Temporal evolution of strut light intensity after implantation of bioresorbable polymeric intracoronary scaffolds in the ABSORB cohort B trial-an application of a new quantitative method based on optical coherence tomography.

BACKGROUND Quantitative light intensity analysis of the strut core by optical coherence tomography (OCT) may enable assessment of changes in the light reflectivity of the bioresorbable polymeric scaffold from polymer to provisional matrix and connective tissues, with full disappearance and integration of the scaffold into the vessel wall. The aim of this report was to describe the methodology and to apply it to serial human OCT images post procedure and at 6, 12, 24 and 36 months in the ABSORB cohort B trial. METHODS AND RESULTS In serial frequency-domain OCT pullbacks, corresponding struts at different time points were identified by 3-dimensional foldout view. The peak and median values of light intensity were measured in the strut core by dedicated software. A total of 303 corresponding struts were serially analyzed at 3 time points. In the sequential analysis, peak light intensity increased gradually in the first 24 months after implantation and reached a plateau (relative difference with respect to baseline [%Dif]: 61.4% at 12 months, 115.0% at 24 months, 110.7% at 36 months), while the median intensity kept increasing at 36 months (%Dif: 14.3% at 12 months, 75.0% at 24 months, 93.1% at 36 months). CONCLUSIONS Quantitative light intensity analysis by OCT was capable of detecting subtle changes in the bioresorbable strut appearance over time, and could be used to monitor the bioresorption and integration process of polylactide struts.

Light intensity selectively influences the distribution and further redistribution of macro- and micronutrients in hydroponically grown wheat ( Triticum aestivum L.)

Investigations were focused on light effects on allocation of root-borne macronutrients (calcium, magnesium and potassium) and micronutrients (iron, manganese, zinc and copper) in roots, shoots and harvested grains of wheat (Triticum aestivum L.). Plants were exposed to low (100 μmol photons m−2 s−1) or high light (380 μmol photons m−2 s−1). High light stimulated both root and shoot growth. While the total contents per plant of some nutrients were markedly higher (calcium and potassium) or lower (copper) under high light, no major differences were observed for other nutrients. The distribution of nutrients and the further redistribution within the shoot were influenced by the light intensity in an element-specific manner. Nutrients were selectively directed to the leaves of the main shoot (low light) or to the tillers (high light). The quality of the harvested grains was also affected by the light intensity.

Use of light intensity, temperature, and humidity to verify exposure location

Research studies on the association between exposures to air contaminants and disease frequently use worn dosimeters to measure the concentration of the contaminant of interest. But investigation of exposure determinants requires additional knowledge beyond concentration, i.e., knowledge about personal activity such as whether the exposure occurred in a building or outdoors. Current studies frequently depend upon manual activity logging to record location. This study's purpose was to evaluate the use of a worn data logger recording three environmental parameters—temperature, humidity, and light intensity—as well as time of day, to determine indoor or outdoor location, with an ultimate aim of eliminating the need to manually log location or at least providing a method to verify such logs. For this study, data collection was limited to a single geographical area (Houston, Texas metropolitan area) during a single season (winter) using a HOBO H8 four-channel data logger. Data for development of a Location Model were collected using the logger for deliberate sampling of programmed activities in outdoor, building, and vehicle locations at various times of day. The Model was developed by analyzing the distributions of environmental parameters by location and time to establish a prioritized set of cut points for assessing locations. The final Model consisted of four "processors" that varied these priorities and cut points. Data to evaluate the Model were collected by wearing the logger during "typical days" while maintaining a location log. The Model was tested by feeding the typical day data into each processor and generating assessed locations for each record. These assessed locations were then compared with true locations recorded in the manual log to determine accurate versus erroneous assessments. The utility of each processor was evaluated by calculating overall error rates across all times of day, and calculating individual error rates by time of day. Unfortunately, the error rates were large, such that there would be no benefit in using the Model. Another analysis in which assessed locations were classified as either indoor (including both building and vehicle) or outdoor yielded slightly lower error rates that still precluded any benefit of the Model's use.^