The neural correlates of road sign knowledge and route learning in semantic dementia and Alzheimer's disease.

BACKGROUND: Although there is a growing body of research on driving and Alzheimer's disease (AD), focal dementias have been understudied. Moreover, driving has never been explored in semantic dementia (SD). METHODS: An experimental battery exploring road sign knowledge and route learning was applied to patients with SD and AD selected in the early-moderate stage of disease and to a group of healthy participants. Neuropsychological data were correlated to cerebral hypometabolism distribution, investigated by means of positron emission tomography. RESULTS: The two dementias showed opposite profiles. Patients with SD showed poor road sign knowledge and normal performance in route learning. By contrast, patients with AD showed low performance in route learning test with preservation of semantic knowledge of road signs. In SD, there was a correlation of semantic knowledge impairment with hypometabolism in the left temporolateral cortex. No correlation between the AD region of interests (ROIs) and the relevant behavioural indices was found, while in the whole-brain analysis there was a significant correlation between route learning and the superior frontal gyrus. DISCUSSION AND CONCLUSIONS: For the first time, driving skills were explored in SD, and it is showed a differential profile from the one detected in AD. We demonstrate that the left anterior temporal cortex is implicated in road sign knowledge, while a distributed cortical network, including the frontal cortex, is likely to process route learning.

Molecular fingerprinting of principal neurons in the rodent hippocampus: A neuroinformatics approach.

Neurons are often classified by their morphological and molecular properties. The online knowledge base Hippocampome.org primarily defines neuron types from the rodent hippocampal formation based on their main neurotransmitter (glutamate or GABA) and the spatial distributions of their axons and dendrites. For each neuron type, this open-access resource reports any and all published information regarding the presence or absence of known molecular markers, including calcium-binding proteins, neuropeptides, receptors, channels, transcription factors, and other molecules of biomedical relevance. The resulting chemical profile is relatively sparse: even for the best studied neuron types, the expression or lack thereof of fewer than 70 molecules has been firmly established to date. The mouse genome-wide in situ hybridization mapping of the Allen Brain Atlas provides a wealth of data that, when appropriately analyzed, can substantially augment the molecular marker knowledge in Hippocampome.org. Here we focus on the principal cell layers of dentate gyrus (DG), CA3, CA2, and CA1, which together contain approximately 90% of hippocampal neurons. These four anatomical parcels are densely packed with somata of mostly excitatory projection neurons. Thus, gene expression data for those layers can be justifiably linked to the respective principal neuron types: granule cells in DG and pyramidal cells in CA3, CA2, and CA1. In order to enable consistent interpretation across genes and regions, we screened the whole-genome dataset against known molecular markers of those neuron types. The resulting threshold values allow over 6000 very-high confidence (>99.5%) expressed/not-expressed assignments, expanding the biochemical information content of Hippocampome.org more than five-fold. Many of these newly identified molecular markers are potential pharmacological targets for major neurological and psychiatric conditions. Furthermore, our approach yields reasonable expression/non-expression estimates for every single gene in each of these four neuron types with >90% average confidence, providing a considerably complete genetic characterization of hippocampal principal neurons.

Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties.

Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures. Mining this knowledge from peer-reviewed reports reveals the troubling extent of terminological ambiguity and undefined terms. Examples span simple cases of using multiple synonyms and acronyms for the same molecular biomarkers (or other property) to more complex cases of neuronal naming. New publications often use different terms without mapping them to previous terms. As a result, neurons of the same type are assigned disparate names, while neurons of different types are bestowed the same name. Furthermore, non-unique properties are frequently used as names, and several neuron types are not named at all. In order to alleviate this nomenclature confusion regarding hippocampal neuron types and properties, we introduce a new functionality of Hippocampome.org: a fully searchable, curated catalog of human and machine-readable definitions, each linked to the corresponding neuron and property terms. Furthermore, we extend our robust approach to providing each neuron type with an informative name and unique identifier by mapping all encountered synonyms and homonyms.

Stereospecific and competitive binding of drugs to human serum albumin: a difference circular dichroism approach.

Simultaneous binding of two drugs to human serum albumin (HSA) was investigated by difference circular dichroism (delta CD) spectroscopy. Phenylbutazone and diazepam were chosen as specific markers for binding areas I (cumarines) and II (indoles), respectively, and their stereospecific interactions with protein were selectively characterized. Displacers were drugs known to specifically bind to areas I (salicylate) and II (racemic ibuprofen). The results indicate two different interaction mechanisms: a direct competition one (diazepam-ibuprofen and phenylbutazone-salicylate) and an indirect competition one (diazepam-salicylate and phenylbutazone-ibuprofen). The two major binding areas on HSA are distinct, but not independent, entities. Finally, the dissociation constants of marker ligands and competitors complexed to HSA were determined by quantitative analysis of CD data.

