Effect of Health-Promoting Agents on Exclusion-Zone Size.

It is now well-confirmed that hydrophilic surfaces including those within the cell generate structural changes in water. This interfacial water is ordered and acquires features different from the bulk. Amongst those features is the exclusion of colloidal and molecular solutes from extensive regions next to the hydrophilic surface, thereby earning it the label of "exclusion zone" (EZ) water. The transition of ordered EZ water to bulk serves as an important trigger of many cellular physiological functions, and in turn cellular health. We tested physiological doses of half a dozen agents generally identified to restore or build health on the extent to which they build EZs. All agents known to enhance biological function resulted in EZ expansion. On the other hand, the weed killer, glyphosate, considerably diminished EZ size. While the expansion effect of the health-promoting agents was observed over a wide range of concentrations, excessive doses ultimately reduced EZ size. We hypothesize that EZ buildup may be a mechanistic feature underlying many health-promoting agents, while agents that impair health may act by diminishing the amount of EZ water.

Within-microenvironment exposure to particulate matter and health effects in children with asthma: a pilot study utilizing real-time personal monitoring with GPS interface.

BACKGROUND: Most particulate matter (PM) and health studies in children with asthma use exposures averaged over the course of a day and do not take into account spatial/temporal variability that presumably occurs as children move from home, into transit and then school microenvironments. The objectives of this work were to identify increases in morning PM exposure occurring within home, transit and school microenvironments and determine their associations with asthma-related inflammation and rescue medication use. METHODS: In 2007-2008, thirty Denver-area schoolchildren with asthma performed personal PM exposure monitoring using a real-time sensor integrated with a geographic information system (GIS) to apportion exposures to home, transit and school microenvironments. Concurrently, daily monitoring of the airway inflammatory biomarker urinary leukotriene E4 (uLTE4) and albuterol usage was performed. RESULTS: Mean PM exposures each morning were relatively well correlated between microenvironments for subject samples (0.3 < r < 0.8), thus limiting use of this exposure metric to attribute health effects to PM exposure in specific microenvironments. Within-microenvironment increases in exposure, such as would be characterized by one or a series of transient spikes or a sustained increase in concentration (exposure event), however, were not strongly correlated between microenvironments (|r| < 0.25). On days when children were exposed to a ≥ 5µg/m3 exposure event during transit, they demonstrated a 24.0 % increase in uLTE4 (95 % CI: 1.5 %, 51.5 %) and a 9.7 % (-5.9 %, 27.9 %) increase in albuterol usage compared to days without transit exposure events. Associations between exposure events and health outcomes in home and school microenvironments tended to be positive as well, but weaker than for transit. CONCLUSIONS: School children with asthma moving across morning microenvironments experience spatially heterogeneous PM exposures with potentially varying health effects.

Development of a method for personal, spatiotemporal exposure assessment.

This work describes the development and evaluation of a high resolution, space and time-referenced sampling method for personal exposure assessment to airborne particulate matter (PM). This method integrates continuous measures of personal PM levels with the corresponding location-activity (i.e. work/school, home, transit) of the subject. Monitoring equipment include a small, portable global positioning system (GPS) receiver, a miniature aerosol nephelometer, and an ambient temperature monitor to estimate the location, time, and magnitude of personal exposure to particulate matter air pollution. Precision and accuracy of each component, as well as the integrated method performance were tested in a combination of laboratory and field tests. Spatial data was apportioned into pre-determined location-activity categories (i.e. work/school, home, transit) with a simple, temporospatially-based algorithm. The apportioning algorithm was extremely effective with an overall accuracy of 99.6%. This method allows examination of an individual's estimated exposure through space and time, which may provide new insights into exposure-activity relationships not possible with traditional exposure assessment techniques (i.e., time-integrated, filter-based measurements). Furthermore, the method is applicable to any contaminant or stressor that can be measured on an individual with a direct-reading sensor.