Parametric analysis of the biomechanical response of head subjected to the primary blast loading – a data mining approach

Traumatic brain injury due to primary blast loading has become a signature injury in recent military conflicts and terrorist activities. Extensive experimental and computational investigations have been conducted to study the interrelationships between intracranial pressure response and intrinsic or ‘input’ parameters such as the head geometry and loading conditions. However, these relationships are very complicated and are usually implicit and ‘hidden’ in a large amount of simulation/test data. In this study, a data mining method is proposed to explore such underlying information from the numerical simulation results. The heads of different species are described as a highly simplified two-part (skull and brain) finite element model with varying geometric parameters. The parameters considered include peak incident pressure, skull thickness, brain radius and snout length. Their interrelationship and coupling effect are discovered by developing a decision tree based on the large simulation data-set. The results show that the proposed data-driven method is superior to the conventional linear regression method and is comparable to the nonlinear regression method. Considering its capability of exploring implicit information and the relatively simple relationships between response and input variables, the data mining method is considered to be a good tool for an in-depth understanding of the mechanisms of blast-induced brain injury. As a general method, this approach can also be applied to other nonlinear complex biomechanical systems.     

Enhanced generation of intraluminal vesicles in neuronal late endosomes in the brain of a Down syndrome mouse model with endosomal dysfunction

Down syndrome (DS) is a human genetic disease caused by trisomy of chromosome 21 and characterized by early developmental brain abnormalities. Dysfunctional endosomal pathway in neurons is an early event of DS and Alzheimer's disease. Recently, we have demonstrated that exosome secretion is upregulated in human DS postmortem brains, in the brain of the trisomic mouse model Ts[Rb(12.17¹⁶)]2Cje (Ts2) and by DS fibroblasts as compared with disomic controls. High levels of the tetraspanin CD63, a regulator of exosome biogenesis, were observed in DS brains. Partially blocking exosome secretion by DS fibroblasts exacerbated a pre‐existing early endosomal pathology. We thus hypothesized that enhanced CD63 expression induces generation of intraluminal vesicles (ILVs) in late endosomes/multivesicular bodies (MVBs), increasing exosome release as an endogenous mechanism to mitigate endosomal abnormalities in DS. Herein, we show a high‐resolution electron microscopy analysis of MVBs in neurons of the frontal cortex of 12‐month‐old Ts2 mice and littermate diploid controls. Our quantitative analysis revealed that Ts2 MVBs are larger, more abundant, and contain a higher number of ILVs per neuron compared to controls. These findings were further corroborated biochemically by Western blot analysis of purified endosomal fractions showing higher levels of ILVs proteins in the same fractions containing endosomal markers in the brain of Ts2 mice compared to controls. These data suggest that upregulation of ILVs production may be a key homeostatic mechanism to alleviate endosomal dysregulation via the endosomal–exosomal pathway.     

Sensitive detection of GFP utilizing tyramide signal amplification to overcome gene silencing

The green fluorescent protein (GFP) is among the most commonly used expression markers in biology. GFP-tagged cells have played a particularly important role in studies of cell lineage. Sensitive detection of GFP is crucially important for such studies to be successful, and problems with detection may account for discrepancies in the literature regarding the possible fate choices of stem cells. Here we describe a very sensitive technique for visualization of GFP. Using it we can detect about 90% of cells of donor origin while we could only see about 50% of these cells when we employ the methods that are in general use in other laboratories. In addition, we provide evidence that some cells permanently silence GFP expression. In the case of the progeny of bone marrow stem cells, it appears that the more distantly related they are to their precursors, the more likely it is that they will turn off the lineage marker.     

Neuronal assemblies: single cortical neurons are obedient members of a huge orchestra

Spontaneous cortical activity of single neurons is often either dismissed as noise, or is regarded as carrying no functional significance and hence is ignored. Our findings suggest that such concepts should be revised. We explored the coherent population activity of neuronal assemblies in primary sensory area in the absence of a sensory input. Recent advances in real-time optical imaging based on voltage-sensitive dyes (VSDI) have facilitated exploration of population activity and its intimate relationship to the activity of individual cortical neurons. It has been shown by in vivo intracellular recordings that the dye signal measures the sum of the membrane potential changes in all the neuronal elements in the imaged area, emphasizing subthreshold synaptic potentials and dendritic action potentials in neuronal arborizations originating from neurons in all cortical layers whose dendrites reach the superficial cortical layers. Thus, the VSDI has allowed us to image the rather illusive activity in neuronal dendrites that cannot be readily explored by single unit recordings. Surprisingly, we found that the amplitude of this type of ongoing subthreshold activity is of the same order of magnitude as evoked activity. We also found that this ongoing activity exhibited high synchronization over many millimeters of cortex. We then investigated the influence of ongoing activity on the evoked response, and showed that the two interact strongly. Furthermore, we found that cortical states that were previously associated only with evoked activity can actually be observed also in the absence of stimulation, for example, the cortical representation of a given orientation may appear without any visual input. This demonstration suggests that ongoing activity may also play a major role in other cortical function by providing a neuronal substrate for the dependence of sensory information processing on context, behavior, memory and other aspects of cognitive function.     

