Normobaric hyperoxia--induced improvement in cerebral metabolism and reduction in intracranial pressure in patients with severe head injury: a prospective historical cohort-matched study

OBJECT: The effect of normobaric hyperoxia (fraction of inspired O2 [FIO2] concentration 100%) in the treatment of patients with traumatic brain injury (TBI) remains controversial. The aim of this study was to investigate the effects of normobaric hyperoxia on five cerebral metabolic indices, which have putative prognostic significance following TBI in humans. METHODS: At two independent neurointensive care units, the authors performed a prospective study of 52 patients with severe TBI who were treated for 24 hours with 100% FIO2, starting within 6 hours of admission. Data for these patients were compared with data for a cohort of 112 patients who were treated in the past; patients in the historical control group matched the patients in our study according to their Glasgow Coma Scale scores after resuscitation and their intracranial pressure within the first 8 hours after admission. Patients were monitored with the aid of intracerebral microdialysis and tissue O2 probes. Normobaric hyperoxia treatment resulted in a significant improvement in biochemical markers in the brain compared with the baseline measures for patients treated in our study (patients acting as their own controls) and also compared with findings from the historical control group. In the dialysate the glucose levels increased (369.02 +/- 20.1 micromol/L in the control group and 466.9 +/- 20.39 micromol/L in the 100% O2 group, p = 0.001), whereas the glutamate and lactate levels significantly decreased (p < 0.005). There were also reductions in the lactate/glucose and lactate/pyruvate ratios. Intracranial pressure in the treatment group was reduced significantly both during and after hyperoxia treatment compared with the control groups (15.03 +/- 0.8 mm Hg in the control group and 12.13 +/- 0.75 mm Hg in the 100% O2 group, p < 0.005) with no changes in cerebral perfusion pressure. Outcomes of the patients in the treatment group improved. CONCLUSIONS: The results of the study support the hypothesis that normobaric hyperoxia in patients with severe TBI improves the indices of brain oxidative metabolism. Based on these data further mechanistic studies and a prospective randomized controlled trial are warranted.

Irradiation of intracerebral 9L gliosarcoma by a single array of microplanar x-ray beams from a synchrotron: balance between curing and sparing

The purpose of this work was the understanding of microbeam radiation therapy at the ESRF in order to find the best compromise between curing of tumors and sparing of normal tissues, to obtain a better understanding of survival curves and to report its efficiency. This method uses synchrotron-generated x-ray microbeams. Rats were implanted with 9L gliosarcomas and the tumors were diagnosed by MRI. They were irradiated 14 days after implantation by arrays of 25 microm wide microbeams in unidirectional mode, with a skin entrance dose of 625 Gy. The effect of using 200 or 100 microm center-to-center spacing between the microbeams was compared. The median survival time (post-implantation) was 40 and 67 days at 200 and 100 microm spacing, respectively. However, 72% of rats irradiated at 100 microm spacing showed abnormal clinical signs and weight patterns, whereas only 12% of rats were affected at 200 microm spacing. In parallel, histological lesions of the normal brain were found in the 100 microm series only. Although the increase in lifespan was equal to 273% and 102% for the 100 and 200 microm series, respectively, the 200 microm spacing protocol provides a better sparing of healthy tissue and may prove useful in combination with other radiation modalities or additional drugs.

Statistical analysis of personal radiofrequency electromagnetic field measurements with nondetects

Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radiofrequency electromagnetic field (RF-EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount of personal exposure data, which can be obtained for several RF-EMF sources. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression on order statistics) method, summary statistics can be calculated by fitting an assumed distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust ROS with a naïve approach, where values below the detection limit were replaced by the value of the detection limit. For the total RF-EMF exposure, differences between the naïve approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF-EMF sources were considerably overestimated with the naïve approach. This results in an underestimation of the exposure range in the population, which may bias the evaluation of potential exposure-response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based on a naïve approach. Nevertheless, estimates of source-specific medians or even lower percentiles depend on the assumed data distribution and should be considered with caution.

Temporal and spatial variability of personal exposure to radio frequency electromagnetic fields

BACKGROUND: Little is known about the population's exposure to radio frequency electromagnetic fields (RF-EMF) in industrialized countries. OBJECTIVES: To examine levels of exposure and the importance of different RF-EMF sources and settings in a sample of volunteers living in a Swiss city. METHODS: RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured with personal exposure meters (exposimeters). Participants carried an exposimeter for 1 week (two separate weeks in 32 participants) and completed an activity diary. Mean values were calculated using the robust regression on order statistics (ROS) method. RESULTS: Mean weekly exposure to all RF-EMF sources was 0.13 mW/m(2) (0.22 V/m) (range of individual means 0.014-0.881 mW/m(2)). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning a DECT phone (total mean 0.15 mW/m(2)) or mobile phone (0.14 mW/m(2)) were exposed more than those not owning a DECT or mobile phone (0.10 mW/m(2)). Mean values were highest in trains (1.16 mW/m(2)), airports (0.74 mW/m(2)) and tramways or buses (0.36 mW/m(2)), and higher during daytime (0.16 mW/m(2)) than nighttime (0.08 mW/m(2)). The Spearman correlation coefficient between mean exposure in the first and second week was 0.61. CONCLUSIONS: Exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland.

A prediction model for personal radio frequency electromagnetic field exposure

Radio frequency electromagnetic fields (RF-EMF) in our daily life are caused by numerous sources such as fixed site transmitters (e.g. mobile phone base stations) or indoor devices (e.g. cordless phones). The objective of this study was to develop a prediction model which can be used to predict mean RF-EMF exposure from different sources for a large study population in epidemiological research. We collected personal RF-EMF exposure measurements of 166 volunteers from Basel, Switzerland, by means of portable exposure meters, which were carried during one week. For a validation study we repeated exposure measurements of 31 study participants 21 weeks after the measurements of the first week on average. These second measurements were not used for the model development. We used two data sources as exposure predictors: 1) a questionnaire on potentially exposure relevant characteristics and behaviors and 2) modeled RF-EMF from fixed site transmitters (mobile phone base stations, broadcast transmitters) at the participants' place of residence using a geospatial propagation model. Relevant exposure predictors, which were identified by means of multiple regression analysis, were the modeled RF-EMF at the participants' home from the propagation model, housing characteristics, ownership of communication devices (wireless LAN, mobile and cordless phones) and behavioral aspects such as amount of time spent in public transports. The proportion of variance explained (R2) by the final model was 0.52. The analysis of the agreement between calculated and measured RF-EMF showed a sensitivity of 0.56 and a specificity of 0.95 (cut-off: 90th percentile). In the validation study, the sensitivity and specificity of the model were 0.67 and 0.96, respectively. We could demonstrate that it is feasible to model personal RF-EMF exposure. Most importantly, our validation study suggests that the model can be used to assess average exposure over several months.