Clinical characteristics and prognosis of osteosarcoma in young children: a retrospective series of 15 cases

<p>Abstract</p> <p>Background</p> <p>Osteosarcoma is the most common primary bone malignancy in childhood and adolescence. However, it is very rare in children under 5 years of age. Although studies in young children are limited in number, they all underline the high rate of amputation in this population, with conflicting results being recently reported regarding their prognosis.</p> <p>Methods</p> <p>To enhance knowledge on the clinical characteristics and prognosis of osteosarcoma in young children, we reviewed the medical records and histology of all children diagnosed with osteosarcoma before the age of five years and treated in SFCE (Société Française des Cancers et leucémies de l'Enfant) centers between 1980 and 2007.</p> <p>Results</p> <p>Fifteen patients from 7 centers were studied. Long bones were involved in 14 cases. Metastases were present at diagnosis in 40% of cases. The histologic type was osteoblastic in 74% of cases. Two patients had a relevant history. One child developed a second malignancy 13 years after osteosarcoma diagnosis.</p> <p>Thirteen children received preoperative chemotherapy including high-dose methotrexate, but only 36% had a good histologic response. Chemotherapy was well tolerated, apart from a case of severe late convulsive encephalopathy in a one-year-old infant. Limb salvage surgery was performed in six cases, with frequent mechanical and infectious complications and variable functional outcomes.</p> <p>Complete remission was obtained in 12 children, six of whom relapsed. With a median follow-up of 5 years, six patients were alive in remission, seven died of their disease (45%), in a broad range of 2 months to 8 years after diagnosis, two were lost to follow-up.</p> <p>Conclusions</p> <p>Osteosarcoma seems to be more aggressive in children under five years of age, and surgical management remains a challange.</p

Contribution a l'etude de la fissuration dans la glace polycristalline en compression

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

L'homme de l'entre-deux. L'identité brouillée du commissaire de police au XIXe siècle

International audienc

L’homme de l’entre-deux

La littérature, puis le cinéma et la télévision ont fait du commissaire de police contemporain une figure familière. De Maigret à Navarro ou à Julie Lescaut, le personnage s’est en effet imposé comme « la figure nationale qui incarne le mythe de la police française », voire comme l’un des points de ralliement de notre imaginaire social. Phénomène récent, cette large visibilité n’a cependant guère affecté les commissaires des siècles précédents. Alors qu’ils constituent l’un des rouages princi..

"L'âge d'argent"

International audienceEtude historique et littéraire de la période de l'histoire russe appelée ""âge d'argent

FORMES ATYPIQUES D'ATTEINTES CEREBRALES D'ADRENOLEUCODYSTROPHIE EN IRM

PARIS6-Bibl. St Antoine CHU (751122104) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Estimation of Aboveground Oil Palm Biomass in a Mature Plantation in the Congo Basin

Agro-industrial oil palm plantations are becoming increasingly established in the Congo Basin (West Equatorial Africa) for mainly economic reasons. Knowledge of oil palm capacity to sequester carbon requires biomass estimates. This study implemented local and regional methods for estimating palm biomass in a mature plantation, using destructive sampling. Eighteen 35-year-old oil palms with breast height diameters (DBH) between 48 and 58 cm were felled and sectioned in a plantation located in Makouk&eacute;, central Gabon. Field and laboratory measurements determined the biomasses of different tree compartments (fruits, leaflets, petioles, rachises, stems). Fruits and leaflets contributed an average of 6% to total aboveground palm biomass, which petioles accounted for 8%, rachises for 13% and the stem, 73%. The best allometric equation for estimating stem biomass was obtained with a composite variable, formulated as DBH2 &times; stem height, weighted by tissue infra-density. For leaf biomass (fruits + leaflets + petioles + rachises), the equation was of a similar form, but included the leaf number instead of infra-density. The allometric model combining the stem and leaf biomass yielded the best estimates of the total aboveground oil palm biomass (coefficient of determination (r2) = 0.972, p &lt; 0.0001, relative root mean square error (RMSE) = 5%). Yet, the model was difficult to implement in practice, given the limited availability of variables such as the leaf number. The total aboveground biomass could be estimated with comparable results using DBH2 &times; stem height, weighted by the infra-density (r2 = 0.961, p &lt; 0.0001, relative RMSE (%RMSE) = 5.7%). A simpler model excluding infra-density did not severely compromise results (R2 = 0.939, p &lt; 0.0003, %RMSE = 8.2%). We also examined existing allometric models, established elsewhere in the world, for estimating aboveground oil palm biomass in our study area. These models exhibited performances inferior to the best local allometric equations that were developed

Estimation of the total dry aboveground biomass in the tropical forests of Congo Basin using optical, LiDAR, and radar data

In this investigation, optical (SPOT-7 NAOMI), airborne LiDAR, and PolInSAR L-band data, along with forest inventories, were employed to develop models for estimating total dry aboveground biomass (AGB) over the tropical forests in the Congo Basin (Gabon) of Central Africa. Remote sensing-based variables like texture (from SPOT), median canopy height (from LiDAR), and backscattering coefficient along with canopy surface heights (from PolInSAR) were used to estimate the AGB. These variables were used individually (or combined) to develop the AGB models based on the multivariate adaptive regression splines (MARS) approach. Validation indicated that in case of the single variable models, the LiDAR-based model yielded the lowest estimation root-mean-square error (RMSE = 28%). The error decreased further when the median canopy height was combined with the texture or with the radar variables (RMSE <25%). The texture derived from the Fourier transform textural ordination (FOTO) approach was more effective in improving the results as compared to the gray level co-occurrence matrices (GLCM) approach. Model validation indicated that the best performance in AGB estimation was achieved by combining optical, LiDAR, and radar data (R2 = 0.89 and RMSE = 24%)