Computer generation and quantitative morphometric analysis of virtual neurons.

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

The binding of 5-fluorouracil to native and modified human serum albumin: UV, CD, and 1H and 19F NMR investigation.

5-Fluorouracil (FU) is an important and widely used antineoplastic drug that is carried in the serum by plasma proteins. Protein binding studies of this drug to human serum albumin (HSA) have been carried out by several spectroscopic techniques. Difference circular dichroism and UV studies provided information on the class of binding sites involved in the interaction. In particular, displacement experiments showed that FU has at least one secondary binding site in the coumarin binding area, but does not interact with the benzodiazepine binding area. Binding was also investigated by difference 1H NMR and by measuring the increase in the 19F NMR signal of FU when bound to HSA. Finally, evidence was obtained that chemical acetylation of Lys199 results in a decreased apparent binding affinity constant (nK) for FU. Such a modification is induced under physiological conditions by aspirin.

[Lumbar extradural Brucella abscess without spondylitis. Apropos of a case]. / Abcès extradural lombaire mélitococcique sans spondylite. A propos d'un cas.

One case of lumbar extradural abscess of brucellar etiology without spondylodiscitis is described. The recovery was obtained only with antibiotic therapy.

Non-homogeneous stereological properties of the rat hippocampus from high-resolution 3D serial reconstruction of thin histological sections.

Integrating hippocampal anatomy from neuronal dendrites to whole system may help elucidate its relation to function. Toward this aim, we digitally traced the cytoarchitectonic boundaries of the dentate gyrus (DG) and areas CA3/CA1 throughout their entire longitudinal extent from high-resolution images of thin cryostatic sections of adult rat brain. The 3D computational reconstruction identified all isotropic 16 µm voxels with appropriate subregions and layers (http://krasnow1.gmu.edu/cn3/hippocampus3d). Overall, DG, CA3, and CA1 occupied comparable volumes (15.3, 12.2, and 18.8 mm(3), respectively), but displayed substantial rostrocaudal volumetric gradients: CA1 made up more than half of the posterior hippocampus, whereas CA3 and DG were more prominent in the anterior regions. The CA3/CA1 ratio increased from ∼0.4 to ∼1 septo-temporally because of a specific change in stratum radiatum volume. Next we virtually embedded 1.8 million neuronal morphologies stochastically resampled from 244 digital reconstructions, emulating the dense packing of granular and pyramidal layers, and appropriately orienting the principal dendritic axes relative to local curvature. The resulting neuropil occupancy reproduced recent electron microscopy data measured in a restricted location. Extension of this analysis across each layer and subregion over the whole hippocampus revealed highly non-homogeneous dendritic density. In CA1, dendritic occupancy was >60% higher temporally than septally (0.46 vs. 0.28, s.e.m. ∼0.05). CA3 values varied both across subfields (from 0.35 in CA3b/CA3c to 0.50 in CA3a) and layers (0.48, 0.34, and 0.27 in oriens, radiatum, and lacunosum-moleculare, respectively). Dendritic occupancy was substantially lower in DG, especially in the supra-pyramidal blade (0.18). The computed probability of dendrodendritic collision significantly correlated with expression of the membrane repulsion signal Down syndrome cell adhesion molecule (DSCAM). These heterogeneous stereological properties reflect and complement the non-uniform molecular composition, circuit connectivity, and computational function of the hippocampus across its transverse, longitudinal, and laminar organization.

The membrane response of hippocampal CA3b pyramidal neurons near rest: Heterogeneity of passive properties and the contribution of hyperpolarization-activated currents.

Pyramidal neurons in the CA3 region of the hippocampal formation integrate synaptic information arriving in the dendrites within discrete laminar regions. At potentials near or below the resting potential integration of synaptic signals is most affected by the passive properties of the cell and hyperpolarization-activated currents (I(h)). Here we focused specifically on a subset of neurons within the CA3b subregion of the rat hippocampus in order to better understand their membrane response within subthreshold voltage ranges. Using a combined experimental and computational approach we found that the passive properties of these neurons varied up to fivefold between cells. Likewise, there was a large variance in the expression of I(h) channels. However, the contribution of I(h) was minimal at resting potentials endowing the membrane with an apparent linear response to somatic current injection within +/-10 mV. Unlike in CA1 pyramidal neurons, however, I(h) activation was not potentiated in an activity-dependent manner. Computer modeling, based on a combination of voltage- and current-clamp data, suggested that an increasing density of these channels with distance from the soma, compared with a uniform distribution, would have no significant effect on the general properties of the cell because of their relatively lower expression. Nonetheless, temporal summation of excitatory inputs was affected by the presence of I(h) in the dendrites in a frequency- and distance-dependent fashion.