecasters agree that needs will increase at an even faster rate throughout the 1990s. As a result of this trend, there is a dire need to develop effective and equitable controls on capital spending in health care. One of the capital payment options under consideration is the establishment of a lid on capital expenditures and the concomitant allocation of capital to health care providers whose applications are the most meritorious. The purpose of this article is to present some ideas and methods for the development of a relative need system to accompany a capital expenditure limit and to supplement and expand the absolute need determinations of the typical CON process.