Imaging mass spectrometry for spatial metabolomics

Over the past decade, mass spectrometry (MS) has seen major technical advances that have increased the scope, applicability and adoption of the technology in a vast array of research areas (1)

The metabolic environment of the developing embryo: A multidisciplinary approach on oilseed rapeseed

Brassicaceae seeds consist of three genetically distinct structures: the embryo, endosperm and seed coat, all of which are involved in assimilate allocation during seed development. The complexity of their metabolic interrelations remains unresolved to date. In the present study, we apply state-of-the-art imaging and analytical approaches to assess the metabolic environment of the Brassica napus embryo. Nuclear magnetic resonance imaging (MRI) provided volumetric data on the living embryo and endosperm, revealing how the endosperm envelops the embryo, determining endosperm's priority in assimilate uptake from the seed coat during early development. MRI analysis showed higher levels of sugars in the peripheral endosperm facing the seed coat, but a lower sugar content within the central vacuole and the region surrounding the embryo. Feeding intact siliques with 13C-labeled sucrose allowed tracing of the post-phloem route of sucrose transfer within the seed at the heart stage of embryogenesis, by means of mass spectrometry imaging. Quantification of over 70 organic and inorganic compounds in the endosperm revealed shifts in their abundance over different stages of development, while sugars and potassium were the main determinants of osmolality throughout these stages. Our multidisciplinary approach allows access to the hidden aspects of endosperm metabolism, a task which remains unattainable for the small-seeded model plant Arabidopsis thaliana

Metabolic profiling of a transgenic Caenorhabditis elegans Alzheimer model

Despite decades of research, no early-onset biomarkers are currently available for Alzheimer’s disease, a cureless neurodegenerative disease afflicting millions worldwide. In this study, transgenic Caenorhabditis elegans were used to investigate changes in the metabolome after induced expression of amyloid-β. GC- and LC–MS-based platforms determined a total of 157 differential features. Some of these were identified using in-house (GC–MS) or public libraries (LC–MS), revealing changes in allantoin, cystathionine and tyrosine levels. Since C. elegans is far better suited to metabolomics studies than most other model systems, the accordance of these findings with vertebrate literature is promising and argues for further use of C. elegans as a model of human pathology in the study of AD

QGP Susceptibilities from PNJL Model

An improved version of the PNJL model is used to calculate various thermodynamical quantities, {\it viz.}, quark number susceptibility, isospin susceptibility, specific heat, speed of sound and conformal measure. Comparison with Lattice data is found to be encouraging.Comment: 4 pages, 2 figures, poster presented at Quark Matter'0

Examining a model of anxiety in autistic adults

Anxiety disorders are common in autism. Research studies have identified factors that influence anxiety in autism, such as difficulties with uncertain situations, difficulties understanding own emotions, differences in processing sensory input (related to our senses) and difficulties regulating emotions. To date, a few studies have considered the combination of these factors within the same sample. This study used structural equation modelling to test the contribution of these factors in autism. Autistic (n = 86) and non-autistic adults (n = 100) completed a battery of self-report questionnaires. Only when applied to each group separately, the broad predictions of the model were confirmed for the autistic group. The model confirmed that difficulties with uncertain situations and in regulating emotions play a central role in anxiety in autism. Difficulties understanding own emotions and differences in processing sensory input both contribute to anxiety indirectly through their respective interrelation with the other two factors (difficulties with uncertain situations and in regulating emotions). Importantly, the results imply that sensory processing differences contribute not only indirectly but also directly to individual differences in anxiety. For the non-autistic group, model fit could only be achieved after removing autism-related traits and sensory processing differences as predictors of anxiety. These results suggest that cause/development and expression of anxiety in autism partially overlap with what is observed in the general population except that sensory processing differences appear to play a relatively unique role in the context of autism

Validation of the German Glasgow Sensory Questionnaire and replication of sensory processing differences in students with higher and lower Autism-Spectrum Quotient

