Completeness of Data Clause Samples

Completeness of Data. A: This piece of work was not anticipated, but it falls into the remit of T1. 3.1. From the cross-SP meeting between ▇▇▇, ▇▇▇, ▇▇▇ and SP6 in the HBP Summit 2014 it was evident that several modelling groups at the cellular (e.g. WP6.4.5), intracellular (e.g. WP6.4.1 and WP6.4.2) and molecular levels (e.g. WP6.

Completeness of Data. The dataset is in line with the anticipated one. The dataset is complete; its quality is expected to increase with time as new structures become available.

Completeness of Data. Although not specifically stated as one or “data production” goals, it must be pointed out a large part of the effort by our group during the Ramp-Up Phase has been invested to testing and developing methods and equipment for efficient and reliable labelling and 3D reconstruction of individual long-range projection neurons across large tissue volumes, potentially the entire brain. Developing these methodologies and workflows is crucial for the future phases of the project. In this regard, we have succeeded in establishing two new protocols for single-cell labelling with high spatial precision based on the electroporation of RNA Sidbis or DNA AAv vectors. A paper reporting the RNA protocol is currently under review in Frontiers in Neuronatomy. In addition, we have labelled a total of 20 (out of 30 planned for M30) cells, of which 11 were found to be of sufficient quality and appropriate location for full 3D reconstructions. During the M1-M30 period a paper has been published (Nakamura et al., 2015) by the laboratory of ▇▇▇▇▇▇▇ ▇▇▇▇▇▇ (Kyoto University) reporting the single cell architecture of thalamocortical projection cells of the lateral posterior complex of rats also using the Sindbis vector. We collaborate with ▇▇▇▇. ▇▇▇▇▇▇’▇ group, and originally obtained from them the vector. Although, because of the species and size difference, the quantitative data from ▇▇▇▇▇▇▇-▇▇▇▇▇▇ rats cannot be used for the HBP atlas and modelling, the study findings validate our approach and provide a framework for reference and interspecies comparison.

Completeness of Data. The delivered dataset meets and exceeds the anticipated one. Instead of a single generic kinetic model, we are proposing three generic models of different complexity. Also, instead of only relying on scarce channel electrophysiological data found in the literature, we have profited from the exhaustive patch-clamp measurements performed at the Brain Mind Institute of the EPFL on all relevant K channels. We can thus provide reliable kinetic models for more channels than initially anticipated. The dataset is complete, but the kinetic models are not fixed in stone and are expected to evolve. Over the last decade, the mechanisms underlying ion channel function have been studied through structural approaches and, unfortunately, kinetic modelling has been mostly abandoned. Our kinetic models are the first to aim at bridging the structural and functional data of K channels.

Completeness of Data. The delivered dataset agrees with the anticipated version. The next stage of work has already been triggered. A new series of acquisition focused on corpus callosum has been performed with ten new subjects on the 7T magnet of Neurospin equipped with a 50mT gradient. This experiment has shown that increasing the number of shells in the QA-space and the sampling of the diffusion time of diffusion-weighted images allows large improvement of the quantification accuracy, which has been proven by comparison with information obtained from post-mortem autopsy. Note that traditional post-mortem strategy is limited to the few specific white matter areas like corpus callosum that can be visualised during dissection. This explains the attractiveness of the diffusion-based strategy, which can directly be compared with 3D-Polarized Light Imaging as obtained in SP2 (see below).

Completeness of Data. We are aware of only one whole-brain dataset (Xue, S et al., 2014) that has been acquired using micro-optical sectioning tomography (MOST) - a modification of knife-edge scanning microscopy (KESM) (Li. A. et al., 2010). We believe that the non-destructive nature of phase-contrast CT and confocal two-photon laser microscopy are clearly preferable over MOST/KESM.

Completeness of Data. Santarus has made available to Norgine at Santarus’ San Diego, California offices, all material regulatory correspondence and clinical study results in its Control for the Currently Approved U.S. Products.

Completeness of Data. We have obtained 3D confocal digital reconstructions of 60 dendrites, including main apical, colateral and basal dendrites from 20 individual identified pyramidal neurons in the hippocampus (n=10) and somatosensory cortex (n=10) together with the distribution of PSD95 puncta in the same stacks of images. We are currently generating the synaptic maps of the 60 dendrites by co-registration of both channels (Alexa and GFP). Unfortunately, we have detected a problem with the data generated with the confocal microscope. The images that were obtained during the last 12 months show a distortion in the z-axis. Image processing to reconstruct dendritic spines is very time consuming because there are not automatic software tools to obtain an accurate 3D reconstruction of the dendritic spine. Thus, the reconstruction of these structures is mainly based on manual tracing using informatic tools. Therefore, it will take longer time than expected to generate the final maps because we have to acquire again the 3D confocal digital reconstructions of 46 dendrites and re-analyse the previous data. In addition to the goal of the generation of synaptic maps on identified neurons, we have developed a new tool called PyramidalExplorer (Toharia et al., 2016) to interactively explore and reveal the detailed organisation of the microanatomy of pyramidal neurons with functionally related models (Figure 9). This tool consists of a set of functionalities that allow possible regional differences in the pyramidal cell architecture to be interactively discovered by combining quantitative morphological information about the structure of the cell with implemented functional models. We are planning to use this tool to analyse the synaptic maps to discover new aspects of the morpho-functional organization of the pyramidal neuron. Graphical user interface (GUI) of PyramidalExplorer showing the cell comparison query result concerning Spine Area, from a pyramidal neuron in a global view (A) and in a zoom in view (B). Values are represented by colour code. Red colours represent highest values whereas blue colours represent the lowest values. White frame in the main window highlights the spine visualized in the Detail viewer widget. Taken from Toharia et al. (Front Neuroanat. 9:159, 2016) As far as we know, this is the only dataset reporting large-scale synaptic maps of individual neurons from intact mouse brain. The technology is now available to be exploited for comprehensive studies on the syn...

Completeness of Data. Dataset generated in T1.2.4 (neocortex) could be considered as the final dataset.