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Speech perception requires rapid extraction of the linguistic content from the acoustic signal. The ability to efficiently process rapid changes in auditory information is important for decoding speech and thereby crucial during language acquisition. Investigating functional networks of speech perception in infancy might elucidate neuronal ensembles supporting perceptual abilities that gate language acquisition. Interhemispheric specializations for language have been demonstrated in infants. How these asymmetries are shaped by basic temporal acoustic properties is under debate. We recently provided evidence that newborns process non-linguistic sounds sharing temporal features with language in a differential and lateralized fashion. The present study used the same material while measuring brain responses of 6 and 3 month old infants using simultaneous recordings of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). NIRS reveals that the lateralization observed in newborns remains constant over the first months of life. While fast acoustic modulations elicit bilateral neuronal activations, slow modulations lead to right-lateralized responses. Additionally, auditory-evoked potentials and oscillatory EEG responses show differential responses for fast and slow modulations indicating a sensitivity for temporal acoustic variations. Oscillatory responses reveal an effect of development, that is, 6 but not 3 month old infants show stronger theta-band desynchronization for slowly modulated sounds. Whether this developmental effect is due to increasing fine-grained perception for spectrotemporal sounds in general remains speculative. Our findings support the notion that a more general specialization for acoustic properties can be considered the basis for lateralization of speech perception. The results show that concurrent assessment of vascular based imaging and electrophysiological responses have great potential in the research on language acquisition.
Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures.
Spatial numerical associations (SNAs) are prevalent yet their origin is poorly understood. We first consider the possible prime role of reading habits in shaping SNAs and list three observations that argue against a prominent influence of this role: (1) directional reading habits for numbers may conflict with those for non-numerical symbols, (2) short-term experimental manipulations can overrule the impact of decades of reading experience, (3) SNAs predate the acquisition of reading. As a promising alternative, we discuss behavioral, neuroscientific, and neuropsychological evidence in support of finger counting as the most likely initial determinant of SNAs. Implications of this "manumerical cognition" stance for the distinction between grounded, embodied, and situated cognition are discussed.
SLocX predicting subcellular localization of Arabidopsis proteins leveraging gene expression data
(2011)
Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mito-chondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.
Large-scale co-expression approach to dissect secondary cell wall formation across plant species
(2011)
Plant cell walls are complex composites largely consisting of carbohydrate-based polymers, and are generally divided into primary and secondary walls based on content and characteristics. Cellulose microfibrils constitute a major component of both primary and secondary cell walls and are synthesized at the plasma membrane by cellulose synthase (CESA) complexes. Several studies in Arabidopsis have demonstrated the power of co-expression analyses to identify new genes associated with secondary wall cellulose biosynthesis. However, across-species comparative co-expression analyses remain largely unexplored. Here, we compared co-expressed gene vicinity networks of primary and secondary wall CESAsin Arabidopsis, barley, rice, poplar, soybean, Medicago, and wheat, and identified gene families that are consistently co-regulated with cellulose biosynthesis. In addition to the expected polysaccharide acting enzymes, we also found many gene families associated with cytoskeleton, signaling, transcriptional regulation, oxidation, and protein degradation. Based on these analyses, we selected and biochemically analyzed T-DNA insertion lines corresponding to approximately twenty genes from gene families that re-occur in the co-expressed gene vicinity networks of secondary wall CESAs across the seven species. We developed a statistical pipeline using principal component analysis and optimal clustering based on silhouette width to analyze sugar profiles. One of the mutants, corresponding to a pinoresinol reductase gene, displayed disturbed xylem morphology and held lower levels of lignin molecules. We propose that this type of large-scale co-expression approach, coupled with statistical analysis of the cell wall contents, will be useful to facilitate rapid knowledge transfer across plant species.
