Barthelemy Aneau: A Study in Humanism

The literary activity of Aneau really begins with his election to the principalship of the Collège de la Trinité. Before 1540, literature was for him mainly a subject for the class-room. The few poems that he composed were either a diversion or intended to inspire his pupils. But after his election to this high position, he enjoyed greater influence in the social life of the city. The successful production of the Mystère de la nativité had indeed made of him a well-known local character; but now it devolved upon him to take part in all the important civic functions and write epigrams on contemporary events. He was placed on reception committees, and was usually requested, when the city welcomed a notable, to write a poem or play commemorating the occasion

Brain maturation of newborns and infants

pre-printRecently, imaging studies of early human development have received more attention, as improved modeling methods might lead to a clearer understanding of the origin, timing, and nature of differences in neurodevelopmental disorders. Non-invasivemagnetic resonance imaging (MRI) can provide three-dimensional images of the infant brain in less than 20 minutes, with unprecedented anatomical details and contrast of brain anatomy cortical and subcortical structures and brain connectivity.1,2,3 Repeating MRI at different stages of development, e.g., in yearly intervals starting after birth, gives scientists the opportunity to study the trajectory of brain growth and compare individual growth trajectories to normative models. These comparisons become highly relevant in personalized medicine, where early diagnosis is a critical juncture for timing and therapy types

Prenatal mild ventriculomegaly predicts abnormal development of the neonatal brain

pre-printBackground: Many psychiatric and neurodevelopmental disorders are associated with mild enlargement of the lateral ventricles thought to have origins in prenatal brain development. Little is known about development of the lateral ventricles and the relationship of prenatal lateral ventricle enlargement with postnatal brain development. Methods: We performed a neonatal MRI on 34 children with isolated mild ventriculomegaly (MVM, width of the atrium of the lateral ventricle ≥ 1.0 cm) on prenatal ultrasound and 34 age and gender matched controls with normal prenatal ventricle size. Lateral ventricle and cortical gray and white matter volumes were assessed. Fractional anisotropy (FA) and mean diffusivity (MD) in corpus callosum and cortico-spinal white matter tracts were determined obtained using quantitative tractography . Results: Neonates with prenatal MVM had significantly larger lateral ventricle volumes than matched controls (286.4%; p < 0.0001). Neonates with MVM also had significantly larger intracranial volumes (ICV; 7.1%, p = 0.0063) and cortical gray matter volumes (10.9%, p = 0.0004) compared to controls. DTI tractography revealed a significantly greater MD in the corpus callosum and cortico-spinal tracts, while FA was significantly smaller in several white matter tract regions. Conclusions: Prenatal enlargement of the lateral ventricle is associated with enlargement of the lateral ventricles after birth, as well as greater gray matter volumes and delayed or abnormal maturation of white matter. It is suggested that prenatal ventricle volume is an early structural marker of altered development of the cerebral cortex and may be marker of risk for neuropsychiatric disorders associated with ventricle enlargement

Regional gray matter growth, sexual dimorphism, and cerebral asymmetry in the Neonatal Brain

journal articleAlthough there has been recent interest in the study of childhood and adolescent brain development, very little is known about normal brain development in the first few months of life. In older children, there are regional differences in cortical gray matter development, whereas cortical gray and white matter growth after birth has not been studied to a great extent. The adult human brain is also characterized by cerebral asymmetries and sexual dimorphisms, although very little is known about how these asymmetries and dimorphisms develop. We used magnetic resonance imaging and an automatic segmentation methodology to study brain structure in 74 neonates in the first few weeks after birth. We found robust cortical gray matter growth compared with white matter growth, with occipital regions growing much faster than prefrontal regions. Sexual dimorphism is present at birth, with males having larger total brain cortical gray and white matter volumes than females. In contrast to adults and older children, the left hemisphere is larger than the right hemisphere, and the normal pattern of fronto-occipital asymmetry described in older children and adults is not present. Regional differences in cortical gray matter growth are likely related to differential maturation of sensory and motor systems compared with prefrontal executive function after birth. These findings also indicate that whereas some adult patterns of sexual dimorphism and cerebral asymmetries are present at birth, others develop after birth

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Twin-singleton developmental study of brain white matter anatomy: Twin-Singleton Developmental Study of Brain White Matter Anatomy