From subgenome analysis to protein structure

Groups of related genes abound in large eukaryotic genomes. In such 'subgenomes', homology modeling carried out for a few genes will probably have relevance to the entire group. Subgenomes also afford unique ways of determining protein structural information. In addition to analyses based on the quantification of residue variability in paralogs, two-way comparisons, both within and among species, help to disclose functional amino acids. Comparative studies of gene families throughout the mammalian genome will also help elucidate the functional significance of single nucleotide polymorphisms in coding regions.     

Coordinate induction of glutathione biosynthesis and glutathione-metabolizing enzymes is correlated with salt tolerance in tomato

The acclimation of reduced glutathione (GSH) biosynthesis and GSH-utilizing enzymes to salt stress was studied in two tomato species that differ in stress tolerance. Salt increased GSH content and GSH:GSSG (oxidized glutathione) ratio in oxidative stress-tolerant Lycopersicon pennellii (Lpa) but not in Lycopersicon esculentum (Lem). These changes were associated with salt-induced upregulation of gamma-glutamylcysteine synthetase protein, an effect which was prevented by preincubation with buthionine sulfoximine. Salt treatment induced glutathione peroxidase and glutathione-S-transferase but not glutathione reductase activities in Lpa. These results suggest a mechanism of coordinate upregulation of synthesis and metabolism of GSH in Lpa, that is absent from Lem.     

A covarion-based method for detecting molecular adaptation: application to the evolution of primate mitochondrial genomes

A new method for detecting site-specific variation of evolutionary rate (the so-called covarion process) from protein sequence data is proposed. It involves comparing the maximum-likelihood estimates of the replacement rate of an amino acid site in distinct subtrees of a large tree. This approach allows detection of covarion at the gene or the amino acid levels. The method is applied to mammalian-mitochondrial-protein sequences. Significant covarion-like evolution is found in the (simian) primate lineage: some amino acid positions are fast-evolving (i.e. unconstrained) in non-primate mammals but slow-evolving (i.e. highly constrained) in primates, and some show the opposite pattern. Our results indicate that the mitochondrial genome of primates reached a new peak of the adaptive landscape through positive selection.     

Regulation of sterol biosynthesis in sunflower by 24(R,S),25-epiminolanosterol, a novel C-24 methyl transferase inhibitor

Whereas sitosterol and 24(28)-methylene cycloartanol were competitive inhibitors (with Ki = 26 microM and 14 microM, respectively), 24(R,S)-25-epiminolanosterol was found to be a potent non-competitive inhibitor (Ki = 3.0 nM) of the S-adenosyl-L-methionine-C-24 methyl transferase from sunflower embryos. Because the ground state analog, 24(R,S)-oxidolanosterol, failed to inhibit the catalysis and 25-azalanosterol inhibited the catalysis with a Ki of 30 nM we conclude that the aziridine functions in a manner similar to the azasteriod (Rahier, A., et al., J. Biol. Chem. (1984) 259, 15215) as a transition state analog mimicking the carbonium intermediate found in the normal transmethylation reaction. Additionally, we observed that the aziridine inhibited cycloartenol metabolism (the preferred substrate for transmethylation) in cultured sunflower cells and cell growth.     

maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments

MOTIVATION: Multi-series time-course microarray experiments are useful approaches for exploring biological processes. In this type of experiments, the researcher is frequently interested in studying gene expression changes along time and in evaluating trend differences between the various experimental groups. The large amount of data, multiplicity of experimental conditions and the dynamic nature of the experiments poses great challenges to data analysis. RESULTS: In this work, we propose a statistical procedure to identify genes that show different gene expression profiles across analytical groups in time-course experiments. The method is a two-regression step approach where the experimental groups are identified by dummy variables. The procedure first adjusts a global regression model with all the defined variables to identify differentially expressed genes, and in second a variable selection strategy is applied to study differences between groups and to find statistically significant different profiles. The methodology is illustrated on both a real and a simulated microarray dataset.