Rousseau's Child: Preschoolers Expect Strangers to Favor Prosocial Actions

Modern thinking about human nature is notoriously divided between two contradictory notions: The Hobbesian tradition portrays men as driven by selfish desires, while the Rousseauian tradition recognizes altruistic proclivities as truemotivations to cooperate. We tested preschoolers' predictions about the prosocial or antisocial manner in which people would behave toward each other. Four stories were presented to 3- and 4-year-old children. In each story, the protagonists could either cooperate, act in terms of their own interests, or adopt a behavior unrelated to the ongoing scenario. Children as young as 3 years of age expected the protagonists to behave prosocially - and even more so if the protagonists were female. The results suggest that, even at an early age, children are inclined to adopt a "Rousseau-like" stance rather than a "suspicious" or "pessimistic" Hobbesian stance.

ESPEN endorsed recommendations: nutritional therapy in major burns.

BACKGROUND & AIMS: Nutrition therapy is a cornerstone of burn care from the early resuscitation phase until the end of rehabilitation. While several aspects of nutrition therapy are similar in major burns and other critical care conditions, the patho-physiology of burn injury with its major endocrine, inflammatory, metabolic and immune alterations requires some specific nutritional interventions. The present text developed by the French speaking societies, is updated to provide evidenced-based recommendations for clinical practice. METHODS: A group of burn specialists used the GRADE methodology (Grade of Recommendation, Assessment, Development and Evaluation) to evaluate human burn clinical trials between 1979 and 2011. The resulting recommendations, strong suggestions or suggestions were then rated by the non-burn specialized experts according to their agreement (strong, moderate or weak). RESULTS: Eight major recommendations were made. Strong recommendations were made regarding, 1) early enteral feeding, 2) the elevated protein requirements (1.5-2 g/kg in adults, 3 g/kg in children), 3) the limitation of glucose delivery to a maximum of 55% of energy and 5 mg/kg/h associated with moderate blood glucose (target ≤ 8 mmol/l) control by means of continuous infusion, 4) to associated trace element and vitamin substitution early on, and 5) to use non-nutritional strategies to attenuate hypermetabolism by pharmacological (propranolol, oxandrolone) and physical tools (early surgery and thermo-neutral room) during the first weeks after injury. Suggestion were made in absence of indirect calorimetry, to use of the Toronto equation (Schoffield in children) for energy requirement determination (risk of overfeeding), and to maintain fat administration ≤ 30% of total energy delivery. CONCLUSION: The nutritional therapy in major burns has evidence-based specificities that contribute to improve clinical outcome.

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.