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.

RNA interference-mediated c-MYC inhibition prevents cell growth and decreases sensitivity to radio- and chemotherapy in childhood medulloblastoma cells

BACKGROUND: With current treatment strategies, nearly half of all medulloblastoma (MB) patients die from progressive tumors. Accordingly, the identification of novel therapeutic strategies remains a major goal. Deregulation of c-MYC is evident in numerous human cancers. In MB, over-expression of c-MYC has been shown to cause anaplasia and correlate with unfavorable prognosis. METHODS: To study the role of c-MYC in MB biology, we down-regulated c-MYC expression by using small interfering RNA (siRNA) and investigated changes in cellular proliferation, cell cycle analysis, apoptosis, telomere maintenance, and response to ionizing radiation (IR) and chemotherapeutics in a representative panel of human MB cell lines expressing different levels of c-MYC (DAOY wild-type, DAOY transfected with the empty vector, DAOY transfected with c-MYC, D341, and D425). RESULTS: siRNA-mediated c-MYC down-regulation resulted in an inhibition of cellular proliferation and clonogenic growth, inhibition of G1-S phase cell cycle progression, and a decrease in human telomerase reverse transcriptase (hTERT) expression and telomerase activity. On the other hand, down-regulation of c-MYC reduced apoptosis and decreased the sensitivity of human MB cells to IR, cisplatin, and etoposide. This effect was more pronounced in DAOY cells expressing high levels of c-MYC when compared with DAOY wild-type or DAOY cells transfected with the empty vector. CONCLUSION: In human MB cells, in addition to its roles in growth and proliferation, c-MYC is also a potent inducer of apoptosis. Therefore, targeting c-MYC might be of therapeutic benefit when used sequentially with chemo- and radiotherapy rather than concomitantly.

Real-Time Passive Capturing of the GSM Radio

This paper addresses the problem of service development based on GSM handset signaling. The aim is to achieve this goal without the participation of the users, which requires the use of a passive GSM receiver on the uplink. Since no tool for GSM uplink capturing was available, we developed a new method that can synchronize to multiple mobile devices by simply overhearing traffic between them and the network. Our work includes the implementation of modules for signal recovery, message reconstruction and parsing. The method has been validated against a benchmark solution on GSM downlink and independently evaluated on uplink channels. Initial evaluations show up to 99% success rate in message decoding, which is a very promising result. Moreover, we conducted measurements that reveal insights on the impact of signal power on the capturing performance and investigate possible reactive measures.

Exposure to Radio-Frequency Electromagnetic Fields From Broadcast Transmitters and Risk of Childhood Cancer: A Census-based Cohort Study

We investigated the association between exposure to radio-frequency electromagnetic fields (RF-EMFs) from broadcast transmitters and childhood cancer. First, we conducted a time-to-event analysis including children under age 16 years living in Switzerland on December 5, 2000. Follow-up lasted until December 31, 2008. Second, all children living in Switzerland for some time between 1985 and 2008 were included in an incidence density cohort. RF-EMF exposure from broadcast transmitters was modeled. Based on 997 cancer cases, adjusted hazard ratios in the time-to-event analysis for the highest exposure category (>0.2 V/m) as compared with the reference category (<0.05 V/m) were 1.03 (95% confidence interval (CI): 0.74, 1.43) for all cancers, 0.55 (95% CI: 0.26, 1.19) for childhood leukemia, and 1.68 (95% CI: 0.98, 2.91) for childhood central nervous system (CNS) tumors. Results of the incidence density analysis, based on 4,246 cancer cases, were similar for all types of cancer and leukemia but did not indicate a CNS tumor risk (incidence rate ratio = 1.03, 95% CI: 0.73, 1.46). This large census-based cohort study did not suggest an association between predicted RF-EMF exposure from broadcasting and childhood leukemia. Results for CNS tumors were less consistent, but the most comprehensive analysis did not suggest an association.