Hydrocarbons can be found in many different habitats and represent an important carbon source for microbes. As fossil fuels, they are also an important economical resource and through natural seepage or accidental release they can be major pollutants. DNA-specific stains and molecular probes bind to hydrocarbons, causing massive background fluorescence, thereby hampering cell enumeration. The cell extraction procedure of Kallmeyer et al. (2008) separates the cells from the sediment matrix. In principle, this technique can also be used to separate cells from oily sediments, but it was not originally optimized for this application. Here we present a modified extraction method in which the hydrocarbons are removed prior to cell extraction. Due to the reduced background fluorescence the microscopic image becomes clearer, making cell identification, and enumeration much easier. Consequently, the resulting cell counts from oily samples treated according to our new protocol are significantly higher than those treated according to Kallmeyer et al. (2008). We tested different amounts of a variety of solvents for their ability to remove hydrocarbons and found that n-hexane and in samples containing more mature oils methanol, delivered the best results. However, as solvents also tend to lyse cells, it was important to find the optimum solvent to sample ratio, at which hydrocarbon extraction is maximized and cell lysis minimized. A volumetric ratio of 1:2-1:5 between a formalin-fixed sediment slurry and solvent delivered highest cell counts. Extraction efficiency was around 30-50% and was checked on both oily samples spiked with known amounts of E. coli cells and oil-free samples amended with fresh and biodegraded oil. The method provided reproducible results on samples containing very different kinds of oils with regard to their degree of biodegradation. For strongly biodegraded oil MeOH turned out to be the most appropriate solvent, whereas for less biodegraded samples n-hexane delivered best results.
The domestic cat is the one of the most popular pets throughout the world. A by-product of owning, interacting with, or being in a household with a cat is the transfer of shed fur to clothing or personal objects. As trace evidence, transferred cat fur is a relatively untapped resource for forensic scientists. Both phenotypic and genotypic characteristics can be obtained from cat fur, but databases for neither aspect exist. Because cats incessantly groom, cat fur may have nucleated cells, not only in the hair bulb, but also as epithelial cells on the hair shaft deposited during the grooming process, thereby generally providing material for DNA profiling. To effectively exploit cat hair as a resource, representative databases must be established. The current study evaluates 402 bp of the mtDNA control region (CR) from 1394 cats, including cats from 25 distinct worldwide populations and 26 breeds. Eighty-three percent of the cats are represented by 12 major mitotypes. An additional 8.0% are clearly derived from the major mitotypes. Unique sequences are found in 7.5% of the cats. The overall genetic diversity for this data set is 0.8813 +/- 0.0046 with a random match probability of 11.8%. This region of the cat mtDNA has discriminatory power suitable for forensic application worldwide.
Highly functionalized dimeric triglycerides, such as compound 2, are obtained as minor products besides branched macromolecules from the acyclic triene metathesis (ATMET) polymerization of unsaturated triglycerides such as glyceryl triundec-10-enoate 1 and methyl acrylate (MA) in the presence of the second generation Hoveyda-Grubbs catalyst. The formed amount of interesting products of lower molecular weight during the ATMET reaction depends on the ratio of MA and triglyceride, reaction time, and temperature. We isolated the dimeric metathesis product 2 and synthesized the respective partially hydrogenated dimer 3 regioselectivly in a seven step reaction sequence starting from 10-undecenoic acid 7 and glycerol. Product 3 was unambiguously characterized by (13)C and (1)H NMR and MS as well as the further intermediate products of the seven step reaction including 10,11 bromo-undecanoic acid 8, the respective brominated 1,3-diglyceride 9, the brominated 1,3-triglyceride 6, and the self-metathesis products 4 and 5 which were isolated and purified.
10-Undecenal, derived by pyrolysis and reduction from castor oil, was almost quantitatively transformed into the corresponding aldol condensation product under basic conditions. This alpha,omega-diene monomer was polymerized using acyclic diene metathesis (ADMET) polymerization. In a catalyst screening, four of nine different ruthenium-based metathesis catalysts showed good reactivity under neat conditions at 80 degrees C in the presence of 1,4-benzoquinone and polymers with molecular weights up to 11 kDa were formed. Furthermore, the (1)H NMR spectra showed that the metathesis catalysts tolerate the alpha,beta-unsaturated aldehyde function and due to the addition of benzoquinone, the degree of double bond isomerization was low. Further experiments investigating reduced catalyst amounts (down to 0.2 mol%) and the temperature dependence of these ADMET polymerizations gave also satisfying results for the formation of poly-alpha,beta-unsaturated aldehydes. Moreover, ADMET polymerizations with different amounts of methyl 10-undecenoate as chain-stopper were performed and the integrals of the corresponding (1)H NMR spectra allowed the determination of an absolute degree of polymerization. Finally, a reduction of a poly-alpha,beta-unsaturated aldehyde with sodium borohydride was accomplished. The resulting poly-(allyl alcohol) could be a useful compound in the generation of polymer networks like polyesters, polyurethanes, and polycarbonates and thus be of high interest in materials research.