Background The Glasgow Sensory Questionnaire (GSQ) gives insight into sensory processing differences (hypo- and hyper-sensitivity across modalities), which is a clinically defining characteristic of autism spectrum disorder (ASD). Because there is no validated German version of this instrument, this study aimed at validating the German GSQ. Further, a replication of the GSQ’s sensory processing differences was intended. Methods University students of Technische Universität or Universitätsklinikum in Dresden, Germany, were recruited via email distribution or the university homepage and 297 German-speaking students completed the online survey, comprising the German GSQ, Autism-Spectrum Quotient (AQ) and Symptom-Checklist (SCL-90). For validation of the German GSQ, confirmatory factor analyses followed by exploratory factor analyses were applied. Results The German GSQ has moderate to low validity, good to acceptable reliability, and a different internal structure from the original GSQ. Replicating the sensory processing differences in students with higher and lower AQ was not successful. Conclusions Results indicate that the GSQ, developed especially for individuals with ASD, is less informative for the general population if there are not enough individuals with higher AQ scores in the sample

A quantitative profiling method of phytohormones and other metabolites applied to barley roots subjected to salinity stress

As integral parts of plant signaling networks, phytohormones are involved in the regulation of plant metabolism and growth under adverse environmental conditions, including salinity. Globally, salinity is one of the most severe abiotic stressors with an estimated 800 million hectares of arable land affected. Roots are the first plant organ to sense salinity in the soil, and are the initial site of sodium (Na + ) exposure. However, the quantification of phytohormones in roots is challenging, as they are often present at extremely low levels compared to other plant tissues. To overcome this challenge, we developed a high-throughput LC-MS method to quantify ten endogenous phytohormones and their metabolites of diverse chemical classes in roots of barley. This method was validated in a salinity stress experiment with six barley varieties grown hydroponically with and without salinity. In addition to phytohormones, we quantified 52 polar primary metabolites, including some phytohormone precursors, using established GC-MS and LC-MS methods. Phytohormone and metabolite data were correlated with physiological measurements including biomass, plant size and chlorophyll content. Root and leaf elemental analysis was performed to determine Na + exclusion and K + retention ability in the studied barley varieties. We identified distinct phytohormone and metabolite signatures as a response to salinity stress in different barley varieties. Abscisic acid increased in the roots of all varieties under salinity stress, and elevated root salicylic acid levels were associated with an increase in leaf chlorophyll content. Furthermore, the landrace Sahara maintained better growth, had lower Na + levels and maintained high levels of the salinity stress linked metabolite putrescine as well as the phytohormone metabolite cinnamic acid, which has been shown to increase putrescine concentrations in previous studies. This study highlights the importance of root phytohormones under salinity stress and the multi-variety analysis provides an important update to analytical methodology, and adds to the current knowledge of salinity stress responses in plants at the molecular level

How large is "large NcN_c" for Nuclear matter?

We argue that a so far neglected dimensionless scale, the number of neighbors in a closely packed system, is relevant for the convergence of the large $N_c$ expansion at high chemical potential. It is only when the number of colors is large w.r.t. this new scale (\sim \order{10}) that a convergent large $N_c$ limit is reached. This provides an explanation as to why the large $N_c$ expansion, qualitatively successful in in vacuum QCD, fails to describe high baryo-chemical potential systems, such as nuclear matter. It also means that phenomenological claims about high density matter based on large $N_c$ extrapolations should be treated with caution.Comment: Proceedings of CPOD2010 conference, in Dubna. Results based on Phys.Rev.C82, 055202 (2010), http://arxiv.org/abs/1006.247

Changes in the crystal lattice parameters of montmorillonite during its modification by cobalt and aluminum cations

The effect the modification (pillarization) of montmorillonite clays from different locations has on the crystallographic lattice parameters of montmorillonite is determined. It is revealed through ultrahigh resolution transmission electron microscopy and analyzing microdiffraction patterns that pillarization raises the distance between montmorillonite structural units to 2.2 nm, while the intracrystal distance between the atoms grows by 0.4 n