Development of a CO2CO_2 cooling prototype for the CBM Silicon Tracking System

Traumatic brain injury (TBI) frequently occurs during childhood and adolescence with long-term neuropsychological and behavioral effects. Greater personal awareness of injury is associated with better outcomes. However, personal awareness is often assessed using ratings obtained from family members or significant others. Surprisingly, the accuracy of family-ratings compared with self-ratings has not been well studied in the TBI population. Thus, the purpose of this study was to examine self versus family-ratings of frontal dysfunction and secondly, the association between self/family reported frontal dysfunction and measured executive function outcomes. A total of 60 participants, approximately 10 years post-TBI, comprised 3 groups including; moderate/severe TBI (N=26; mean age 22.9, SD=3.0), mild TBI (N=20; mean age, 21.7, SD=2.7), and control (N=14: mean age, 21.6, SD=3.7). Neuropsychological testing was used to obtain domain scores for executive function and working memory/attention for each participant, and nominated family members and participants with TBI were asked to complete the Frontal Systems Behaviour Scale (FrSBe), consisting of three sub-scales; apathy, disinhibition, and executive dysfunction. Using the FrSBe there was no significant difference between the groups in executive function score, but the moderate/severe and mild groups had significantly lower working memory/attention scores compared with the control group (p<0.05). Repeated measures analysis of variance showed higher self-ratings on all sub-scales compared with family in each group (p<0.05). Scores on executive function and working memory/attention domains correlated with self, but not family reported executive dysfunction. Self-rated executive dysfunction explained 36% of the variance in executive function (p<0.001). While agreement between self-rated and family-rated total FrSBe scores was significant in all groups (p<0.001), our results showed that self-ratings were of higher predictive utility for executive functioning compared with family ratings. Further, at 10 years post-TBI, patients show greater awareness of deficits compared with family who rate consistently closer to the normal functioning range

Nemo: a computational tool for analyzing nematode locomotion

The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement. In this paper, we introduce Nemo (nematode movement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification. Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.Comment: 12 pages, 2 figures. accepted by BMC Neuroscience 2007, 8:8

Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain

Background: Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network. Methodology/Principal Findings: Here, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm's locomotion. Conclusions/Significance: The analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological) motifs as long as both wiring and functional information is available

Cosmic ray energy loss in the heliosphere: Direct evidence from electron-capture-decay secondary isotopes

Measurements by the Cosmic Ray Isotope Spectrometer (CRIS) on the Advanced Composition Explorer (ACE) spacecraft provide direct evidence that galactic cosmic rays lose energy as a result of their interactions with magnetic fields expanding with the solar wind. The secondary isotopes ^(49)V and ^(51)Cr can decay to ^(49)Ti and ^(51)V, respectively, only by electron capture. The observed abundances of these isotopes are directly related to the probability of attaching an electron from the interstellar medium; this probability decreases strongly with increasing energy around a few hundred MeV/nucleon. At the highest energies observed by CRIS, electron attachment on these nuclides is very unlikely, and thus ^(49)V and ^(51)Cr are essentially stable. At lower energies, attachment and decay do occur. Comparison of the energy dependence of the daughter/parent ratios ^(49)Ti/^(49)V and ^(51)V/^(51)Cr during solar minimum and solar maximum conditions confirms that increased energy loss occurs during solar maximum. This analysis indicates an increase in the modulation parameter ϕ of about 400 to 700 MV corresponding to an increase in average energy loss for these elements of about 200 to 300 MeV/nucleon

Direct Evidence of Energy-Loss in Electron-Capture-Decay Secondary Isotopes in the Heliosphere

We report direct evidence of the energy loss of galactic cosmic rays as they diffuse in magnetic irregularities expanding with the solar wind. Using the Cosmic Ray Isotope Spectrometer (CRIS) on the Advanced Composition Explorer (ACE), we report on the energy-dependence of the electron-capture decay of the secondary isotopes ^(49)V and ^(51)Cr. At the highest energies observed by CRIS, where electron attachment is unlikely, ^(49)V and ^(51)Cr are essentially stable; at lower energies the timescale for electron attachment is much shorter and substantial decay does occur. Comparing the energy dependence of the daughter/parent ratios ^(49)Ti/^(49)V and ^(51)V/^(51)Cr during periods of solar minimum and maximum demonstrates that the solar modulation parameter φ is about 400 to 700 MV higher during solar maximum than at minimum. Absolute values of φ inferred from these electron-capture-isotope data agree well with values inferred from comparison of the observed elemental energy spectra with model calculations