Twin studies provide valuable insights into the analysis of genetic and environmental factors influencing human brain development. However, these findings may not generalize to singletons due to differences in pre- and postnatal environments. One would expect the effect of these differences to be greater during the early years of life. To address this concern, we compare longitudinal diffusion data of white matter regions for 26 singletons and 76 twins (monozygotic and dizygotic) from birth to 2 years of age. We use nonlinear mixed effect modeling where the temporal changes in the diffusion parameters are described by the Gompertz function. The Gompertz function describes growth trajectory in terms of intuitive parameters: asymptote, delay, and speed. We analyzed fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) for 21 regions of interest (ROIs). These ROIs included areas in the association, projection, and commissural fiber tracts. We did not find any differences in the diffusion parameters between monozygotic and dizygotic twins. In addition, FA and RD showed no developmental differences between singletons and twins for the regions analyzed. However, the delay parameter of the Gompertz function of AD for the anterior limb of the internal capsule and anterior corona radiata was significantly different between singletons and twins. Further analysis indicated that the differences are small, and twins “catch up” by the first few months of life. These results suggest that the effects of differences of pre- and postnatal environments between twins and singletons are minimal on white matter development and disappear early in life

Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs

Deformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. Often it takes a significant amount of computation time and thus becomes infeasible for practical purposes. In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. We show results on the registrations of neonatal to 2-year old infant MRIs. Quantitative validation demonstrates that our proposed method generates registrations that better maintain the consistency of anatomical structures over time and provides transformations that better preserve structures undergoing large deformations than transformations obtained by standard intensity-only registration. We also achieve the speedup of three orders of magnitudes compared to a CPU reference implementation, making it possible to use the technique in time-critical applications

Electrochemical Investigation of Azurin Thermodynamic and Adsorption Properties at Monolayer-Protected Cluster Film Assemblies – Evidence for a More Homogeneous Adsorption Interface

Thermodynamic and adsorption properties of protein monolayer electrochemistry (PME) are examined for Pseudomonas aeruginosa azurin (AZ) immobilized at an electrode modified with a networked film of monolayer-protected clusters (MPCs) to assess if nanoparticle films of this nature offer a more homogeneous adsorption interface compared to traditional self-assembled monolayer (SAM) modified electrodes. Specifically, electrochemistry is used to assess properties of surface coverage, formal potential, peak broadening, and electron transfer (ET) kinetics as a function of film thickness. The modification of a surface with dithiol-linked films of MPCs (Au225C675) provides a more uniform binding interface for AZ that results in voltammetry with less peak broadening (mV) compared to SAMs (\u3e120–130 mV). Improved homogeneity of the MPC interface for protein adsorption is confirmed by atomic force microscopy imaging that shows uniform coverage of the gold substrate topography and by electrochemical analysis of film properties during systematic desorption of AZ, which indicates a more homogeneous population of adsorbed protein at MPC films. These results suggest MPC film assemblies may be used in PME to provide greater molecular level control of the protein adsorption interface, a development with applications for strategies to study biological ET processes as well as the advancement of biosensor technologies

Group analysis of DTI fiber tract statistics with application to neurodevelopment

Diffusion tensor imaging (DTI) provides a unique source of information about the underlying tissue structure of brain white matter in vivo including both the geometry of major fiber bundles as well as quantitative information about tissue properties represented by derived tensor measures. This paper presents a method for statistical comparison of fiber bundle diffusion properties between populations of diffusion tensor images. Unbiased diffeomorphic atlas building is used to compute a normalized coordinate system for populations of diffusion images. The diffeomorphic transformations between each subject and the atlas provide spatial normalization for the comparison of tract statistics. Diffusion properties, such as fractional anisotropy (FA) and tensor norm, along fiber tracts are modeled as multivariate functions of arc length. Hypothesis testing is performed non-parametrically using permutation testing based on the Hotelling T2 statistic. The linear discriminant embedded in the T2 metric provides an intuitive, localized interpretation of detected differences. The proposed methodology was tested on two clinical studies of neurodevelopment. In a study of one and two year old subjects, a significant increase in FA and a correlated decrease in Frobenius norm was found in several tracts. Significant differences in neonates were found in the splenium tract between controls and subjects with isolated mild ventriculomegaly (MVM) demonstrating the potential of this method for clinical studies

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction☆

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome