Cancer mortality after radiotherapy for a skin hemangioma during childhood.

International audienceBACKGROUND AND PURPOSE: A cohort study was performed as part of a European Radiation Protection Program to investigate the carcinogenic effect of treatment with ionizing radiation in early childhood. This paper presents mortality after radiotherapy in this cohort. PATIENTS AND METHODS: The cohort comprised 7037 patients under 15 years of age treated for a skin hemangioma between 1940 and 1973 at the Institut Gustave-Roussy, among whom 4940 received radiotherapy. The vital status and causes of death were obtained as well as the mortality rates in the general French population. External and internal analyses were performed. Standardized mortality ratio (SMR) and relative risk (RR) variations according to exposure to radiotherapy or not and the type of treatment were studied. RESULTS: During the 1969-1997 follow-up period, 16 cohort patients died of cancer, 14 after radiotherapy. A non-significant excess of cancer-related mortality was observed for irradiated patients as compared to the general population (SMR=1.53; 95% CI=0.86-2.48). Treatment with (226)Ra seemed to play a significant role (RR=2.53; 95% CI=0.84-7.07) compared to no radiotherapy. CONCLUSION: This study suggests an excess risk of cancer-related mortality in patients treated during early childhood with radiotherapy for skin hemangioma, and especially with (226)Ra. These patients need to be followed up in the future

A Joint Mechanistic Description of Plasma Polymers Synthesized at Low and Atmospheric Pressure

info:eu-repo/semantics/publishe

Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan‐tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey’s height, community wood density and above ground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey’s height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change

Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan-tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change